2.5 CE Credits: JINS Special Issue: INS 50th Anniversary - Neurological Disorders (JINS 23:9-10, 2017): CE Bundle 2

- Discuss major changes in the neuropsychology of epilepsy over the last several decades.
- Describe major scientific advances in research on traumatic brain injury (TBI)
- Describe underlying pathophysiology and biomarker techniques to detect Alzheimer’s disease in its earliest stages.
- Describe current knowledge in the neuropsychological assessment and treatment of cognitive dysfunction in adult and pediatric MS patients.
Target Audience: | Intermediate |
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Availability: | Date Available: 2018-03-19 |
You may obtain CE for this JINS package at any time. | |
Offered for CE | Yes |
Cost | Members $25 |
Non-Members $37.50 | |
Refund Policy | This JINS package is not eligible for refunds |
CE Credits | 2.5 |
The International Neuropsychological Society is celebrating its 50th anniversary (1967-2017). Over the course of these 50 years, members of the society have made great strides in advancing our knowledge of the workings of the human brain both in health and in disease. For the past 2 decades, many of these advances have appeared in the society’s flagship scientific outlet, the Journal of the International Neuropsychological Society. To commemorate the INS 50th anniversary, the two previous JINS editors, Igor Grant and Kathleen Haaland, joined the current editor, Stephen Rao, in organizing this special double issue of JINS. We have invited some of our leading senior investigators, most of whom have served in leadership positions in the INS, to write reviews in their areas of expertise. These reviews are designed to highlight scientific discoveries that have contributed to progress in the field of neuropsychology over the past 50 years. The authors were instructed to selectively discuss landmark discoveries that have had a lasting impact in advancing scientific knowledge rather than to provide comprehensive literature reviews. In addition, the authors were asked to provide their predictions regarding scientific directions of their field over the coming decade.
The papers reflect in a remarkable way the evolution of neuropsychology over the past 5 decades. There is a movement from viewing neurocognitive change from a static anatomic perspective to one that embraces the notion of functional connectivity within neural circuits, and considers how imbalances in circuitry crosstalk may be reflected in the kinds of processes that we neuropsychologists study, for example, executive function, components of memory and attention, and so forth. The field of neuropsychology now interacts with technological advances in structural and functional brain imaging, electrophysiological methods, fluid biomarkers (e.g., cerebral spinal fluid), and genetics, to name a few. The increased emphasis on observational longitudinal designs has provided a more comprehensive understanding of the evolution of neuropsychological disorders. Finally, while neuropsychology has traditionally focused on assessment, each of these reviews also highlight advances made in the treatment of neuropsychological disorders.
We have organized this special issue into four sections: Brain Systems and Assessment, Neurological Disorders, Neuropsychiatric Disorders, and Pediatric Disorders. In the following sections of this introduction, we highlight some of the key take-home messages from these scholarly reviews. It is important to note that all of these invited reviews were peer reviewed and required multiple revisions before acceptance. Another caveat is that we do not pretend to have covered the entire scope of the scientific underpinnings of neuropsychology and we are sure that we have omitted several key research areas in our diverse field. Likewise, we recognize that only a small percentage of our thought leaders in neuropsychology were able to be invited to contribute to this special issue.
In this section, Corballis emphasizes that hemispheric asymmetry exists in great apes as well as humans (although to a lesser extent in the former), is characterized by significant individual variability and complex genetic influences, and encompasses a broader range of functions and associated neural networks than initially thought before more recent neuroimaging studies.
McDonald emphasizes significant developments in our understanding of emotion, including delineation of the neuroanatomical substrates for different aspects of emotion, the influence of emotion on cognitive processes, and the clinical implications of emotion, which necessitate the need to directly examine emotion clinically using newly developed normative procedures.
Verfaellie and Keane discuss a shift toward a more nuanced understanding of the medial temporal lobes (MTL) in human memory and amnesia over the past 30 years. On the one hand, this body of evidence has highlighted that not all types of memory are impaired in patients with MTL lesions. On the other hand, this research has made apparent that the role of the MTL extends beyond the domain of long-term memory, to include working memory, perception, and future thinking.
Dronkers and Baldo emphasize that the study of language has had a major impact on our understanding of brain-behavior relationships. This paper highlights well-known historical case studies with updates using structural MRI and functional imaging in group studies which show that language, like other complex cognitive processes, is dependent upon neural systems rather than single cortical loci.
Stuss and Burgess review how our knowledge of prefrontal functions in the context of neuropsychological assessment has been transformed over the past 50 years with key themes, including development of theoretical frameworks that address the role of prefrontal systems in the organization of human cognition, the importance of naturalistic tests, the emerging integration of functional imaging into clinical practice, and how we might develop new ways to measure executive function to fill existing gaps.
Haaland, Dum, Mutha, Strick, and Troster, a multidisciplinary group of experts in movement and movement disorders, summarize the influence of animal and human studies in showing that the corticospinal tract includes projections from multiple premotor regions as well as the motor cortex, that cognition strongly impacts even what appear to be simple motor skills, and that differential connectivity among cortical, cerebellar, and striatal regions influences normal movement and impairment with movement disorders and cortical lesions.
Casaletto and Heaton identify historical pioneers and their approaches to neuropsychological assessment as well as factors that have influenced neuropsychological interpretation (e.g., normative standards, cultural considerations, quantifying longitudinal change). They also emphasize the importance of enhancing ecological validity and ways that technological advances have impacted assessment.
Hermann, Loring, and Wilson discuss five major paradigm shifts that have occurred within the neuropsychology of epilepsy, including departure from syndrome-specific pathophysiology, bidirectional comorbidities, quality of life, surgical outcomes, and iatrogenic treatment effects. Unlike most other disorders evaluated by neuropsychologists, surgical interventions have played an important role. This review focuses on the neuropsychological consequences of different surgical interventions and the re-emergence of electroencephalography as an important research tool for probing cognitive dysfunction.
Yeates, Levin, and Ponsford highlight progress made through studies of traumatic brain injury in adults and children. The study focuses on contributions of advances in neuroimaging in characterizing the pathophysiology of traumatic brain injury, the impact of non-injury factors on outcomes (pre-morbid factors), and medical and non-medical interventions to improve outcomes.
Bondi, Edmonds, and Salmon survey historical advances in Alzheimer’s disease, beginning with studies profiling the neuropsychological deficits associated with AD and its differentiation from other dementias, identification of specific cognitive mechanisms affected by neuropathological substrates, the shift in focus to the study of prodromal stages of neurodegenerative disease (mild cognitive impairment), and the rise of imaging and other biomarkers to characterize preclinical disease before the development of significant cognitive decline.
Benedict, DeLuca, Enzinger, Geurts, Krupp, and Rao highlight advances made in the areas of neuropathology, neuroimaging, diagnosis, and treatment that pertain to the neuropsychological aspects of multiple sclerosis (MS). This review focuses on the discovery that MS produces pathological lesions of gray matter that have consequences for cognitive functions, the use of multimodal imaging that integrates structural and functional imaging methods to better understand cognitive test performance and functional reserve, screening and comprehensive assessment of cognitive disorders including pediatric MS, and outcome studies in cognitive rehabilitation.
Sullivan shows us how early careful observations of neuropsychological patterns in alcoholism led to modern neuroimaging confirmations and deepening understanding not only of the structural neuroanatomy underlying alcoholism, but also to new appreciation of functional connectivity disruptions. Ongoing studies now hope to relate such functional connectivity changes not only to specific cognitive profiles but also to related deficits in self-regulation, impulse control, and reward processing that are linked to such neurocognitive deficits.
Saloner and Cysique summarize the progress from earliest reports of neurocognitive changes, first reported in 1987, to the delineation of the specific syndromes of HIV-associated neurocognitive disorders (HAND). The authors demonstrate that neuropsychology has led the way in appreciating that the brain continues to be affected by the HIV process despite good control of virus by modern antiretroviral treatments; and they note that the consequences of these persisting mild cognitive disorders include disturbance in quality of life and everyday functioning in those affected by HIV.
Waters and Mayberg present depression as a failure in the coordination of distributed frontal networks, and discuss how differential functional brain responses to different therapies, for example, pharamacotherapy versus cognitive behavioral therapy (CBT), provide for a better understanding of the component elements of depression. They suggest that increases in adaptive functionality of dorsal frontal networks controlling attention and executive function may be specifically targeted by CBT, whereas antidepressant drugs may reduce the hyper-reactivity of ventral corticolimbic structures.
Seidman and Mirsky note that the view of schizophrenia has shifted from one of “functional psychosis” (i.e., with no known brain substrate) to that of a neurodevelopmental disorder. Neuropsychological deficits, once viewed as the result of psychosis, are now thought to be a prodrome of the disorder, since they are found many years before the onset of symptoms and occur in biological relatives who never develop psychosis. They note a steady increase in convergence of neuropsychological, structural, and functional brain mapping toward understanding of the neurodevelopmental events that lead to these symptoms, such as perinatal insults, abnormal neural network organization, faulty pruning, and genetic alterations.
Gonzalez, Pacheco-Colón, Duperrouzel, and Hawes address progress in the field of cannabis use, which was just being born 50 years ago when the INS was founded. The earliest reports were a few experimental cognitive studies and case reports. Now, there is a vast neuropsychological literature and, as with studies on alcoholism and depression, an increased emphasis on structural-functional brain correlates and their relation to neurodevelopmental outcomes. While they note that evidence for persisting adverse effects of moderate marijuana use by adults is inconclusive, there is increasing concern that marijuana may not be so benign in children, adolescents, and extremely heavy cannabis users.
Fein and Helt indicate that the pace of research in autism has accelerated moving from an initial focus on behavior and cognition to advances associated with the incorporation of imaging and genetics. Despite these recent advances, a coherent picture of the syndrome at either a phenotypic or biological level has not emerged. They provide a roadmap for future progress, in which studies include individuals defined by social impairment without regard to repetitive behaviors to form narrowly defined subtypes, focus on characteristics that are less influenced by environmental factors, study children as early as possible thereby minimizing environmental influence, emphasize the longitudinal course, examine the relationship between specific subtypes and environmental risk factors, distinguish between what participants can do and what they typically do, and aggregate large data sets across sites.
Mahone and Denckla review the key literature pertaining to the neuropsychology of attention-deficit hyperactivity disorder (ADHD) over the past 35 years. These include the evolution of the diagnosis, influential theories, landmark treatment studies, and advances in brain mapping techniques, including anatomic, task activation and resting state fMRI, and diffusion tensor imaging. Challenges associated with studying and treating a heterogeneous neurodevelopmental disorder such as ADHD are described, along with an emphasis on associated disorders and conditions and special populations.
Fletcher and Grigorenko make the case that experimental trials of interventions focused on improving academic skills and addressing comorbid conditions are most effective for diagnosing and treating learning disabilities with a particular focus on reading disability. They conclude that neuropsychological assessment needs to move away from a focus on delineation of cognitive skills toward performance-based assessments of academic achievement and comorbid conditions, along with intervention responses that lead directly to evidence-based treatment plans. Finally, they emphasize that the path to further understanding learning disabilities will be strongly influenced by interdisciplinary research that includes the neuropsychologist and links data from cognitive neuroscience with assessment and treatment of these disorders.
Upon reflection of the articles contained within this special issue, we believe members of the INS will be proud of the many scientific accomplishments that have occurred over the past 50 years of our society’s existence. We are also assured that the future will see even greater scientific innovation in the field of neuropsychology. We think you will agree.
On a closing sad note, Larry Seidman, an Associate Editor of JINS and a co-author of the review on schizophrenia in this special issue, died unexpectedly in September 2017. We will miss this valued friend and colleague, who has made such important discoveries in the neuropsychology of mental health research.
This article reviews the major paradigm shifts that have occurred in the area of the application of clinical and experimental neuropsychology to epilepsy and epilepsysurgery since the founding of the International Neuropsychological Society. The five paradigm shifts discussed include: 1) The neurobiology of cognitive disordersin epilepsy – expanding the landscape of syndrome-specific neuropsychological impairment; 2) pathways to comorbidities: bidirectional relationships and their clinicalimplications; 3) discovering quality of life: The concept, its quantification and applicability; 4) outcomes of epilepsy surgery: challenging conventional wisdom;and 5) Iatrogenic effects of treatment: cognitive and behavioral effects of antiepilepsy drugs. For each area we characterize the status of knowledge, the key developmentsthat have occurred, and how they have altered our understanding of the epilepsies and their management. We conclude with a brief overview of where we believe the fieldwill be headed in the next decade which includes changes in assessment paradigms, moving from characterization of comorbidities to interventions; increasing developmentof new measures, terminology and classification; increasing interest in neurodegenerative proteins; transitioning from clinical seizure features to modifiable riskfactors; and neurobehavioral phenotypes. Overall, enormous progress has been made over the lifespan of the INS with promise of ongoing improvements in understandingof the cognitive and behavioral complications of the epilepsies and their treatment. (JINS, 2017, 23, 791–805)
- Abbott, D.F., Waites, A.B., Lillywhite, L.M., & Jackson, G.D. (2010). fMRI assessment of language lateralization: An objective approach. NeuroImage, 50(4), 1446–1455. doi: 10.1016/j.neuroimage.2010.01.059 CrossRef Google Scholar
- Adams, J., Alipio-Jocson, V., Inoyama, K., Bartlett, V., Sandhu, S., Oso, J., & Meador, K. (2017). Methylphenidate, cognition, and epilepsy: A double-blind, placebo-controlled, single-dose study. Neurology, 88(5), 470–476. doi: 10.1212/WNL.0000000000003564 CrossRef Google Scholar PubMed
- Agah, E., Asgari-Rad, N., Ahmadi, M., Tafakhori, A., & Aghamollaii, V. (2017). Evaluating executive function in patients with temporal lobe epilepsy using the frontal assessment battery. Epilepsy Research, 133, 22–27. doi: 10.1016/j.eplepsyres.2017.03.011 CrossRef Google Scholar PubMed
- Alhusaini, S., Doherty, C.P., Scanlon, C., Ronan, L., Maguire, S., Borgulya, G., & Cavalleri, G.L. (2012). A cross-sectional MRI study of brain regional atrophy and clinical characteristics of temporal lobe epilepsy with hippocampal sclerosis. Epilepsy Research, 99(1-2), 156–166. doi: 10.1016/j.eplepsyres.2011.11.005 CrossRef Google Scholar PubMed
- Alhusaini, S., Whelan, C.D., Doherty, C.P., Delanty, N., Fitzsimons, M., & Cavalleri, G.L. (2016). Temporal cortex morphology in mesial temporal lobe epilepsy patients and their asymptomatic siblings. Cerebral Cortex, 26, 1234–1241. doi: 10.1093/cercor/bhu315 CrossRef Google Scholar PubMed
- Aronu, A.E., & Iloeje, S.O. (2011). Behavioral problems of siblings of epileptic children in Enugu. Nigerian Journal of Clinical Practice, 14(2), 132–136. doi: 10.4103/1119-3077.84000 CrossRef Google Scholar PubMed
- Austin, J.K., Harezlak, J., Dunn, D.W., Huster, G.A., Rose, D.F., & Ambrosius, W.T. (2001). Behavior problems in children before first recognized seizures. Pediatrics, 107(1), 115–122. CrossRef Google Scholar PubMed
- Badawy, R.A., Vogrin, S.J., Lai, A., & Cook, M.J. (2013). Capturing the epileptic trait: Cortical excitability measures in patients and their unaffected siblings. Brain, 136(Pt 4), 1177–1191. doi: 10.1093/brain/awt047 CrossRef Google Scholar PubMed
- Baker, G.A. (1998). Quality of life and epilepsy: The Liverpool experience. Clinical Therapeutics, 20(Suppl A), A2–A12. CrossRef Google Scholar PubMed
- Baker, G.A., Jacoby, A., Buck, D., Stalgis, C., & Monnet, D. (1997). Quality of life of people with epilepsy: A European study. Epilepsia, 38(3), 353–362. CrossRef Google Scholar PubMed
- Baker, G.A., Smith, D.F., Dewey, M., Jacoby, A., & Chadwick, D.W. (1993). The initial development of a health-related quality of life model as an outcome measure in epilepsy. Epilepsy Research, 16(1), 65–81. CrossRef Google Scholar PubMed
- Baker, G.A., Taylor, J., Aldenkamp, A.P., & SANAD group. (2011). Newly diagnosed epilepsy: Cognitive outcome after 12 months. Epilepsia, 52(6), 1084–1091. doi: 10.1111/j.1528-1167.2011.03043.x CrossRef Google Scholar PubMed
- Barnes, D.E., & Yaffe, K. (2011). The projected effect of risk factor reduction on Alzheimer’s disease prevalence. Lancet Neurology, 10(9), 819–828. doi: 10.1016/S1474-4422(11)70072-2 CrossRef Google Scholar PubMed
- Barr, W.B. (1997). Examining the right temporal lobe’s role in nonverbal memory. Brain and Cognition, 35, 26–41. CrossRef Google Scholar PubMed
- Baxendale, S., McGrath, K., Donnachie, E., Wintle, S., Thompson, P., & Heaney, D. (2015). The role of obesity in cognitive dysfunction in people with epilepsy. Epilepsy & Behavior, 45, 187–190. doi: 10.1016/j.yebeh.2015.01.032 CrossRef Google Scholar PubMed
- Baxendale, S. (2009). The Wada test. Current Opinion in Neurology, 22(2), 185–189. doi: 10.1097/WCO.0b013e328328f32e CrossRef Google Scholar PubMed
- Baxendale, S., Sisodiya, S.M., Thompson, P.J., Free, S.L., Kitchen, N.D., Stevens, J.M., & Shorvon, S.D. (1999). Disproportion in the distribution of gray and white matter: Neuropsychological correlates. Neurology, 52(2), 248–252. CrossRef Google Scholar PubMed
- Baxendale, S., & Thompson, P. (2010). Beyond localization: The role of traditional neuropsychological tests in an age of imaging. Epilepsia, 51(11), 2225–2230. doi: 10.1111/j.1528-1167.2010.02710.x CrossRef Google Scholar
- Baxendale, S.A., Thompson, P.J., & Duncan, J.S. (2008). Evidence-based practice: A reevaluation of the intracarotid amobarbital procedure (Wada test). Archives of Neurology, 65(6), 841–845. doi: 10.1001/archneur.65.6.841 CrossRef Google Scholar
- Bell, B., Lin, J.J., Seidenberg, M., & Hermann, B. (2011). The neurobiology of cognitive disorders in temporal lobe epilepsy. Nature Reviews. Neurology, 7(3), 154–164. doi: 10.1038/nrneurol.2011.3 CrossRef Google Scholar PubMed
- Bell, B.D., Hermann, B.P., Woodard, A.R., Jones, J.E., Rutecki, P.A., Sheth, R., & Seidenberg, M. (2001). Object naming and semantic knowledge in temporal lobe epilepsy. Neuropsychology, 15(4), 434–443. CrossRef Google Scholar PubMed
- Benke, T., Kuen, E., Schwarz, M., & Walser, G. (2013). Proper name retrieval in temporal lobe epilepsy: Naming of famous faces and landmarks. Epilepsy Behavior, 27(2), 371–377. doi: 10.1016/j.yebeh.2013.02.013 CrossRef Google Scholar PubMed
- Berg, A.T., Berkovic, S.F., Brodie, M.J., Buchhalter, J., Cross, J.H., van Emde Boas, W., & Scheffer, I.E. (2010). Revised terminology and concepts for organization of seizures and epilepsies: Report of the ILAE Commission on Classification and Terminology, 2005-2009. Epilepsia, 51(4), 676–685. doi: 10.1111/j.1528-1167.2010.02522.x CrossRef Google Scholar PubMed
- Berg, A.T., Smith, S.N., Frobish, D., Levy, S.R., Testa, F.M., Beckerman, B., && Shinnar, S. (2005). Special education needs of children with newly diagnosed epilepsy. Developmental Medicine & Child Neurology, 47(11), 749–753. CrossRef Google Scholar PubMed
- Berl, M.M., Zimmaro, L.A., Khan, O.I., Dustin, I., Ritzl, E., Duke, E.S., & Gaillard, W.D. (2014). Characterization of atypical language activation patterns in focal epilepsy. Annals of Neurology, 75(1), 33–42. doi: 10.1002/ana.24015 CrossRef Google Scholar PubMed
- Bernhardt, B.C., Hong, S.J., Bernasconi, A., & Bernasconi, N. (2015). Magnetic resonance imaging pattern learning in temporal lobe epilepsy: Classification and prognostics. Annals of Neurology, 77(3), 436–446. doi: 10.1002/ana.24341 CrossRef Google Scholar PubMed
- Binder, J.R., Swanson, S.J., Hammeke, T.A., Morris, G.L., Mueller, W.M., Fischer, M., & Haughton, V.M. (1996). Determination of language dominance using functional MRI: A comparison with the Wada test. Neurology, 46(4), 978–984. CrossRef Google Scholar PubMed
- Binder, J.R., Swanson, S.J., Sabsevitz, D.S., Hammeke, T.A., Raghavan, M., & Mueller, W.M. (2010). A comparison of two fMRI methods for predicting verbal memory decline after left temporal lobectomy: Language lateralization versus hippocampal activation asymmetry. Epilepsia, 51(4), 618–626. doi: EPI2340 [pii]10.1111/j.1528-1167.2009.02340.x [doi] CrossRef Google Scholar PubMed
- Bladin, P.F. (1992). Psychosocial difficulties and outcome after temporal lobectomy. Epilepsia, 33(5), 898–907. CrossRef Google Scholar PubMed
- Blanc, F., Martinian, L., Liagkouras, I., Catarino, C., Sisodiya, S.M., & Thom, M. (2011). Investigation of widespread neocortical pathology associated with hippocampal sclerosis in epilepsy: A postmortem study. Epilepsia, 52(1), 10–21. doi: 10.1111/j.1528-1167.2010.02773.x CrossRef Google Scholar PubMed
- Bonelli, S.B., Powell, R.H., Yogarajah, M., Samson, R.S., Symms, M.R., Thompson, P.J., & Duncan, J.S. (2010). Imaging memory in temporal lobe epilepsy: Predicting the effects of temporal lobe resection. Brain, 133(Pt 4), 1186–1199. doi: awq006 [pii]10.1093/brain/awq006 [doi] CrossRef Google Scholar PubMed
- Braakman, H.M., Ijff, D.M., Vaessen, M.J., Debeij-van Hall, M.H., Hofman, P.A., Backes, W.H., & Aldenkamp, A.P. (2012). Cognitive and behavioural findings in children with frontal lobe epilepsy. European Journal of Paediatric Neurology, 16(6), 707–715. doi: 10.1016/j.ejpn.2012.05.003 CrossRef Google Scholar PubMed
- Braakman, H.M., Vaessen, M.J., Jansen, J.F., Debeij-van Hall, M.H., de Louw, A., Hofman, P.A., & Backes, W.H. (2014). Pediatric frontal lobe epilepsy: White matter abnormalities and cognitive impairment. Acta Neurologica Scandinavica, 129(4), 252–262. doi: 10.1111/ane.12183 CrossRef Google Scholar PubMed
- Braakman, H.M., Vaessen, M.J., Jansen, J.F., Debeij-van Hall, M.H., de Louw, A., Hofman, P.A., & Backes, W.H. (2015). Aetiology of cognitive impairment in children with frontal lobe epilepsy. Acta Neurologica Scandinavica, 131(1), 17–29. doi: 10.1111/ane.12283 CrossRef Google Scholar PubMed
- Breuer, L.E., Grevers, E., Boon, P., Bernas, A., Bergmans, J.W., Besseling, R.M., & Aldenkamp, A.P. (2017). Cognitive deterioration in adult epilepsy: Clinical characteristics of “Accelerated Cognitive Ageing”. Acta Neurologica Scandinavica, 136, 47–53. doi: 10.1111/ane.12700 CrossRef Google Scholar PubMed
- Brodie, M.J., Mintzer, S., Pack, A.M., Gidal, B.E., Vecht, C.J., & Schmidt, D. (2013). Enzyme induction with antiepileptic drugs: Cause for concern? Epilepsia, 54(1), 11–27. doi: 10.1111/j.1528-1167.2012.03671.x CrossRef Google Scholar PubMed
- Busch, R.M., Floden, D.P., Prayson, B., Chapin, J.S., Kim, K.H., Ferguson, L., & Najm, I.M. (2016). Estimating risk of word-finding problems in adults undergoing epilepsy surgery. Neurology, 87(22), 2363–2369. doi: 10.1212/WNL.0000000000003378 CrossRef Google Scholar PubMed
- Busch, R.M., Frazier, T.W., Iampietro, M.C., Chapin, J.S., & Kubu, C.S. (2009). Clinical utility of the Boston Naming Test in predicting ultimate side of surgery in patients with medically intractable temporal lobe epilepsy: A double cross-validation study. Epilepsia, 50(5), 1270–1273. doi: 10.1111/j.1528-1167.2008.01865.x CrossRef Google Scholar PubMed
- Caller, T.A., Ferguson, R.J., Roth, R.M., Secore, K.L., Alexandre, F.P., Zhao, W., & Jobst, B.C. (2016). A cognitive behavioral intervention (HOBSCOTCH) improves quality of life and attention in epilepsy. Epilepsy Behavior, 57(Pt A), 111–117. doi: 10.1016/j.yebeh.2016.01.024 CrossRef Google Scholar PubMed
- Chang, Y.A., Kemmotsu, N., Leyden, K.M., Kucukboyaci, N.E., Iragui, V.J., Tecoma, E.S., & McDonald, C.R. (2017). Multimodal imaging of language reorganization in patients with left temporal lobe epilepsy. Brain and Language, 170, 82–92. doi: 10.1016/j.bandl.2017.03.012 CrossRef Google Scholar PubMed
- Chelune, G.J. (1995). Hippocampal adequacy versus functional reserve: Predicting memory functions following temporal lobectomy. Archives of Clinical Neuropsychology, 10(5), 413–432. doi: 0887-6177(95)00015-V [pii] CrossRef Google Scholar PubMed
- Chowdhury, F.A., Elwes, R.D., Koutroumanidis, M., Morris, R.G., Nashef, L., & Richardson, M.P. (2014). Impaired cognitive function in idiopathic generalized epilepsy and unaffected family members: An epilepsy endophenotype. Epilepsia, 55(6), 835–840. doi: 10.1111/epi.12604 CrossRef Google Scholar PubMed
- Coras, R., Pauli, E., Li, J., Schwarz, M., Rossler, K., Buchfelder, M., & Blumcke, I. (2014). Differential influence of hippocampal subfields to memory formation: Insights from patients with temporal lobe epilepsy. Brain, 137(Pt 7), 1945–1957. doi: 10.1093/brain/awu100 CrossRef Google Scholar PubMed
- Dabbs, K., Jones, J., Seidenberg, M., & Hermann, B. (2009). Neuroanatomical correlates of cognitive phenotypes in temporal lobe epilepsy. Epilepsy & Behavior, 15, 445–451. CrossRef Google Scholar PubMed
- Daviglus, M.L., Bell, C.C., Berrettini, W., Bowen, P.E., Connolly, E.S. Jr., Cox, N.J., & Trevisan, M. (2010). NIH state-of-the-science conference statement: Preventing Alzheimer’s disease and cognitive decline. NIH Consens and State-of-the-Science Statements, 27(4), 1–30. Google Scholar PubMed
- Del Felice, A., Alderighi, M., Martinato, M., Grisafi, D., Bosco, A., Thompson, P.J., & Masiero, S. (2017). Memory rehabilitation strategies in nonsurgical temporal lobe epilepsy: A review. American Journal of Physical Medicine & Rehabilitation, doi: 10.1097/PHM.0000000000000714 CrossRef Google Scholar
- Devinsky, O., Vickrey, B.G., Cramer, J., Perrine, K., Hermann, B., Meador, K., & Hays, R.D. (1995). Development of the quality of life in epilepsy inventory. Epilepsia, 36(11), 1089–1104. CrossRef Google Scholar PubMed
- Djordjevic, J. (2011). Inquiry on assessments across epilepsy centers in different cultures. In C. Helmstaedter, B. Hermann, M. Lassonde, P. Kahane & A. Arzimanoglou (Eds.), Progress in epilepstic disorders: Neuropsychology in the care of people with epilepsy. (Vol. 11, pp. 13–26). Montrouge, France: John Libbey Eurotext. Google Scholar
- Dodrill, C.B., Batzel, L.W., Queisser, H.R., & Temkin, N.R. (1980). An objective method for the assessment of psychological and social problems among epileptics. Epilepsia, 21(2), 123–135. CrossRef Google Scholar PubMed
- Dodrill, C.B., & Matthews, C.G. (1992). The role of neuropsychology in the assessment and treatment of persons with epilepsy. The American Psychologist, 47(9), 1139–1142. CrossRef Google Scholar PubMed
- Dodrill, C.B., & Troupin, A.S. (1977). Psychotropic effects of carbamazepine in epilepsy: A double-blind comparison with phenytoin. Neurology, 27(11), 1023–1028. CrossRef Google Scholar PubMed
- Doucet, G.E., Rider, R., Taylor, N., Skidmore, C., Sharan, A., Sperling, M., && Tracy, J.I. (2015). Presurgery resting-state local graph-theory measures predict neurocognitive outcomes after brain surgery in temporal lobe epilepsy. Epilepsia, 56(4), 517–526. doi: 10.1111/epi.12936 CrossRef Google Scholar PubMed
- Drane, D.L., Ojemann, G.A., Aylward, E., Ojemann, J.G., Johnson, L.C., Silbergeld, D.L., & Tranel, D. (2008). Category-specific naming and recognition deficits in temporal lobe epilepsy surgical patients. Neuropsychologia, 46(5), 1242–1255. doi: S0028-3932(07)00412-5 [pii]10.1016/j.neuropsychologia.2007.11.034 [doi] CrossRef Google Scholar PubMed
- Drane, D.L., Ojemann, J.G., Phatak, V., Loring, D.W., Gross, R.E., Hebb, A.O., & Tranel, D. (2013). Famous face identification in temporal lobe epilepsy: Support for a multimodal integration model of semantic memory. Cortex, 49(6), 1648–1667. doi: 10.1016/j.cortex.2012.08.009 CrossRef Google Scholar PubMed
- Elger, C.E., Helmstaedter, C., & Kurthen, M. (2004). Chronic epilepsy and cognition. Lancet Neurology, 3(11), 663–672. CrossRef Google Scholar PubMed
- Engel, J. (1987). Outcome with respect to epileptic seizures. In J. Engel, Jr. (Ed.), Surgical treatment of the epilepsies (pp. 553–571). New York, NY: Raven Press. Google Scholar PubMed
- Engel, J. (1993). Surgical treatment of the epilepsies (2nd ed.). New York: Raven Press. Google Scholar PubMed
- Farina, E., Raglio, A., & Giovagnoli, A.R. (2015). Cognitive rehabilitation in epilepsy: An evidence-based review. Epilepsy Research, 109, 210–218. doi: 10.1016/j.eplepsyres.2014.10.017 CrossRef Google Scholar
- Farwell, J.R., Lee, Y.J., Hirtz, D.G., Sulzbacher, S.I., Ellenberg, J.H., & Nelson, K.B. (1990). Phenobarbital for febrile seizures--Effects on intelligence and on seizure recurrence. New England Journal of Medicine, 322(6), 364–369. doi: 10.1056/NEJM199002083220604 CrossRef Google Scholar PubMed
- Fastenau, P.S., Johnson, C.S., Perkins, S.M., Byars, A.W., deGrauw, T.J., Austin, J.K., && Dunn, D.W. (2009). Neuropsychological status at seizure onset in children: Risk factors for early cognitive deficits. Neurology, 73(7), 526–534. doi: WNL.0b013e3181b23551[pii]10.1212/WNL.0b013e3181b23551 [doi] CrossRef Google Scholar PubMed
- Folsom, A. (1952). Psychological testing in epilepsy. Epilepsia, 1, 15–22. Google Scholar
- Forsgren, L., & Nystrom, L. (1990). An incident case-referent study of epileptic seizures in adults. Epilepsy Research, 6(1), 66–81. CrossRef Google Scholar PubMed
- Gaillard, W.D., Balsamo, L., Xu, B., McKinney, C., Papero, P.H., Weinstein, S., & Theodore, W.H. (2004). fMRI language task panel improves determination of language dominance. Neurology, 63(8), 1403–1408. CrossRef Google Scholar PubMed
- Gaitatzis, A., Sisodiya, S.M., & Sander, J.W. (2012). The somatic comorbidity of epilepsy: A weighty but often unrecognized burden. Epilepsia, 53(8), 1282–1293. doi: 10.1111/j.1528-1167.2012.03528.x CrossRef Google Scholar PubMed
- Gandy, M., Sharpe, L., & Perry, K.N. (2013). Cognitive behavior therapy for depression in people with epilepsy: A systematic review. Epilepsia, 54(10), 1725–1734. doi: 10.1111/epi.12345 CrossRef Google Scholar PubMed
- Gilliam, F., Kuzniecky, R., Meador, K., Martin, R., Sawrie, S., Viikinsalo, M., & Faught, E. (1999). Patient-oriented outcome assessment after temporal lobectomy for refractory epilepsy. Neurology, 53(4), 687–694. CrossRef Google Scholar PubMed
- Giovagnoli, A.R. (2014). The importance of theory of mind in epilepsy. Epilepsy & Behavior, 39, 145–153. doi: 10.1016/j.yebeh.2014.05.021 CrossRef Google Scholar PubMed
- Glauser, T.A., Cnaan, A., Shinnar, S., Hirtz, D.G., Dlugos, D., & Masur, D., … Childhood Absence Epilepsy Study Group. (2010). Ethosuximide, valproic acid, and lamotrigine in childhood absence epilepsy. New England Journal of Medicine, 362(9), 790–799. doi: 10.1056/NEJMoa0902014 CrossRef Google Scholar PubMed
- Glosser, G., Cole, L.C., French, J.A., Saykin, A.J., & Sperling, M.R. (1997). Predictors of intellectual performance in adults with intractable temporal lobe epilepsy. Journal of the International Neuropsychological Society, 3(3), 252–259. Google Scholar PubMed
- Guimaraes, C.A., Li, L.M., Rzezak, P., Fuentes, D., Franzon, R.C., Augusta Montenegro, M., & Guerreiro, M.M. (2007). Temporal lobe epilepsy in childhood: Comprehensive neuropsychological assessment. Journal of Child Neurology, 22(7), 836–840. doi: 22/7/836 [pii]10.1177/0883073807304701 [doi] CrossRef Google Scholar PubMed
- Hamberger, M.J., & Cole, J. (2011). Language organization and reorganization in epilepsy. Neuropsychological Review, 21(3), 240–251. doi: 10.1007/s11065-011-9180-z CrossRef Google Scholar PubMed
- Hamed, S.A. (2014). Atherosclerosis in epilepsy: Its causes and implications. Epilepsy & Behavior, 41, 290–296. doi: 10.1016/j.yebeh.2014.07.003 CrossRef Google Scholar PubMed
- Hamed, S.A. (2015). Antiepileptic drugs influences on body weight in people with epilepsy. Expert Review of Clinical Pharmacology, 8(1), 103–114. doi: 10.1586/17512433.2015.991716 CrossRef Google Scholar PubMed
- Harnod, T., Chen, H.J., Li, T.C., Sung, F.C., & Kao, C.H. (2014). A high risk of hyperlipidemia in epilepsy patients: A nationwide population-based cohort study. Annals of Epidemiology, 24(12), 910–914. doi: 10.1016/j.annepidem.2014.09.008 CrossRef Google Scholar PubMed
- Helmstaedter, C., & Witt, J.A. (2012). Clinical neuropsychology in epilepsy: Theoretical and practical issues. Handbook of Clinical Neurology, 107, 437–459. doi: 10.1016/B978-0-444-52898-8.00036-7 CrossRef Google Scholar PubMed
- Hermann, B.P., Lin, J.J., Jones, J.E., & Seidenberg, M. (2009). The emerging architecture of neuropsychological impairment in epilepsy. Neurology Clinics, 27(4), 881–907. doi: 10.1016/j.ncl.2009.08.001 CrossRef Google Scholar PubMed
- Hermann, B.P., Seidenberg, M., Bell, B., Rutecki, P., Sheth, R.D., Wendt, G., & Magnotta, V. (2003). Extratemporal quantitative MR volumetrics and neuropsychological status in temporal lobe epilepsy. Journal of the International Neuropsychological Society, 9(3), 353–362. doi: 10.1017/S1355617703930013 [doi]S1355617703930013 [pii] CrossRef Google Scholar
- Hermann, B.P., & Stone, J.L. (1989). A historical review of the epilepsy surgery program at the University of Illinois Medical Center: The contributions of Bailey, Gibbs, and collaborators to the refinement of anterior temporal lobectomy. Journal of Epilepsy, 2, 155–163. CrossRef Google Scholar
- Hermann, B.P., Wyler, A.R., Somes, G., Berry, A.D. III, & Dohan, F.C. Jr. (1992). Pathological status of the mesial temporal lobe predicts memory outcome from left anterior temporal lobectomy. Neurosurgery, 31(4), 652–656; discussion 656–657. Google Scholar PubMed
- Hermann, B.P., Zhao, Q., Jackson, D.C., Jones, J.E., Dabbs, K., Almane, D., & Rathouz, P.J. (2016). Cognitive phenotypes in childhood idiopathic epilepsies. Epilepsy & Behavior, 61, 269–274. doi: 10.1016/j.yebeh.2016.05.013 CrossRef Google Scholar PubMed
- Hesdorffer, D.C. (2016). Comorbidity between neurological illness and psychiatric disorders. CNS Spectrums, 21(3), 230–238. doi: 10.1017/S1092852915000929 CrossRef Google Scholar PubMed
- Hesdorffer, D.C., Caplan, R., & Berg, A.T. (2012). Familial clustering of epilepsy and behavioral disorders: Evidence for a shared genetic basis. Epilepsia, 53(2), 301–307. doi: 10.1111/j.1528-1167.2011.03351.x CrossRef Google Scholar PubMed
- Hesdorffer, D.C., Hauser, W.A., Annegers, J.F., & Cascino, G. (2000). Major depression is a risk factor for seizures in older adults. Annals of Neurology, 47(2), 246–249.3.0.CO;2-E>CrossRef Google Scholar PubMed
- Ho, N., & Lee, T. (2011). Developing epilepsy-specific international cognitive assessment: Approaches, opportunities, and limitations. In C. Helmstaedter, B. Hermann, M. Lassonde, P. Kahane, & A. Arzimanoglou (Eds.), Progress in epileptic disorders: Neuropsychology in the care of people with epilespy (Vol. 11, pp. 47–56). Montrouge, France: John Libbey Eurotext. Google Scholar
- Hoare, P. (1984). The development of psychiatric disorder among schoolchildren with epilepsy. Developmental Medicine and Child Neurology, 26(1), 3–13. CrossRef Google Scholar PubMed
- Iqbal, N., Caswell, H., Muir, R., Cadden, A., Ferguson, S., Mackenzie, H., & Duncan, S. (2015). Neuropsychological profiles of patients with juvenile myoclonic epilepsy and their siblings: An extended study. Epilepsia, 56(8), 1301–1308. doi: 10.1111/epi.13061 CrossRef Google Scholar
- Iqbal, N., Caswell, H.L., Hare, D.J., Pilkington, O., Mercer, S., & Duncan, S. (2009). Neuropsychological profiles of patients with juvenile myoclonic epilepsy and their siblings: A preliminary controlled experimental video-EEG case series. Epilepsy & Behavior, 14(3), 516–521. doi: 10.1016/j.yebeh.2008.12.025 CrossRef Google Scholar PubMed
- Jackson, C.F., Makin, S.M., & Baker, G.A. (2015). Neuropsychological and psychological interventions for people with newly diagnosed epilepsy. Cochrane Database System Reviews, (7), CD011311. doi: 10.1002/14651858.CD011311.pub2 Google Scholar PubMed
- Jacoby, A., Snape, D., & Baker, G.A. (2009). Determinants of quality of life in people with epilepsy. Neurology Clinics, 27(4), 843–863. doi: 10.1016/j.ncl.2009.06.003 CrossRef Google Scholar PubMed
- Jobst, B.C., & MEW network. (2017). A common vision and the power of collaboration: The Managing Epilepsy Well Network (MEW). Epilepsy & Behavior, 69, 184–185. doi: 10.1016/j.yebeh.2017.01.023 CrossRef Google Scholar
- Jones, J.E., Blocher, J.B., & Jackson, D.C. (2013). Life outcomes of anterior temporal lobectomy: Serial long-term follow-up evaluations. Neurosurgery, 73(6), 1018–1025. doi: 10.1227/NEU.0000000000000145 CrossRef Google Scholar PubMed
- Jones-Gotman, M., Smith, M.L., Risse, G.L., Westerveld, M., Swanson, S.J., Giovagnoli, A.R., & Piazzini, A. (2010). The contribution of neuropsychology to diagnostic assessment in epilepsy. Epilepsy & Behavior, 18(1-2), 3–12. doi: 10.1016/j.yebeh.2010.02.019 CrossRef Google Scholar PubMed
- Joutsa, J., Rinne, J.O., Hermann, B., Karrasch, M., Anttinen, A., Shinnar, S., && Sillanpaa, M. (2017). Association between childhood-onset epilepsy and amyloid burden 5 decades later. JAMA Neurology, 74(5), 583–590. doi: 10.1001/jamaneurol.2016.6091 CrossRef Google Scholar PubMed
- Kanner, A.M. (2012). Can neurobiological pathogenic mechanisms of depression facilitate the development of seizure disorders? Lancet Neurology, 11(12), 1093–1102. doi: 10.1016/S1474-4422(12)70201-6 CrossRef Google Scholar PubMed
- Kanner, A.M., Barry, J.J., Gilliam, F., Hermann, B., & Meador, K.J. (2010). Anxiety disorders, subsyndromic depressive episodes, and major depressive episodes: Do they differ on their impact on the quality of life of patients with epilepsy? Epilepsia, 51(7), 1152–1158. doi: 10.1111/j.1528-1167.2010.02582.x CrossRef Google Scholar PubMed
- Keezer, M.R., Sisodiya, S.M., & Sander, J.W. (2016). Comorbidities of epilepsy: Current concepts and future perspectives. Lancet Neurology, 15(1), 106–115. doi: 10.1016/S1474-4422(15)00225-2 CrossRef Google Scholar PubMed
- Keller, S.S., Baker, G., Downes, J.J., & Roberts, N. (2009). Quantitative MRI of the prefrontal cortex and executive function in patients with temporal lobe epilepsy. Epilepsy & Behavior, 15, 186–195. CrossRef Google Scholar PubMed
- Keller, S.S., O’Muircheartaigh, J., Traynor, C., Towgood, K., Barker, G.J., & Richardson, M.P. (2014). Thalamotemporal impairment in temporal lobe epilepsy: A combined MRI analysis of structure, integrity, and connectivity. Epilepsia, 55(2), 306–315. doi: 10.1111/epi.12520 CrossRef Google Scholar PubMed
- Keller, S.S., Richardson, M.P., O’Muircheartaigh, J., Schoene-Bake, J.C., Elger, C., & Weber, B. (2015). Morphometric MRI alterations and postoperative seizure control in refractory temporal lobe epilepsy. Human Brain Mapping, 36(5), 1637–1647. doi: 10.1002/hbm.22722 CrossRef Google Scholar PubMed
- Keller, S.S., & Roberts, N. (2008). Voxel-based morphometry of temporal lobe epilepsy: An introduction and review of the literature. Epilepsia, 49(5), 741–757. CrossRef Google Scholar PubMed
- Kobau, R., Zahran, H., Thurman, D.J., Zack, M.M., Henry, T.R., Schachter, S.C., … CDC. (2008). Epilepsy surveillance among adults--19 States, Behavioral Risk Factor Surveillance System, 2005. Morbidity and Mortality Weekly Report. Surveillance Summaries, 57(6), 1–20. Google Scholar PubMed
- Lencz, T., McCarthy, G., Bronen, R.A., Scott, T.M., Inserni, J.A., Sass, K.J., & Spencer, D.D. (1992). Quantitative magnetic resonance imaging in temporal lobe epilepsy: Relationship to neuropathology and neuropsychological function. Annals of Neurology, 31(6), 629–637. CrossRef Google Scholar PubMed
- Levav, M., Mirsky, A.F., Herault, J., Xiong, L., Amir, N., & Andermann, E. (2002). Familial association of neuropsychological traits in patients with generalized and partial seizure disorders. Journal of Clinical and Experimental Neuropsychology, 24(3), 311–326. doi: 10.1076/jcen.24.3.311.985 CrossRef Google Scholar PubMed
- Lin, Mula, M., & Hermann, B.P. (2012). Uncovering the neurobehavioural comorbidities of epilepsy over the lifespan. Lancet, 380(9848), 1180–1192. doi: https://doi.org/10.1016/s0140-6736(12)61455-x CrossRef Google Scholar PubMed
- Lin, J.J., Salamon, N., Lee, A.D., Dutton, R.A., Geaga, J.A., Hayashi, K.M., & Thompson, P.M. (2007). Reduced neocortical thickness and complexity mapped in mesial temporal lobe epilepsy with hippocampal sclerosis. Cerebral Cortex, 17(9), 2007–2018. CrossRef Google Scholar PubMed
- Loring, D.W. (2010). History of neuropsychology through epilepsy eyes. Archives of Clinical Neuropsychology, 25(4), 259–273. doi: acq024 [pii]10.1093/arclin/acq024 [doi] CrossRef Google Scholar PubMed
- Loring, D.W., & Bauer, R.M. (2010). Testing the limits: Cautions and concerns regarding the new Wechsler IQ and Memory scales. Neurology, 74(8), 685–690. doi: 74/8/685 [pii]10.1212/WNL.0b013e3181d0cd12 [doi] CrossRef Google Scholar PubMed
- Loring, D.W., Kapur, R., Meador, K.J., & Morrell, M.J. (2015). Differential neuropsychological outcomes following targeted responsive neurostimulation for partial-onset epilepsy. Epilepsia, 56(11), 1836–1844. doi: 10.1111/epi.13191 CrossRef Google Scholar PubMed
- Loring, D.W., Meador, K.J., Lee, G.P., Murro, A.M., Smith, J.R., Flanigin, H.F., & King, D.W. (1990). Cerebral language lateralization: Evidence from intracarotid amobarbital testing. Neuropsychologia, 28(8), 831–838. CrossRef Google Scholar PubMed
- Loring, D.W., Williamson, D.J., Meador, K.J., Wiegand, F., & Hulihan, J. (2011). Topiramate dose effects on cognition: A randomized double-blind study. Neurology, 76(2), 131–137. doi: 10.1212/WNL.0b013e318206ca02 CrossRef Google Scholar PubMed
- Loughman, A., Bowden, S.C., & D’Souza, W. (2014). Cognitive functioning in idiopathic generalised epilepsies: A systematic review and meta-analysis. Neuroscience and Biobehavioral Reviews, 43, 20–34. doi: 10.1016/j.neubiorev.2014.02.012 CrossRef Google Scholar PubMed
- Mackenzie, I.R., & Miller, L.A. (1994). Senile plaques in temporal lobe epilepsy. Acta Neuropathologica, 87(5), 504–510. CrossRef Google Scholar PubMed
- Margerison, J.H., & Corsellis, J.A. (1966). Epilepsy and the temporal lobes. A clinical, electroencephalographic and neuropathological study of the brain in epilepsy, with particular reference to the temporal lobes. Brain, 89(3), 499–530. CrossRef Google Scholar PubMed
- Martin, R.C., Sawrie, S.M., Roth, D.L., Gilliam, F.G., Faught, E., Morawetz, R.B., & Kuzniecky, R. (1998). Individual memory change after anterior temporal lobectomy: A base rate analysis using regression-based outcome methodology. Epilepsia, 39(10), 1075–1082. CrossRef Google Scholar PubMed
- Mazur-Mosiewicz, A., Carlson, H.L., Hartwick, C., Dykeman, J., Lenders, T., Brooks, B.L., && Wiebe, S. (2015). Effectiveness of cognitive rehabilitation following epilepsy surgery: Current state of knowledge. Epilepsia, 56(5), 735–744. doi: 10.1111/epi.12963 CrossRef Google Scholar PubMed
- McDonald, C.R., Hagler, D.J. Jr., Ahmadi, M.E., Tecoma, E., Iragui, V., Gharapetian, L., & Halgren, E. (2008). Regional neocortical thinning in mesial temporal lobe epilepsy. Epilepsia, 49(5), 794–803. CrossRef Google Scholar PubMed
- McDonald, C.R., Leyden, K.M., Hagler, D.J., Kucukboyaci, N.E., Kemmotsu, N., Tecoma, E.S., && Iragui, V.J. (2014). White matter microstructure complements morphometry for predicting verbal memory in epilepsy. Cortex, 58, 139–150. doi: 10.1016/j.cortex.2014.05.014 CrossRef Google Scholar PubMed
- Meador, K.J., Baker, G.A., Browning, N., Clayton-Smith, J., Combs-Cantrell, D.T., Cohen, M., & Loring, D.W. (2009). Cognitive function at 3 years of age after fetal exposure to antiepileptic drugs. New England Journal of Medicine, 360(16), 1597–1605. CrossRef Google Scholar PubMed
- Milner, B. (1958). Psychological defects produced by temporal lobe excision. Research Publications - Association for Research in Nervous and Mental Disease, 36, 244–257. Google Scholar PubMed
- Milner, B. (1965). Visually guided maze learning in man: Effects of bilateral hippocampal, bilateral frontal, and unilateral cerebral lesions. Neuropsychologia, 3(4), 317–338. doi: https://doi.org/10.1016/0028-3932(65)9005-9 CrossRef Google Scholar
- Milner, B. (1972). Disorders of learning and memory after temporal lobe lesions in man. Clinical Neurosurgery, 19, 421–446. CrossRef Google Scholar PubMed
- Milner, B., Branch, C., & Rassmussen, T. (1962). Study of short-term memory after intracarotid injection of sodium amytal. Transactions of American Neurological Association, 87, 224–226. Google Scholar
- Mueller, S.G., Laxer, K.D., Cashdollar, N., Buckley, S., Paul, C., & Weiner, M.W. (2006). Voxel-based optimized morphometry (VBM) of gray and white matter in temporal lobe epilepsy (TLE) with and without mesial temporal sclerosis. Epilepsia, 47(5), 900–907. CrossRef Google Scholar PubMed
- Norton, S., Matthews, F.E., Barnes, D.E., Yaffe, K., & Brayne, C. (2014). Potential for primary prevention of Alzheimer’s disease: An analysis of population-based data. Lancet Neurology, 13(8), 788–794. doi: 10.1016/S1474-4422(14)70136-X CrossRef Google Scholar PubMed
- Novelly, R.A. (1992). The debt of neuropsychology to the epilepsies. The American Psychologist, 47(9), 1126–1129. CrossRef Google Scholar PubMed
- Nowinski, C.J., Siderowf, A., Simuni, T., Wortman, C., Moy, C., & Cella, D. (2016). Neuro-QoL health-related quality of life measurement system: Validation in Parkinson’s disease. Movement Disorders, 31(5), 725–733. doi: 10.1002/mds.26546 CrossRef Google Scholar PubMed
- O’Rourke, D.M., Saykin, A.J., Gilhool, J.J., Harley, R., O’Connor, M.J., & Sperling, M.R. (1993). Unilateral hemispheric memory and hippocampal neuronal density in temporal lobe epilepsy. Neurosurgery, 32(4), 574–580; discussion 580–571. CrossRef Google Scholar PubMed
- Oostrom, K.J., Smeets-Schouten, A., Kruitwagen, C.L., Peters, A.C., & Jennekens-Schinkel, A. (2003). Not only a matter of epilepsy: Early problems of cognition and behavior in children with “epilepsy only”--A prospective, longitudinal, controlled study starting at diagnosis. Pediatrics, 112(6 Pt 1), 1338–1344. CrossRef Google Scholar
- Otte, W.M., van Eijsden, P., Sander, J.W., Duncan, J.S., Dijkhuizen, R.M., & Braun, K.P. (2012). A meta-analysis of white matter changes in temporal lobe epilepsy as studied with diffusion tensor imaging. Epilepsia, 53(4), 659–667. doi: 10.1111/j.1528-1167.2012.03426.x CrossRef Google Scholar PubMed
- Overvliet, G.M., Aldenkamp, A.P., Klinkenberg, S., Vles, J.S., & Hendriksen, J. (2011). Impaired language performance as a precursor or consequence of Rolandic epilepsy? Journal of the Neurological Sciences, 304(1-2), 71–74. doi: 10.1016/j.jns.2011.02.009 CrossRef Google Scholar PubMed
- Oyegbile, T., Hansen, R., Magnotta, V., O’Leary, D., Bell, B., Seidenberg, M., && Hermann, B.P. (2004). Quantitative measurement of cortical surface features in localization-related temporal lobe epilepsy. Neuropsychology, 18(4), 729–737. CrossRef Google Scholar PubMed
- Oyegbile, T.O., Dow, C., Jones, J., Bell, B., Rutecki, P., Sheth, R., & Hermann, B.P. (2004). The nature and course of neuropsychological morbidity in chronic temporal lobe epilepsy. Neurology, 62(10), 1736–1742. CrossRef Google Scholar PubMed
- Pardoe, H.R., Cole, J.H., Blackmon, K., Thesen, T., Kuzniecky, R., & Human Epilepsy Project Ivestigators. (2017). Structural brain changes in medically refractory focal epilepsy resemble premature brain aging. Epilepsy Research, 133, 28–32. doi: 10.1016/j.eplepsyres.2017.03.007 CrossRef Google Scholar PubMed
- Pohlmann-Eden, B., Aldenkamp, A., Baker, G.A., Brandt, C., Cendes, F., Coras, R., & Hermann, B.P. (2015). The relevance of neuropsychiatric symptoms and cognitive problems in new-onset epilepsy - Current knowledge and understanding. Epilepsy & Behavior, 51, 199–209. doi: 10.1016/j.yebeh.2015.07.005 CrossRef Google Scholar PubMed
- Puvenna, V., Engleler, M., Banjara, M., Brennan, C., Schreiber, P., Dadas, A., & Janigro, D. (2016). Is phosphorylated tau unique to chronic traumatic encephalopathy? Phosophorylated tau in epileptic brain and chronic traumatic encephalopathy. Brain Research, 1630, 225–240. doi: 10.1016/j.brainres.2015.11.007 CrossRef Google Scholar
- Rasmussen, T., & Milner, B. (1977). The role of early left-brain injury in determining lateralization of cerebral speech functions. Annals of the New York Academy of Sciences, 299, 355–369. CrossRef Google Scholar PubMed
- Rausch, R., & Babb, T.L. (1987). Evidence for memory specialization within the mesial temporal lobe in man. In J. Engel, Jr. (Ed.), Fundamental mechanisms of human brain function (pp. 103–109). New York: Raven Press. Google Scholar
- Rausch, R., & Babb, T.L. (1993). Hippocampal neuron loss and memory scores before and after temporal lobe surgery for epilepsy. Archives of Neurology, 50(8), 812–817. CrossRef Google Scholar PubMed
- Rayner, G., Jackson, G.D., & Wilson, S.J. (2016a). Mechanisms of memory impairment in epilepsy depend on age at disease onset. Neurology, 87(16), 1642–1649. doi: 10.1212/WNL.0000000000003231 CrossRef Google Scholar PubMed
- Rayner, G., Jackson, G.D., & Wilson, S.J. (2016b). Two distinct symptom-based phenotypes of depression in epilepsy yield specific clinical and etiological insights. Epilepsy & Behavior, 64(Pt B), 336–344. doi: 10.1016/j.yebeh.2016.06.007 CrossRef Google Scholar PubMed
- Ronan, L., Alexander-Bloch, A.F., Wagstyl, K., Farooqi, S., Brayne, C., Tyler, L.K., & Fletcher, P.C. (2016). Obesity associated with increased brain age from midlife. Neurobiology of Aging, 47, 63–70. doi: 10.1016/j.neurobiolaging.2016.07.010 CrossRef Google Scholar PubMed
- Ronan, L., Murphy, K., Delanty, N., Doherty, C., Maguire, S., Scanlon, C., && Fitzsimons, M. (2007). Cerebral cortical gyrification: A preliminary investigation in temporal lobe epilepsy. Epilepsia, 48(2), 211–219. CrossRef Google Scholar PubMed
- Rzezak, P., Fuentes, D., Guimarães, C.A., Thome-Souza, S., Kuczynski, E., Li, L.M., & Valente, K.D. (2007). Frontal lobe dysfunction in children with temporal lobe epilepsy. Pediatric Neurology, 37(3), 176–185. CrossRef Google Scholar PubMed
- Saez, P.A., Bender, H.A., Barr, W.B., Rivera Mindt, M., Morrison, C.E., Hassenstab, J., & Vazquez, B. (2014). The impact of education and acculturation on nonverbal neuropsychological test performance among Latino/a patients with epilepsy. Applied Neuropsychology. Adult, 21(2), 108–119. doi: 10.1080/09084282.2013.768996 CrossRef Google Scholar PubMed
- Saling, M.M. (2009). Verbal memory in mesial temporal lobe epilepsy: Beyond material specificity. Brain, 132(Pt 3), 570–582. doi: awp012 [pii]10.1093/brain/awp012 [doi] CrossRef Google Scholar PubMed
- Saling, M.M., Berkovic, S.F., O’Shea, M.F., Kalnins, R.M., Darby, D.G., & Bladin, P.F. (1993). Lateralization of verbal memory and unilateral hippocampal sclerosis: Evidence of task-specific effects. Journal of Clinical and Experimental Neuropsychology, 15(4), 608–618. CrossRef Google Scholar PubMed
- Sass, K.J., Lencz, T., Westerveld, M., Novelly, R.A., Spencer, D.D., & Kim, J.H. (1991). The neural substrate of memory impairment demonstrated by the intracarotid amobarbital procedure. Archives of Neurology, 48(1), 48–52. CrossRef Google Scholar PubMed
- Sass, K.J., Sass, A., Westerveld, M., Lencz, T., Novelly, R.A., Kim, J.H., & Spencer, D.D. (1992). Specificity in the correlation of verbal memory and hippocampal neuron loss: Dissociation of memory, language, and verbal intellectual ability. Journal of Clinical and Experimental Neuropsychology, 14(5), 662–672. CrossRef Google Scholar PubMed
- Sass, K.J., Spencer, D.D., Kim, J.H., Westerveld, M., Novelly, R.A., & Lencz, T. (1990). Verbal memory impairment correlates with hippocampal pyramidal cell density. Neurology, 40(11), 1694–1697. CrossRef Google Scholar PubMed
- Sass, K.J., Westerveld, M., Buchanan, C.P., Spencer, S.S., Kim, J.H., & Spencer, D.D. (1994). Degree of hippocampal neuron loss determines severity of verbal memory decrease after left anteromesiotemporal lobectomy. Epilepsia, 35(6), 1179–1186. CrossRef Google Scholar PubMed
- Sawrie, S.M., Chelune, G.J., Naugle, R.I., & Lüders, H.O. (1996). Empirical methods for assessing meaningful neuropsychological change following epilepsy surgery. Journal of the International Neuropsychological Society, 2(6), 556–564. CrossRef Google Scholar PubMed
- Scheffer, I.E., Berkovic, S., Capovilla, G., Connolly, M.B., French, J., Guilhoto, L., & Zuberi, S.M. (2017). ILAE classification of the epilepsies: Position paper of the ILAE Commission for Classification and Terminology. Epilepsia, 58(4), 512–521. doi: 10.1111/epi.13709 CrossRef Google Scholar PubMed
- Seidenberg, M., Griffith, R., Sabsevitz, D., Moran, M., Haltiner, A., Bell, B., && Hermann, B. (2002). Recognition and identification of famous faces in patients with unilateral temporal lobe epilepsy. Neuropsychologia, 40(4), 446–456. CrossRef Google Scholar PubMed
- Seidenberg, M., Kelly, K.G., Parrish, J., Geary, E., Dow, C., Rutecki, P., && Hermann, B. (2005). Ipsilateral and contralateral MRI volumetric abnormalities in chronic unilateral temporal lobe epilepsy and their clinical correlates. Epilepsia, 46(3), 420–430. CrossRef Google Scholar PubMed
- Sen, A., Thom, M., Martinian, L., Harding, B., Cross, J.H., Nikolic, M., && Sisodiya, S.M. (2007). Pathological tau tangles localize to focal cortical dysplasia in older patients. Epilepsia, 48(8), 1447–1454. doi: 10.1111/j.1528-1167.2007.01107.x CrossRef Google Scholar PubMed
- Shegog, R., Bamps, Y.A., Patel, A., Kakacek, J., Escoffery, C., Johnson, E.K., && Ilozumba, U.O. (2013). Managing Epilepsy Well: Emerging e-Tools for epilepsy self-management. Epilepsy & Behavior, 29(1), 133–140. doi: 10.1016/j.yebeh.2013.07.002 CrossRef Google Scholar PubMed
- Sherman, E.M., Wiebe, S., Fay-McClymont, T.B., Tellez-Zenteno, J., Metcalfe, A., Hernandez-Ronquillo, L., & Jetté, N. (2011). Neuropsychological outcomes after epilepsy surgery: Systematic review and pooled estimates. Epilepsia, 52(5), 857–869. doi: 10.1111/j.1528-1167.2011.03022.x CrossRef Google Scholar PubMed
- Singhi, P.D., Bansal, U., Singhi, S., & Pershad, D. (1992). Determinants of IQ profile in children with idiopathic generalized epilepsy. Epilepsia, 33(6), 1106–1114. CrossRef Google Scholar PubMed
- Sinjab, B., Martinian, L., Sisodiya, S.M., & Thom, M. (2013). Regional thalamic neuropathology in patients with hippocampal sclerosis and epilepsy: A postmortem study. Epilepsia, 54(12), 2125–2133. doi: 10.1111/epi.12403 CrossRef Google Scholar PubMed
- Sisodiya, S.M., Moran, N., Free, S.L., Kitchen, N.D., Stevens, J.M., Harkness, W.F., & Shorvon, S.D. (1997). Correlation of widespread preoperative magnetic resonance imaging changes with unsuccessful surgery for hippocampal sclerosis. Annals of Neurology, 41(4), 490–496. doi: 10.1002/ana.410410412 [doi] CrossRef Google Scholar PubMed
- Slinger, G., Sinke, M.R., Braun, K.P., & Otte, W.M. (2016). White matter abnormalities at a regional and voxel level in focal and generalized epilepsy: A systematic review and meta-analysis. NeuroImage. Clinical, 12, 902–909. doi: 10.1016/j.nicl.2016.10.025 CrossRef Google Scholar
- Smith, A.B., Kavros, P.M., Clarke, T., Dorta, N.J., Tremont, G., & Pal, D.K. (2012). A neurocognitive endophenotype associated with rolandic epilepsy. Epilepsia, 53(4), 705–711. doi: 10.1111/j.1528-1167.2011.03371.x CrossRef Google Scholar PubMed
- Smith, M.L. (2016). Rethinking cognition and behavior in the new classification for childhood epilepsy: Examples from frontal lobe and temporal lobe epilepsies. Epilepsy & Behavior, 64(Pt B), 313–317. doi: 10.1016/j.yebeh.2016.04.050 CrossRef Google Scholar PubMed
- Stewart, C.C., Swanson, S.J., Sabsevitz, D.S., Rozman, M.E., Janecek, J.K., & Binder, J.R. (2014). Predictors of language lateralization in temporal lobe epilepsy. Neuropsychologia, 60, 93–102. doi: 10.1016/j.neuropsychologia.2014.05.021 CrossRef Google Scholar PubMed
- Stretton, J., & Thompson, P.J. (2012). Frontal lobe function in temporal lobe epilepsy. Epilepsy Research, 98(1), 1–13. doi: 10.1016/j.eplepsyres.2011.10.009 CrossRef Google Scholar PubMed
- Subota, A., Pham, T., Jette, N., Sauro, K., Lorenzetti, D., & Holroyd-Leduc, J. (2017). The association between dementia and epilepsy: A systematic review and meta-analysis. Epilepsia, 58, 962–972. doi: 10.1111/epi.13744 CrossRef Google Scholar PubMed
- Sulzbacher, S., Farwell, J.R., Temkin, N., Lu, A.S., & Hirtz, D.G. (1999). Late cognitive effects of early treatment with phenobarbital. Clinical Pediatrics, 38(7), 387–394. doi: 10.1177/000992289903800702 CrossRef Google Scholar PubMed
- Szaflarski, J.P., Gloss, D., Binder, J.R., Gaillard, W.D., Golby, A.J., Holland, S.K., & Theodore, W.H. (2017). Practice guideline summary: Use of fMRI in the presurgical evaluation of patients with epilepsy: Report of the Guideline Development, Dissemination, and Implementation Subcommittee of the American Academy of Neurology. Neurology, 88(4), 395–402. doi: 10.1212/WNL.0000000000003532 CrossRef Google Scholar PubMed
- Tai, X.Y., Koepp, M., Duncan, J.S., Fox, N., Thompson, P., Baxendale, S., & Thom, M. (2016). Hyperphosphorylated tau in patients with refractory epilepsy correlates with cognitive decline: A study of temporal lobe resections. Brain, 139(Pt 9), 2441–2455. doi: 10.1093/brain/aww187 CrossRef Google Scholar PubMed
- Tarter, R.E. (1972). Intellectual and adaptive functioning in epilepsy. A review of 50 years of research. Diseases of the Nervous System, 33(12), 763–770. Google Scholar
- Taylor, J., & Baker, G.A. (2010). Newly diagnosed epilepsy: Cognitive outcome at 5 years. Epilepsy & Behavior, 18(4), 397–403. doi: S1525-5050(10)00376-8 [pii]10.1016/j.yebeh.2010.05.007 [doi] CrossRef Google Scholar PubMed
- Taylor, D. (1993). Epilepsy as a chronic sickness: Remediating its impact. In J. Engel, (Ed.), Surgical treatment of the epilepsies (2nd ed., pp. 11–22). New York: Raven Press. 1993. Google Scholar PubMed
- Taylor, J., Kolamunnage-Dona, R., Marson, A.G., Smith, P.E., Aldenkamp, A.P., & Baker, G.A. (2010). Patients with epilepsy: Cognitively compromised before the start of antiepileptic drug treatment? Epilepsia, 51(1), 48–56. doi: EPI2195 [pii]10.1111/j.1528-1167.2009.02195.x [doi] CrossRef Google Scholar PubMed
- Tellez-Zenteno, J.F., Matijevic, S., & Wiebe, S. (2005). Somatic comorbidity of epilepsy in the general population in Canada. Epilepsia, 46(12), 1955–1962. CrossRef Google Scholar
- Tellez-Zenteno, J.F., Patten, S.B., Jette, N., Williams, J., & Wiebe, S. (2007). Psychiatric comorbidity in epilepsy: A population-based analysis. Epilepsia, 48, 2336–2344. Google Scholar PubMed
- Thom, M., Liu, J.Y., Thompson, P., Phadke, R., Narkiewicz, M., Martinian, L., & Sisodiya, S.M. (2011). Neurofibrillary tangle pathology and Braak staging in chronic epilepsy in relation to traumatic brain injury and hippocampal sclerosis: A post-mortem study. Brain, 134(Pt 10), 2969–2981. doi: 10.1093/brain/awr209 CrossRef Google Scholar PubMed
- Tippett, L.J., Glosser, G., & Farah, M.J. (1996). A category-specific naming impairment after temporal lobectomy. Neuropsychologia, 34(2), 139–146. CrossRef Google Scholar PubMed
- Trenerry, M.R., Jack, C.R. Jr., Ivnik, R.J., Sharbrough, F.W., Cascino, G.D., Hirschorn, K.A., & Meyer, F.B. (1993). MRI hippocampal volumes and memory function before and after temporal lobectomy. Neurology, 43(9), 1800–1805. CrossRef Google Scholar PubMed
- Trimble, M.R., & Thompson, P.J. (1986). Neuropsychological and behavioral sequelae of spontaneous seizures. Annals of the New York Academy of Sciences, 462, 284–292. CrossRef Google Scholar PubMed
- Tsai, M.H., Pardoe, H.R., Perchyonok, Y., Fitt, G.J., Scheffer, I.E., Jackson, G.D., && Berkovic, S.F. (2013). Etiology of hippocampal sclerosis: Evidence for a predisposing familial morphologic anomaly. Neurology, 81(2), 144–149. doi: 10.1212/WNL.0b013e31829a33ac CrossRef Google Scholar PubMed
- Vaessen, M.J., Jansen, J.F., Vlooswijk, M.C., Hofman, P.A., Majoie, H.J., Aldenkamp, A.P., && Backes, W.H. (2012). White matter network abnormalities are associated with cognitive decline in chronic epilepsy. Cerebral Cortex, 22(9), 2139–2147. doi: 10.1093/cercor/bhr298 CrossRef Google Scholar PubMed
- Valente, K.D., Rzezak, P., Moschetta, S.P., de Vincentiis, S., Coan, A.C., & Guerreiro, C.A. (2016). Delineating behavioral and cognitive phenotypes in juvenile myoclonic epilepsy: Are we missing the forest for the trees? Epilepsy & Behavior, 54, 95–99. doi: 10.1016/j.yebeh.2015.10.022 CrossRef Google Scholar PubMed
- Velissaris, S.L., Saling, M.M., Newton, M.R., Berkovic, S.F., & Wilson, S.J. (2012). Psychological trajectories in the year after a newly diagnosed seizure. Epilepsia, 53(10), 1774–1781. doi: 10.1111/j.1528-1167.2012.03658.x CrossRef Google Scholar PubMed
- Velissaris, S.L., Wilson, S.J., Saling, M.M., Newton, M.R., & Berkovic, S.F. (2007). The psychological impact of a newly diagnosed seizure: Losing and restoring perceived control. Epilepsy & Behavior, 10(2), 223–233. doi: 10.1016/j.yebeh.2006.12.008 CrossRef Google Scholar PubMed
- Vermeulen, J., & Aldenkamp, A.P. (1995). Cognitive side-effects of chronic antiepileptic drug treatment: A review of 25 years of research. Epilepsy Research, 22(2), 65–95. CrossRef Google Scholar
- Verrotti, A., Matricardi, S., Di Giacomo, D.L., Rapino, D., Chiarelli, F., & Coppola, G. (2013). Neuropsychological impairment in children with Rolandic epilepsy and in their siblings. Epilepsy & Behavior, 28(1), 108–112. doi: 10.1016/j.yebeh.2013.04.005 CrossRef Google Scholar PubMed
- Vickrey, B.G., Hays, R.D., Rausch, R., Engel, J. Jr., Visscher, B.R., Ary, C.M., & Brook, R.H. (1995). Outcomes in 248 patients who had diagnostic evaluations for epilepsy surgery. Lancet, 346(8988), 1445–1449. CrossRef Google Scholar PubMed
- Vogt, V.L., Aikia, M., Del Barrio, A., Boon, P., Borbely, C., Bran, E., & E-PILEPSY consortium. (2017). Current standards of neuropsychological assessment in epilepsy surgery centers across Europe. Epilepsia, 58(3), 343–355. doi: 10.1111/epi.13646 CrossRef Google Scholar PubMed
- Wagner, J.L., Modi, A.C., Johnson, E.K., Shegog, R., Escoffery, C., Bamps, Y., & Smith, G. (2017). Self-management interventions in pediatric epilepsy: What is the level of evidence? Epilepsia, 58(5), 743–754. doi: 10.1111/epi.13711 CrossRef Google Scholar PubMed
- Wandschneider, B., Centeno, M., Vollmar, C., Symms, M., Thompson, P.J., Duncan, J.S., && Koepp, M.J. (2014). Motor co–activation in siblings of patients with juvenile myoclonic epilepsy: An imaging endophenotype? Brain, 137(Pt 9), 2469–2479. doi: 10.1093/brain/awu175 CrossRef Google Scholar
- Wandschneider, B., Kopp, U.A., Kliegel, M., Stephani, U., Kurlemann, G., Janz, D., && Schmitz, B. (2010). Prospective memory in patients with juvenile myoclonic epilepsy and their healthy siblings. Neurology, 75(24), 2161–2167. doi: 10.1212/WNL.0b013e318202010a CrossRef Google Scholar PubMed
- Wang, W.H., Liou, H.H., Chen, C.C., Chiu, M.J., Chen, T.F., Cheng, T.W., && Hua, M.S. (2009). Neuropsychological performance and seizure-related risk factors in patients with temporal lobe epilepsy: A retrospective cross-sectional study. Epilepsy & Behavior, 22(4), 728–734. doi: 10.1016/j.yebeh.2011.08.038 CrossRef Google Scholar PubMed
- Weintraub, S., Dikmen, S.S., Heaton, R.K., Tulsky, D.S., Zelazo, P.D., Bauer, P.J., & Gershon, R.C. (2013). Cognition assessment using the NIH Toolbox. Neurology, 80(11 Suppl 3), S54–S64. doi: 10.1212/WNL.0b013e3182872ded CrossRef Google Scholar PubMed
- Wilson, S.J., & Baxendale, S. (2014). The new approach to classification: Rethinking cognition and behavior in epilepsy. Epilepsy & Behavior, 41, 307–310. doi: 10.1016/j.yebeh.2014.09.011 CrossRef Google Scholar PubMed
- Wilson, S., Bladin, P., & Saling, M. (2001). The “burden of normality”: Concepts of adjustment after surgery for seizures. The Journal of Neurology, Neurosurgery, and Psychiatry, 70(5), 649–656. CrossRef Google Scholar PubMed
- Wilson, S. (2011). Depression, anxiety, and cognition in epilepsy: Clinical and neuro. In C. Helmstaedter, B. Hermann, M. Lassonde, P. Kahane, & A. Arzimanoglou (Eds.), Neuropsychology in the care of people with epilepsy (pp. 259–261). Montrouge, France: John Libbey Eurotext Google Scholar
- Wilson, S.J., Baxendale, S., Barr, W., Hamed, S., Langfitt, J., Samson, S., & Smith, M.L. (2015). Indications and expectations for neuropsychological assessment in routine epilepsy care: Report of the ILAE Neuropsychology Task Force, Diagnostic Methods Commission, 2013-2017. Epilepsia, 56(5), 674–681. doi: 10.1111/epi.12962 CrossRef Google Scholar PubMed
- Wilson, S.J., & Engel, J. Jr. (2010). Diverse perspectives on developments in epilepsy surgery. Seizure, 19(10), 659–668. doi: 10.1016/j.seizure.2010.10.028 CrossRef Google Scholar PubMed
- Wilson, S.J., Micallef, S., Henderson, A., Rayner, G., Wrennall, J.A., Spooner, C., && Harvey, A.S. (2012). Developmental outcomes of childhood-onset temporal lobe epilepsy: A community-based study. Epilepsia, 53(9), 1587–1596. doi: 10.1111/j.1528-1167.2012.03632.x CrossRef Google Scholar PubMed
- Witt, J.A., Coras, R., Schramm, J., Becker, A.J., Elger, C.E., Blumcke, I., && Helmstaedter, C. (2015). Relevance of hippocampal integrity for memory outcome after surgical treatment of mesial temporal lobe epilepsy. Journal of Neurology, 262(10), 2214–2224. doi: 10.1007/s00415-015-7831-3 CrossRef Google Scholar PubMed
- Witt, J.A., & Helmstaedter, C. (2011). A survey on neuropsychological practice in German-speaking epilepsy centers. In C. Helmstaedter, B. Hermann, M. Lassonde, P. Kahane, & A. Arzimanoglou (Eds.), Progress in epileptic disorders: Neuropsychology in the care of people with epilepsy (Vol. 11, pp. 27–32). Montrouge, France: John Libbey Eurotext. Google Scholar
- Witt, J.A., & Helmstaedter, C. (2012). Should cognition be screened in new-onset epilepsies? A study in 247 untreated patients. Journal of Neurology, 259(8), 1727–1731. doi: 10.1007/s00415-012-6526-2 CrossRef Google Scholar PubMed
- Witt, J.A., & Helmstaedter, C. (2015). Cognition in the early stages of adult epilepsy. Seizure, 26, 65–68. doi: 10.1016/j.seizure.2015.01.018 CrossRef Google Scholar PubMed
- Witt, J.A., Werhahn, K.J., Kramer, G., Ruckes, C., Trinka, E., & Helmstaedter, C. (2014). Cognitive-behavioral screening in elderly patients with new-onset epilepsy before treatment. Acta Neurologica Scandinavica, 130(3), 172–177. doi: 10.1111/ane.12260 CrossRef Google Scholar PubMed
- Wolf, P. (2009). Development of the nosology and classification of epilepsy: 1909-2009. In S. Shorvon, G. Weiss, G. Avanzini, J. Engel, H. Meinardi, S. Moshe, E. Reynolds, & P. Wolf (Eds.), The international league against epilepsy 1909-2009: A centenary history (pp. 131–142). New York: Wiley-Blackwell. Google Scholar
- Wood, A.G., Saling, M.M., O’Shea, M.F., Jackson, G.D., & Berkovic, S.F. (1999). Reorganization of berbal memory and language: A case of dissociation. Journal of the International Neuropsychological Society, 5(1), 69–74. doi: https://doi.org/10.1017/s1355617799511090 CrossRef Google Scholar
- Wrench, J.M., Matsumoto, R., Inoue, Y., & Wilson, S.J. (2011). Current challenges in the practice of epilepsy surgery. Epilepsy & Behavior, 22(1), 23–31. doi: 10.1016/j.yebeh.2011.02.011 CrossRef Google Scholar PubMed
The past 50 years have been a period of exciting progress in neuropsychological research on traumatic brain injury (TBI). Neuropsychologists and neuropsychological testinghave played a critical role in these advances. This study looks back at three major scientific advances in research on TBI that have been critical in pushing the fieldforward over the past several decades: The advent of modern neuroimaging; the recognition of the importance of non-injury factors in determining recovery from TBI;and the growth of cognitive rehabilitation. Thanks to these advances, we now have a better understanding of the pathophysiology of TBI and how recovery from the injuryis also shaped by pre-injury, comorbid, and contextual factors, and we also have increasing evidence that active interventions, including cognitive rehabilitation,can help to promote better outcomes. The study also peers ahead to discern two important directions that seem destined to influence research on TBI over the next 50years: the development of large, multi-site observational studies and randomized controlled trials, bolstered by international research consortia and the adoptionof common data elements; and attempts to translate research into health care and health policy by the application of rigorous methods drawn from implementation science.Future research shaped by these trends should provide critical evidence regarding the outcomes of TBI and its treatment, and should help to disseminate and implementthe knowledge gained from research to the betterment of the quality of life of persons with TBI. (JINS, 2017, 23,806–817)
- Adelson, P.D. (2010). Clinical trials for pediatric traumatic brain injury. In V.A. Anderson & K.O. Yeates (Eds.), Pediatric traumatic brain injury: New frontiers in clinical and translational research (pp 54–67). New York: Oxford University Press. CrossRef Google Scholar
- Alway, Y., Gould, K.R., Johnston, L., McKenzie, D., & Ponsford, J. (2016). A prospective examination of Axis I psychiatric disorders in the first 5 years following moderate to severe traumatic brain injury. Psychological Medicine, 46, 1331–1441. CrossRef Google Scholar PubMed
- Alway, Y., McKay, A., Gould, K.R., Johnston, L., & Ponsford, J. (2016). Factors associated with posttraumatic stress disorder following moderate to severe traumatic brain injury: A prospective study. Depression and Anxiety, 33, 19–26. CrossRef Google Scholar PubMed
- Anderson, V., Catroppa, C., Morse, S., Haritou, F., & Rosenfeld, J. (2000). Recovery of intellectual ability following traumatic brain injury: Impact of injury severity and age at injury. Pediatric Neurosurgery, 32, 282–290. CrossRef Google Scholar PubMed
- Bayley, M., Tate, R., Douglas, J., Turkstra, L.S., Ponsford, J., Stergiou-Kita, M., & Bragge, P. (2014). INCOG guidelines for cognitive rehabilitation following traumatic brain injury: Methods and overview. Journal of Head Trauma Rehabilitation, 29, 290–306. CrossRef Google Scholar PubMed
- Bloom, D.R., Levin, H.S., Ewing-Cobbs, L., Saunders, A.E., Song, J., Fletcher, J.M., && Kowatch, R.A. (2001). Lifetime and novel psychiatric disorders after pediatric traumatic brain injury. Journal of the American Academy of Child & Adolescent Psychiatry, 40, 572–579. CrossRef Google Scholar PubMed
- Bombardier, C.H., Fann, J.R., Temkin, N.R., Esselman, P.C., Barber, J., & Dikmen, S.S. (2010). Rates of major depressive disorder and clinical outcomes following traumatic brain injury. Journal of the American Medical Association, 303, 1938–1945. CrossRef Google Scholar PubMed
- Braga, L.W., Da Paz Júnior, A.C., & Ylvisaker, M. (2005). Direct clinician-delivered versus indirect family-supported rehabilitation of children with traumatic brain injury: A randomized controlled trial. Brain Injury, 19, 819–831. CrossRef Google Scholar PubMed
- Broglio, S. (2015, October). The National Collegiate Athletic Association and Department of Defense Grand Alliance: The Concussion Assessment, Research and Education Consortium. Paper presented at the International Initiative for Traumatic Brain Injury Research (InTBIR) meeting, Brussels, Belgium. Google Scholar
- Brown, G., Chadwick, O., Shaffer, D., Rutter, M., & Traub, M. (1981). A prospective study of children with head injuries: III. Psychiatric sequelae. Psychological Medicine, 11, 63–78. CrossRef Google Scholar PubMed
- Bryant, R.A., & Harvey, A.G. (1999). Postconcussive symptoms and posttraumatic stress disorder after mild traumatic brain injury. Journal of Nervous & Mental Disease, 18, 302–305. CrossRef Google Scholar
- Bullmore, E., & Sporns, O. (2009). Complex brain networks: Graph theoretical analysis of structural and functional systems. Nature Reviews Neuroscience, 10, 186–198. CrossRef Google Scholar PubMed
- Bullmore, E., & Sporns, O. (2012). The economy of brain network organization. Nature Reviews Neuroscience, 13, 336–349. Google Scholar PubMed
- Cattelani, R., Zettin, M., & Zoccolotti, P. (2010). Rehabilitation treatments for adults with behavioral and psychosocial disorders following ABI: A systematic review. Neuropsychology Review, 20, 52–85. CrossRef Google Scholar
- Cicerone, K.D., Dahlberg, C., Kalmar, K., Langenbahn, D.M., Malec, J.F., Bergquist, T.F., & Morse, P.A. (2000). Evidence-based cognitive rehabilitation: Recommendations for clinical practice. Archives of Physical Medicine and Rehabilitation, 81, 1596–1615. CrossRef Google Scholar PubMed
- Cicerone, K.D., Dahlberg, C., Malec, J.F., Langenbahn, D.M., Felicetti, T., Kneipp, S., & Catanese, J. (2005). Evidence-based cognitive rehabilitation: Updated review of the literature from 1998 through 2002. Archives of Physical Medicine and Rehabilitation, 86, 1681–1692. CrossRef Google Scholar PubMed
- Cicerone, K.D., Langenbahn, D.M., Braden, C., Malec, J.F., Kalmar, K., Fraas, M., & Ashman, T. (2011). Evidence-based cognitive rehabilitation: Updated review of the literature from 2003 through 2008. Archives of Physical Medicine and Rehabilitation, 92, 519–530. CrossRef Google Scholar PubMed
- Coelho, C., Ylvisaker, M., & Turkstra, L. (2005). Nonstandardized assessment approaches for individuals with traumatic brain injuries. Seminars in Speech & Language, 4, 223–241. CrossRef Google Scholar
- Dawson, D.R., Gaya, A., Hunt, A., Levine, B., Lemsky, C., & Polatajko, H.J. (2009). Using the Cognitive Orientation to Occupational Performance (CO-OP) with adults with executive dysfunction following traumatic brain injury. Canadian Journal of Occupational Therapy, 76, 115–127. CrossRef Google Scholar
- Dennis, M., Yeates, K.O., Taylor, H.G., & Fletcher, J.M. (2007). Brain reserve capacity, cognitive reserve capacity, and age-based functional plasticity after congenital and acquired brain injury in children. In Y. Stern (Ed.), Cognitive reserve (pp 53–83). New York: Taylor & Francis. Google Scholar
- Dikmen, S., Machamer, J., Fann, J.R., & Temkin, N.R. (2010). Rates of symptom reporting following traumatic brain injury. Journal of the International Neuropsychological Society, 16, 401–411. CrossRef Google Scholar PubMed
- Dickstein, D.L., Pullman, M.Y., Fernandez, C., Short, J.A., Kostakoglu, L., Knesaurek, K., & Gandy, S. (2016). Cerebral [18F]T807/AV1451 retention pattern in clinically probable CTE resembles pathognomonic distribution of CTE tauopathy. Translational Psychiatry, 6, e900. CrossRef Google Scholar PubMed
- Duhaime, A.C., Gean, A.D., Haacke, E.M., Hicks, R., Wintermark, M., Mukherjee, P., ... Common Data Elements Neuroimaging Workgroup Members, Pediatric Working Group Members. (2010). Common data elements in radiologic imaging of traumatic brain injury. Archives of Physical Medicine and Rehabilitation, 91, 1661–1666. CrossRef Google Scholar PubMed
- Eames, P., & Wood, R. (1985). Rehabilitation after severe brain injury: A follow-up study of a behaviour modification approach. Journal of Neurology, Neurosurgery, and Psychiatry, 48, 613–619. CrossRef Google Scholar PubMed
- Ehlhardt, L.A., Sohlberg, M.M., Kennedy, M., Coelho, C., Ylvisaker, M., Turkstra, L., && Yorkston, K. (2008). Evidence-based practice guidelines for instructing individuals with neurogenic memory impairments: What have we learned in the last 20 years? Neuropsychological Rehabilitation, 18, 300–342. CrossRef Google Scholar
- Eisenberg, H.M., Gary, H.E. Jr, Aldrich, E.F., Saydjari, C., Turner, B., Foulkes, M.A., & Young, H.F. (1990). Initial CT findings in 753 patients with severe head injury. A report from the NIH Traumatic Coma Data Bank. Journal of Neurosurgery, 73, 688–698. CrossRef Google Scholar PubMed
- Ewing-Cobbs, L., Prasad, M.R., Swank, P., Kramer, L., Cox, C.S. Jr, Fletcher, J.M., & Hasan, K.M. (2008). Arrested development and disrupted callosal microstructure following pediatric traumatic brain injury: Relation to neurobehavioral outcomes. Neuroimage, 42, 1305–1315. CrossRef Google Scholar PubMed
- Fay, T.B., Yeates, K.O., Taylor, H.G., Bangert, B., Dietrich, A., Nuss, K.E., & Wright, M. (2010). Cognitive reserve as a moderator of postconcussive symptoms in children with complicated and uncomplicated mild traumatic brain injury. Journal of the International Neuropsychological Society, 16, 94–105. CrossRef Google Scholar PubMed
- Fleming, J.M., & Ownsworth, T. (2006). A review of awareness interventions in brain injury rehabilitation. Neuropsychological Rehabilitation, 16, 474–500. CrossRef Google Scholar PubMed
- Fox, M.D., Snyder, A.Z., Vincent, J.L., Corbetta, M., Van Essen, D.C., & Raichle, M.E. (2005). The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proceedings of the National Academy of Sciences of the United States of America, 102, 9673–9678. CrossRef Google Scholar PubMed
- Gardner, R.C., Burke, J.F., Nettiksimmons, J., Kaup, A., Barnes, D.E., & Yaffe, K. (2014). Dementia risk after traumatic brain injury vs nonbrain trauma: The role of age and severity. JAMA Neurology, 71, 1490–1497. CrossRef Google Scholar PubMed
- Gatson, J.W., Stebbins, C., Mathews, D., Harris, T.S., Madden, C., Batjer, H., & Minei, J.P. (2016). Evidence of increased brain amyloid in severe TBI survivors at 1, 12, and 24 months after injury: Report of 2 cases. Journal of Neurosurgery, 124, 1646–1653. CrossRef Google Scholar PubMed
- Govindarajan, K.A., Narayana, P.A., Hasan, K.M., Wilde, E.A., Levin, H.S., Hunter, J.V., & McCarthy, J.J. (2016). Cortical thickness in mild traumatic brain injury. Journal of Neurotrauma, 33, 1809–1817. CrossRef Google Scholar PubMed
- Grant, M., Ponsford, J., & Bennett, P.C. (2012). The application of goal management training to aspects of financial management in individuals with traumatic brain injury. Neuropsychological Rehabilitation, 22, 852–873. CrossRef Google Scholar PubMed
- Grimshaw, J.M., Eccles, M.P., Lavis, J.N., Hill, S.J., & Squires, J.E. (2012). Knowledge translation of research findings. Implementation Science, 7, 50. CrossRef Google Scholar PubMed
- Hayes, J.P., Bigler, E.D., & Verfaellie, M. (2016). Traumatic brain injury as a disorder of brain connectivity. Journal of the International Neuropsychological Society, 22, 120–137. CrossRef Google Scholar PubMed
- Hicks, R., Giacino, J., Harrison-Felix, C., Manley, G., Valadka, A., & Wilde, E.A. (2013). Progress in developing common data elements for traumatic brain injury research: Version two--the end of the beginning. Journal of Neurotrauma, 30, 1852–1861. CrossRef Google Scholar PubMed
- Himanen, L., Portin, R., Isoniemi, H., Helenius, H., Kurkj, T., & Tenovuo, O. (2006). Longitudinal cognitive changes in traumatic brain injury: A 30-year follow-up study. Neurology, 66, 187–192. CrossRef Google Scholar PubMed
- Hoge, C.W., McGurk, D., Thomas, J.L., Cox, A.L., Engel, C.C., & Castro, C.A. (2008). Mild traumatic brain injury in U.S. soldiers returning from Iraq. New England Journal of Medicine, 358, 453–463. CrossRef Google Scholar PubMed
- Hoofien, D., Gilboa, A., Vakil, E., & Donovick, P.J. (2001). Traumatic brain injury 10-20 years later: A comprehensive outcome study of psychiatric symptomatology, cognitive abilities, and psychosocial functioning. Brain Injury, 15, 189–209. Google Scholar PubMed
- Hukkelhoven, C.W., Steyerberg, E.W., Rampen, A.J., Farace, E., Habbema, J.D., & Maas, A.I. (2003). Patient age and outcome following severe traumatic brain injury: An analysis of 5600 patients. Journal of Neurosurgery, 99, 666–673. CrossRef Google Scholar PubMed
- Hulkower, M.B., Poliak, D.B., Rosenbaum, S.B., Zimmerman, M.E., & Lipton, M.L. (2013). A decade of DTI in traumatic brain injury: 10 years and 100 articles later. AJNR American Journal of Neuroradiology, 34, 2064–2074. CrossRef Google Scholar PubMed
- Humphreys, I., Wood, R.L., Phillips, C.J., & Macey, S. (2013). The costs of traumatic brain injury: A literature review. Clinico Economics and Outcomes Research, 5, 281–287. CrossRef Google Scholar PubMed
- Jankowitz, B.T., & Adelson, P.D. (2006). Pediatric traumatic brain injury: Past, present, and future. Developmental Neuroscience, 28, 264–275. CrossRef Google Scholar
- Keris, V., Lavendelis, E., & Macane, I. (2007). Association between implementation of clinical practice guidelines and outcome for traumatic brain injury. World Journal of Surgery, 31, 1352–1355. CrossRef Google Scholar PubMed
- Kreutzer, J.S., Stejskal, T.M., Ketchum, J.M., Marwitz, J.H., Taylor, L.A., & Menzel, J.C. (2009). A preliminary investigation of the brain injury family intervention: Impact on family members. Brain Injury, 23, 535–547. CrossRef Google Scholar
- Kurowski, B., Martin, L.J., & Wade, S.L. (2012). Genetics and outcomes after traumatic brain injury (TBI): What do we know about pediatric TBI? Journal of Pediatric Rehabilitation Medicine, 5, 217–231. Google Scholar
- Laatsch, L., Harrington, D., Hotz, G., Maracantuomo, J., Mozzoni, M., Walsh, V., && Hersey, K.P. (2007). An evidence-based review of cognitive and behavioural rehabilitation treatment studies in children with acquired brain injury. Journal of Head Trauma Rehabilitation, 22, 248–256. CrossRef Google Scholar PubMed
- Larsen, G.Y., Schober, M., Fabio, A., Wisniewski, S.R., Grant, M.J., Shafi, N., & Bell, M.J. (2016). Structure, process, and culture differences of pediatric trauma centers participating in an international comparative effectiveness study of children with severe traumatic brain injury. Neurocritical Care, 24, 353–360. CrossRef Google Scholar
- Lawson, M.J., & Rice, D.N. (1989). Effects of training in use of executive strategies on a verbal memory problem resulting from closed head injury. Journal of Experimental and Clinical Neuropsychology, 11, 942–854. CrossRef Google Scholar PubMed
- Levin, H.S., Benavidez, D.A., Verger-Maestre, K., Perachio, N., Song, J., Mendelsohn, D.B., && Fletcher, J.M. (2000). Reduction of corpus callosum growth after severe traumatic brain injury in children. Neurology, 54, 647–653. CrossRef Google Scholar PubMed
- Levin, H.S., Gary, H.E. Jr., & Eisenberg, H.M. (1989). Duration of impaired consciousness in relation to side of lesion after severe head injury. NIH Traumatic Coma Data Bank Research Group. Lancet, 1, 1001–1003. CrossRef Google Scholar PubMed
- Levin, H.S., Madison, C.F., Bailey, C.B., Meyers, C.A., Eisenberg, H.M., & Guinto, F.C. (1983). Mutism after closed head injury. Archives of Neurology, 40, 601–606. CrossRef Google Scholar PubMed
- Levine, B., Schweizer, T.A., O’Connor, C., Turner, G., Gillingham, S., Stuss, D.T., & Robertson, I.H. (2011). Rehabilitation of executive functioning in patients with frontal lobe brain damage with goal management training. Frontiers in Human Neuroscience, 5, 1–9. CrossRef Google Scholar PubMed
- Lew, H.L., Otis, J.D., Tun, C., Kerns, R.D., Clark, M.E., & Cifu, D.X. (2009). Prevalence of chronic pain, posttraumatic stress disorder, and persistent postconcussive symptoms in OIF/OEF veterans: Polytrauma clinical triad. Journal of Rehabilitation Research & Development, 46, 697–702. CrossRef Google Scholar PubMed
- Marshall, L.F., Marshall, S.B., Klauber, M.R., Van Berkum Clark, M., Eisenberg, H., Jane, J.A., & Foulkes, M.A. (1992). The diagnosis of head injury requires a classification based on computed axial tomography. Journal of Neurotrauma, 9(Suppl 1), S287–S292. Google Scholar
- Mateer, C.A., & Sira, C.S. (2006). Cognitive and emotional consequences of TBI: Intervention strategies for vocational rehabilitation. NeuroRehabilitation, 21, 315–326. Google Scholar PubMed
- Mayer, A.R., Ling, J.M., Dodd, A.B., Gasparovic, C., Klimaj, S.D., & Meier, T.B. (2015). A longitudinal assessment of structural and chemical alterations in mixed martial arts fighters. Journal of Neurotrauma, 32, 1759–1767. CrossRef Google Scholar PubMed
- McAllister, T.W. (2015). Genetic factors in traumatic brain injury. Handbook of Clinical Neurology, 128, 723–739. CrossRef Google Scholar PubMed
- McAllister, T.W., Saykin, A.J., Flashman, L.A., Sparling, M.B., Johnson, S.C., Guerin, S.J., & Yanofsky, N. (1999). Brain activation during working memory 1 month after mild traumatic brain injury: A functional MRI study. Neurology, 53, 1300–1308. CrossRef Google Scholar PubMed
- McCauley, S.R., Wilde, E.A., Anderson, V.A., Bedell, G., Beers, S.R., Campbell, T.F., & Yeates, K.O. (2012). Recommendations for the use of common outcome measures in pediatric traumatic brain injury research. Journal of Neurotrauma, 29, 678–705. CrossRef Google Scholar
- McDonald, S., Togher, L., Tate, R., Randall, R., English, T., & Gowland, A. (2013). A randomised controlled trial evaluating a brief intervention for deficits in recognising emotional prosody following severe ABI. Neuropsychological Rehabilitation, 23, 267–286. CrossRef Google Scholar PubMed
- Medd, J., & Tate, R.L. (2000). Evaluation of an anger management therapy programme following acquired brain injury: A preliminary study. Neuropsychological Rehabilitation, 10, 185–201. CrossRef Google Scholar
- Nampiaparampil, D.E. (2008). Prevalence of chronic pain after traumatic brain injury: A systematic review. Journal of the American Medical Association, 300, 711–719. CrossRef Google Scholar PubMed
- Newsome, M.R., Li, X., Lin, X., Wilde, E.A., Ott, S., Biekman, B., & Levin, H.S. (2016). Functional connectivity is alterted in concussed adolescent athletes despite medical clearance to return to play: A preliminary report. Frontiers in Neurology, 7, 116. CrossRef Google Scholar
- Newsome, M.R., Scheibel, R.S., Hanten, G., Chu, Z., Steinberg, J.L., Hunter, J.V., & Levin, H.S. (2010). Brain activation while thinking about the self from another person’s perspective after traumatic brain injury in adolescents. Neuropsychology, 24, 139–147. CrossRef Google Scholar
- Nguyen, S., McKay, A., Wong, D., Spitz, G., Mansfield, D., Williams, G., & Ponsford, J. (2017). Cognitive behavior therapy to treat sleep disturbance and fatigue following traumatic brain injury: A pilot randomized study. Archives of Physical Medicine and Rehabilitation. [Epub ahead of print]. Google Scholar
- Paniak, C.S., Reynolds, S., Toller-Lobe, G., Melnyk, A., Nagy, J., & Schmidt, D. (2002). A longitudinal study of the relationship between financial compensation and symptoms after treated mild traumatic brain injury. Journal of Clinical and Experimental Neuropsychology, 24, 187–193. CrossRef Google Scholar PubMed
- Podell, K., Gifford, K., Bougakov, D., & Goldberg, E. (2014). Neuropsychological assessment in traumatic brain injury. Psychiatric Clinics of North America, 33, 855–876. CrossRef Google Scholar PubMed
- Ponsford, J., Bayley, M., Wiseman-Hakes, C., Togher, L., Velikonja, D., McIntyre, A., & Tate, R. (2014). INCOG recommendations for management of cognition following TBI Part II: Attention and information processing speed. Journal of Head Trauma Rehabilitation, 29, 321–337. CrossRef Google Scholar
- Ponsford, J.L., Downing, M., Olver, J., Ponsford, M., Acher, R., Carty, M., && Spitz, G. (2014). Longitudinal follow-up of patients with traumatic brain injury: Outcome at two, five, and ten years post-injury. Journal of Neurotrauma, 31, 64–77. CrossRef Google Scholar PubMed
- Ponsford, J., Lee, N., McKay, A., Wong, D., Haines, K., Alway, Y., & O’Donnell, M. (2016). Efficacy of motivational interviewing and cognitive behavioral therapy for anxiety and depression symptoms following traumatic brain injury. Psychological Medicine, 46, 1079–1090. CrossRef Google Scholar PubMed
- Ponsford, J.L., Ziino, C., Parcell, D.L., Shekleton, J.A., Roper, M., Redman, J.R., & Rajaratnam, S.M. (2012). Fatigue and sleep disturbance following traumatic brain injury – Their nature, causes and potential treatments. Journal of Head Trauma Rehabilitation, 27, 224–233. CrossRef Google Scholar PubMed
- Radice-Neumann, D., Zupan, B., Tomita, M., & Willer, B. (2009). Training emotional processing in persons with brain injury. Journal of Head Trauma Rehabilitation, 24, 313–323. CrossRef Google Scholar PubMed
- Roebuck-Spencer, T., & Sherer, M. (2008). Moderate and severe traumatic brain injury. In J.E. Morgan & J.H. Ricker (Eds.), Textbook of clinical neuropsychology (pp 411–429). New York: Taylor & Francis. Google Scholar
- Roozenbeek, B., Lingsma, H.F., Lecky, F.E., Lu, J., Weir, J., Butcher, I., & Steyerberg, E.W., on behalf of the International Mission on Prognosis and Analysis of Clinical Trials in Traumatic Brain Injury (IMPACT) Study Group, the Corticosteroid Randomisation After Significant Head Injury (CRASH) Trial Collaborators, and the Trauma Audit and Research Network (TARN). (2012). Prediction of outcome after moderate and severe traumatic brain injury: External validation of the IMPACT and CRASH Prognostic Models. Critical Care Medicine, 40, 1609–1617. CrossRef Google Scholar
- Roozenbeek, B., Maas, A.I., & Menon, D.K. (2013). Changing patterns in the epidemiology of traumatic brain injury. Nature Reviews Neuroscience, 9, 231–236. Google Scholar PubMed
- Saatman, K.E., Duhaime, A.C., Bullock, R., Maas, A.I., Valadka, A., & Manley, G.T., Workshop Scientific Team and Advisory Panel Members. (2008). Classification of traumatic brain injury for targeted therapies. Journal of Neurotrauma, 25, 719–738. CrossRef Google Scholar PubMed
- Sander, A.M., Caroselli, J.S., High, W.M. Jr., Becker, C., Neese, L., & Scheibel, R. (2002). Relationship of family functioning to progress in a post-acute rehabilitation programme following traumatic brain injury. Brain Injury, 16, 649–657. CrossRef Google Scholar
- Savage, R.C., DePompei, R., Tyler, J., & Lash, M. (2005). Paediatric traumatic brain injury: A review of pertinent issues. Paediatric Rehabilitation, 8, 92–103. CrossRef Google Scholar PubMed
- Scheibel, R.S., Newsome, M.R., Troyanskaya, M., Steinberg, J.L., Goldstein, F.C., Mao, H., && Levin, H.S. (2009). Effects of severity of traumatic brain injury and brain reserve on cognitive-control related brain activation. Journal of Neurotrauma, 26, 1447–1461. CrossRef Google Scholar PubMed
- Sharp, D.J., Scott, G., & Leech, R. (2014). Network dysfunction after traumatic brain injury. Nature Reviews Neurology, 10, 156–166. CrossRef Google Scholar PubMed
- Sherer, M., & Sander, A.M. (2014). Handbook on the neuropsychology of traumatic brain injury. New York: Springer. CrossRef Google Scholar
- Sherer, M., Sander, A.M., Nick, T.G., High, W.M., Malec, J.F., & Rosenthal, M. (2002). Early cognitive status and productivity outcome after traumatic brain injury: Findings from the TBI Model Systems. Archives of Physical Medicine and Rehabilitation, 83, 183–192. CrossRef Google Scholar PubMed
- Sherman, K.B., Goldberg, M., & Bell, K.R. (2006). Traumatic brain injury and pain. Physical Medicine and Rehabilitation Clinics of North America, 17, 473–490. CrossRef Google Scholar PubMed
- Shum, D., Fleming, J., Gill, H., Gullo, M.J., & Strong, J. (2011). A randomized controlled trial of prospective memory rehabilitation in adults with traumatic brain injury. Journal of Rehabilitation Medicine, 43, 216–223. CrossRef Google Scholar PubMed
- Sinclair, K.L., Ponsford, J.L., Taffe, J., Lockley, S.W., & Rajaratnam, S.M.W. (2014). Randomized controlled trial of light therapy for fatigue following traumatic brain injury. Neurorehabilitation and Neural Repair, 28, 303–313. CrossRef Google Scholar PubMed
- Sohlberg, M.M., Kennedy, M., Avery, J., Coelho, C., Turkstra, L., Ylvisaker, M., && Yorkston, K. (2007). Evidence-based practice for the use of external aids as a memory compensation technique. Journal of Medical Speech-Language Pathology, 5. Google Scholar
- Spikman, J.M., Boelen, D.H.E., Lamberts, K.F., Brouwer, W.H., & Fasotti, L. (2010). Effects of a multifaceted treatment program for executive dysfunction after acquired brain injury on indications of executive functioning in daily life. Journal of the International Neuropsychological Society, 16, 118–129. CrossRef Google Scholar PubMed
- Stern, Y. (2000). Cognitive reserve. Neuropsychologia, 47, 2015–2028. CrossRef Google Scholar PubMed
- Tate, R., Kennedy, M., Ponsford, J., Douglas, J., Velikonja, D., Bayley, M., && Stergiou-Kita, M. (2014). INCOG Recommendations for management of cognition following traumatic brain injury. Part III: Executive function and self-awareness. Journal of Head Trauma Rehabilitation, 29(4), 338–352. CrossRef Google Scholar PubMed
- Taylor, H.G., Yeates, K.O., Wade, S.L., Drotar, D., Klein, S.K., & Stancin, T. (1999). Influences on first-year recovery from traumatic brain injury in children. Neuropsychology, 13, 76–89. CrossRef Google Scholar PubMed
- Taylor, H.G., Yeates, K.O., Wade, S.L., Drotar, D., Stancin, T., & Minich, M. (2002). A prospective study of short- and long-term outcomes after traumatic brain injury in children: Behavior and achievement. Neuropsychology, 16, 15–27. CrossRef Google Scholar
- Teasdale, G., & Jennett, B. (1974). Assessment of coma and impaired consciousness. A practical scale. Lancet, 13, 81–84. CrossRef Google Scholar
- Tham, S.W., Palermo, T.M., Wang, J., Jaffe, K.M., Temkin, N., Durbin, D., && Rivara, F.P. (2013). Persistent pain in adolescents following traumatic brain injury. The Journal of Pain, 14, 1242–1249. CrossRef Google Scholar PubMed
- Togher, L., Wiseman-Hakes, C., Douglas, J., Stergiou-Kita, M., Ponsford, J., Teasell, R., & Turkstra, L.S. (2014). INCOG Recommendations for management of cognition following traumatic brain injury: Part IV. Cognitive communication. Journal of Head Trauma Rehabilitation, 29, 353–368. CrossRef Google Scholar PubMed
- Tosetti, P., Hicks, R.R., Theriault, E., Phillips, A., Koroshetz, W., & Draghia-Akli, R., workshop participants. (2013). Toward an international initiative for traumatic brain injury research. Journal of Neurotrauma, 30, 1211–1222. CrossRef Google Scholar PubMed
- Treble-Barna, A., Zang, H., Zhang, N., Martin, L.J., Yeates, K.O., Taylor, H.G., & Kurowski, B.G. (2016). Does Apolipoprotein e4 status moderate the association of family environment with long-term child functioning following early moderate to severe traumatic brain injury? A preliminary study. Journal of the International Neuropsychological Society, 22, 859–864. CrossRef Google Scholar PubMed
- Turkheimer, E., Cullum, C.M., Hubler, D.W., Paver, S.W., Yeo, R.A., & Bigler, E.D. (1984). Quantifying cortical atrophy. Neurology, Neurosurgery, and Psychiatry, 47, 1314–1318. CrossRef Google Scholar PubMed
- Velikonja, D., Tate, R., Ponsford, J., McIntyre, A., Janzen, S., & Bayley, M. (2014). INCOG recommendations for management of cognition following traumatic brain injury, Part V: Memory. Journal of Head Trauma Rehabilitation, 29, 369–386. CrossRef Google Scholar PubMed
- Wade, S., Walz, N., Carey, J., McMullen, K., Cass, J., Mark, E., && Yeates, K.O. (2011). Effect on behavior problems of teen online problem-solving for adolescent traumatic brain injury. Pediatrics, 128, e947–e953. CrossRef Google Scholar PubMed
- Washington, P.M., Vilapol, S., & Burns, M.P. (2016). Polypathology and dementia after brain trauma: Does brain injury trigger distinct neurodegenerative diseases or should it be classified together as traumatic encephalopathy? Experimental Neurology, 275, 81–88. CrossRef Google Scholar PubMed
- Wilde, E.A., Bouix, S., Tate, D.F., Lin, A.P., Newsome, M.R., Taylor, B.A., & York, G. (2015). Advanced neuroimaging applied to veterans and service personnel with traumatic brain injury: State of the art and potential benefits. Brain Imaging and Behavior, 9, 367–402. CrossRef Google Scholar PubMed
- Williams, D.H., Levin, H.S., & Eisenberg, H.M. (1990). Mild head injury classification. Neurosurgery, 27, 422–428. CrossRef Google Scholar PubMed
- Wilson, B.A., Emslie, H.C., Quirk, K., & Evans, J.J. (2001). Reducing everyday memory and planning problems by means of a paging system: A randomised control crossover study. Journal of Neurology, Neurosurgery, and Psychiatry, 70, 477–482. CrossRef Google Scholar PubMed
- Yeates, K.O. (2010). Traumatic brain injury. In K.O. Yeates, M.D. Ris, H.G. Taylor & B.F. Pennington (Eds.), Pediatric neuropsychology: Research, theory, and practice (2nd ed, pp 112–146). New York: Guilford Press. Google Scholar
- Yeates, K.O., Armstrong, K., Janusz, J., Taylor, H.G., Wade, S., Stancin, T., && Drotar, D. (2005). Long-term attention problems in children with traumatic brain injury. Journal of the American Academy of Child and Adolescent Psychiatry, 44, 574–584. CrossRef Google Scholar PubMed
- Yeates, K.O., Taylor, H.G., Drotar, D., Wade, S., Klein, S., & Stancin, T. (1997). Premorbid family environment as a predictor of neurobehavioral outcomes following pediatric TBI. Journal of the International Neuropsychological Society, 3, 617–630. Google Scholar
- Yeates, K.O., Taylor, H.G., Walz, N.C., Stancin, T., & Wade, S.L. (2010). The family environment as a moderator of psychosocial outcomes following traumatic brain injury in young children. Neuropsychology, 24, 345–356. CrossRef Google Scholar PubMed
- Ylvisaker, M., Adelson, D., Braga, L.W., Burnett, S.M., Glang, A., Feeney, T., & Todis, B. (2005). Rehabilitation and ongoing support after pediatric TBI: Twenty years of progress. Journal of Head Trauma Rehabilitation, 20, 90–104. CrossRef Google Scholar PubMed
- Ylvisaker, M., Jacobs, H., & Feeney, T.J. (2003). Positive supports for people who experience behavioral and cognitive disability after brain injury: A review. Journal of Head Trauma Rehabilitation, 18, 7–32. CrossRef Google Scholar PubMed
- Ylvisaker, M., Todis, B., Glang, A., Urbanczyk, B., Franklin, C., DePompei, R., & Tyler, J.S. (2001). Educating students with TBI: Themes and recommendations. Journal of Head Trauma Rehabilitation, 16, 76–93. CrossRef Google Scholar PubMed
- Ylvisaker, M., Turkstra, L.S., & Coelho, C. (2005). Behavioral and social interventions for individuals with traumatic brain injury: A summary of the research with clinical implications. Seminars in Speech & Language, 26, 256–267. CrossRef Google Scholar PubMed
- Ylvisaker, M., Turkstra, L., Coehlo, C., Yorkston, K., Kennedy, M., Sohlberg, M.M., && Avery, J. (2007). Behavioural interventions for children and adults with behaviour disorders after TBI: A systematic review of the evidence. Brain Injury, 21, 769–805. CrossRef Google Scholar
- Yue, J.K., Vassar, M.J., Lingsma, H.F., Cooper, S.R., Okonkwo, D.O., Valadka, A.B., & Manley, G.T., TRACK-TBI Investigators. (2013). Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) pilot: Multicenter implementation of the common data elements for traumatic brain injury. Journal of Neurotrauma, 30, 1831–1844. CrossRef Google Scholar PubMed
- Yuh, E.L., Mukherjee, P., Lingsma, H.F., Yue, J.K., Ferguson, A.R., Gordon, W.A., & Manley, G.T., TRACK-TBI Investigators. (2013). Magnetic resonance imaging improves 3-month outcome prediction in mild traumatic brain injury. Annals of Neurology, 73, 224–235. CrossRef Google Scholar PubMed
- Zatzick, D.F., Rivara, F.P., Jurkovich, G.J., Hoge, C.W., Wang, J., Fan, M.Y., & Mackenzie, E.J. (2010). Multisite investigation of traumatic brain injuries, posttraumatic stress disorder, and self-reported health and cognitive impairments. Archives of General Psychiatry, 67, 1291–1300. CrossRef Google Scholar PubMed
- Zemek, R., Osmond, M.H., & Barrowman, N., on behalf of Pediatric Emergency Research Canada (PERC) concussion team. (2013). Predicting and preventing postconcussive problems in paediatrics (5P) study: Protocol for a prospective multicenter clinical prediction rule derivation study in children with concussion. BMJ Open, 3, e003550. doi: 10.1136/bmjopen-2013-003550. CrossRef Google Scholar
Although dementia has been described in ancient texts over many centuries (e.g., “Be kind to your father, even if his mind fail him.” – Old Testament: Sirach 3:12), ourknowledge of its underlying causes is little more than a century old. Alzheimer published his now famous case study only 110 years ago, and our modern understandingof the disease that bears his name, and its neuropsychological consequences, really only began to accelerate in the 1980s. Since then we have witnessed an explosionof basic and translational research into the causes, characterizations, and possible treatments for Alzheimer’s disease (AD) and other dementias. We review this lineageof work beginning with Alzheimer’s own writings and drawings, then jump to the modern era beginning in the 1970s and early 1980s and provide a sampling of neuropsychologicaland other contextual work from each ensuing decade. During the 1980s our field began its foundational studies of profiling the neuropsychological deficits associatedwith AD and its differentiation from other dementias (e.g., cortical vs. subcortical dementias). The 1990s continued these efforts andbegan to identify the specific cognitive mechanisms affected by various neuropathologic substrates. The 2000s ushered in a focus on the study of prodromal stages ofneurodegenerative disease before the full-blown dementia syndrome (i.e., mild cognitive impairment). The current decade has seen the rise of imaging and other biomarkersto characterize preclinical disease before the development of significant cognitive decline. Finally, we suggest future directions and predictions for dementia-relatedresearch and potential therapeutic interventions. (JINS, 2017, 23, 818–831)
- Albert, M.L., Feldman, R.G., & Willis, A.L. (1974). The ‘subcortical dementia’ of progressive supranuclear palsy. Journal of Neurology, Neurosurgery, and Psychiatry, 37, 121–130. CrossRef Google Scholar PubMed
- Albert, M.S., DeKosky, S.T., Dickson, D., Dubois, B., Feldman, H.H., Fox, N.C., & Phelps, C.H. (2011). The diagnosis of mild cognitive impairment due to Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimer’s & Dementia, 7, 270–279. CrossRef Google Scholar
- Alzheimer, A. (1907). über eine eigenartige Erkankung der Hirnrinde. Allgemeine Zeitschrift fur Psychiatrie under Psychisch-Gerichtliche Medizin, 64, 146–148. Google Scholar
- Alzheimer, A. (1911). Über eigenartige Krankheitsfälle des späteren Alters. Zeitschrift für die Gesamte Neurologie und Psychiatrie, 4, 356–385. CrossRef Google Scholar
- American Psychiatric Association. (1968). Diagnostic and Statistical Manual of Mental Disorders (2nd Ed). Washington, DC: American Psychiatric Association. Google Scholar PubMed
- American Psychiatric Association. (1980). Task force on nomenclature and statistics. Diagnostic and statistical manual of mental disorders (DSM-III). Washington, DC: American Psychiatric Association. Google Scholar
- Baddeley, A.D., Bressi, S., Della Sala, S., Logie, R., & Spinnler, H. (1991). The decline of working memory in Alzheimer’s disease: A longitudinal study. Brain, 114, 2521–2542. CrossRef Google Scholar PubMed
- Bateman, R.J., Xiong, C., Benzinger, T.L., Fagan, A.M., Goate, A., Fox, N.C., & Morris, J.C.; Dominantly Inherited Alzheimer Network. (2012). Clinical and biomarker changes in dominantly inherited Alzheimer’s disease. The New England Journal of Medicine, 367, 795–804. CrossRef Google Scholar PubMed
- Bird, T.D. (1999). Clinical genetics of familial Alzheimer’s disease. In R.D. Terry, R. Katzman, K.L. Bick & S.S. Sisodia (Eds.), Alzheimer disease (pp. 57–66). Philadelphia: Lippincott Williams & Wilkens. Google Scholar PubMed
- Blessed, G., Tomlinson, B., & Roth, M. (1968). The association between quantitative measures of dementia and of senile changes in the cerebral grey matter of elderly subjects. British Journal of Psychiatry, 114, 797–811. CrossRef Google Scholar
- Bondi, M.W., Edmonds, E.C., Jak, A.J., Clark, L.R., Delano-Wood, L., McDonald, C.R., & Salmon, D.P. (2014). Neuropsychological criteria for mild cognitive impairment improves diagnostic precision, biomarker associations, and prediction of progression. Journal of Alzheimer’s Disease, 42, 275–289. Google Scholar
- Bondi, M.W., Monsch, A.U., Butters, N., Salmon, D.P., & Paulsen, J.S. (1993). Utility of a modified version of the Wisconsin Card Sorting Test in the detection of dementia of the Alzheimer type. Clinical Neuropsychologist, 7, 161–170. CrossRef Google Scholar PubMed
- Bondi, M.W., Monsch, A.U., Galasko, D., Butters, N., Salmon, D.P., & Delis, D.C. (1994). Preclinical cognitive markers of dementia of the Alzheimer’s type. Neuropsychology, 8, 374–384. CrossRef Google Scholar
- Bondi, M.W., Salmon, D.P., Galasko, D., Thomas, R.G., & Thal, L.J. (1999). Neuropsychological function and apolipoprotein E qgenotype in the preclinical detection of Alzheimer’s disease. Psychology and Aging, 14, 295–303. CrossRef Google Scholar PubMed
- Bondi, M.W., Salmon, D.P., Monsch, A.U., Galasko, D., Butters, N., Klauber, M.R., & Saitoh, T. (1995). Episodic memory changes are associated with the ApoE-ε4 allele in nondemented older adults. Neurology, 45, 2203–2206. CrossRef Google Scholar
- Braak, H., & Braak, E. (1991). Neuropathological staging of Alzheimer-related changes. Acta Neuropathologica, 82, 239–259. CrossRef Google Scholar
- Braak, H., & Del Tredici, K. (2014). Are cases with tau pathology occurring in the absence of Aβ deposits part of the AD-related pathological process? Acta Neuropathologica, 128, 767–772. CrossRef Google Scholar PubMed
- Braak, H., & Del Tredici, K. (2015). The preclinical phase of the pathological process underlying sporadic Alzheimer’s disease. Brain, 138, 2814–2833. CrossRef Google Scholar PubMed
- Braak, H., Thal, D.R., Ghebremedhin, E., & Del Tredici, K. (2011). Stages of the pathologic process in Alzheimer disease: age categories from 1 to 100 years. Journal of Neuropathology & Experimental Neurology, 70, 960–969. CrossRef Google Scholar PubMed
- Braak, H., Zetterberg, H., Del Tredici, K., & Blennow, K. (2013). Intraneuronal tau aggregation precedes diffuse plaque deposition, but amyloid-β changes occur before increases of tau in cerebrospinal fluid. Acta Neuropathologica, 126, 631–641. CrossRef Google Scholar PubMed
- Brosch, J.R., Farlow, M.R., Risacher, S.L., & Apostolova, L.G. (2017). Tau imaging in Alzheimer’s disease diagnosis and clinical trials. Neurotherapeutics, 14, 62–68. CrossRef Google Scholar PubMed
- Buschke, H., Sliwinski, M.J., Kuslansky, G., & Lipton, R.B. (1997). Diagnosis of early dementia by the double memory test. Neurology, 48, 989–997. CrossRef Google Scholar PubMed
- Butters, N., Granholm, E., Salmon, D.P., Grant, I., & Wolfe, J. (1987). Episodic and semantic memory: A comparison of amnesic and demented patients. Journal of Clinical and Experimental Neuropsychology, 9, 479–497. CrossRef Google Scholar PubMed
- Caine, D. (2004). Posterior cortical atrophy: a review of the literature. Neurocase, 10, 382–385. CrossRef Google Scholar PubMed
- Chertkow, H., & Bub, D. (1990). Semantic memory loss in dementia of Alzheimer’s type. Brain, 113, 397–417. CrossRef Google Scholar PubMed
- Clark, L.R., Delano-Wood, L., Libon, D.J., McDonald, C.R., Nation, D.A., Bangen, K.J., & Bondi, M.W. (2013). Are empirically derived subtypes of mild cognitive impairment consistent with conventional subtypes? Journal of the International Neuropsychological Society, 19, 635–645. CrossRef Google Scholar PubMed
- Collette, F., Van der Linden, M., Bechet, S., & Salmon, E. (1999). Phonological loop and central executive functioning in Alzheimer’s disease. Neuropsychologia, 37, 905–918. CrossRef Google Scholar PubMed
- Crary, J.F., Trojanowski, J.Q., Schneider, J.A., Abisambra, J.F., Abner, E.L., Alafuzoff, I., & Nelson, P.T. (2014). Primary age-related tauopathy (PART): A common pathology associated with human aging. Acta Neuropathologica, 128, 755–766. CrossRef Google Scholar PubMed
- Cronin-Golomb, A., & Amick, M. (2001). Spatial abilities in aging, Alzheimer’s disease, and Parkinson’s disease. In F. Boller & S.F. Cappa (Eds.), Handbook of Neuropsychology. Aging and dementia (2nd, ed.), Vol. 6., pp. 119–143). Amsterdam: Elsevier. Google Scholar
- Cummings, J.L. (1990). Subcortical dementia. New York: Oxford University Press. Google Scholar PubMed
- Cummings, J.L., & Benson, D.F. (1992). Dementia: A clinical approach. Boston: Butterworth-Heinemann. Google Scholar
- Cummings, J.L., Morstorf, T., & Zhong, K. (2014). Alzheimer’s disease drug-development pipeline: few candidates, frequent failures. Alzheimer’s Research & Therapy, 6, 37. CrossRef Google Scholar PubMed
- Delis, D.C., Massman, P.J., Butters, N., Salmon, D.P., Cermak, L.S., & Kramer, J.H. (1991). Profiles of demented and amnesic patients on the California verbal learning test: Implications for the assessment of memory disorders. Psychological Assessment, 3, 19–26. CrossRef Google Scholar
- Drachman, D.A. (2014). The amyloid hypothesis, time to move on: Amyloid is the downstream result, not cause, of Alzheimer’s disease. Alzheimer’s & Dementia, 10, 372–380. CrossRef Google Scholar
- Edmonds, E.C., Delano-Wood, L., Clark, L.R., Jak, A.J., Nation, D.A., McDonald, C.R., & Bondi, M.W. (2015). Susceptibility of the conventional criteria for mild cognitive impairment to false-positive diagnostic errors. Alzheimer’s & Dementia, 11, 415–424. CrossRef Google Scholar PubMed
- Edmonds, E.C., Delano-Wood, L., Galasko, D.R., Salmon, D.P., & Bondi, M.W. (2015). Subtle cognitive decline and biomarker staging in preclinical Alzheimer’s disease. Journal of Alzheimer’s Disease, 47, 231–242. CrossRef Google Scholar PubMed
- Edmonds, E.C., Eppig, J., Bondi, M.W., Leyden, K.M., Goodwin, B., Delano-Wood, L., & McDonald, C.R. (2016). Heterogeneous cortical atrophy patterns not captured by conventional diagnostic criteria. Neurology, 87, 2108–2116. CrossRef Google Scholar
- Folstein, M.F., Folstein, S.E., & McHugh, P.R. (1975). “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12, 189–198. CrossRef Google Scholar PubMed
- Frisoni, G.B., Fox, N.C., Jack, C.R. Jr., Scheltens, P., & Thompson, P.M. (2010). The clinical use of structural MRI in Alzheimer’s disease. Nature Reviews Neurology, 6, 67–77. CrossRef Google Scholar
- Gomar, J.J., Conejero-Goldberg, C., Davies, P., & Goldberg, T.E., Alzheimer’s Disease Neuroimaging Initiative. (2014). Extension and refinement of the predictive value of different classes of markers in ADNI: Four-year follow-up data. Alzheimer’s & Dementia, 10, 704–712. CrossRef Google Scholar PubMed
- Gorno-Tempini, M.L., Dronkers, N.F., Rankin, K.P., Ogar, J.M., Phengrasamy, L., Rosen, H.J., & Miller, B.L. (2004). Cognition and anatomy in three variants of primary progressive aphasia. Annals of Neurology, 55, 335–346. CrossRef Google Scholar PubMed
- Gorno-Tempini, M.L., Hillis, A.E., Weintraub, S., Kertesz, A., Mendez, M., Cappa, S.F., & Grossman, M. (2011). Classification of primary progressive aphasia and its variants. Neurology, 76, 1006–1014. CrossRef Google Scholar PubMed
- Gottesman, I.I. (2001). Psychopathology through a life span-genetic prism. American Psychologist, 56, 867–878. CrossRef Google Scholar PubMed
- Heister, D., Brewer, J.B., Magda, S., Blennow, K., & McEvoy, L.K., Alzheimer’s Disease Neuroimaging Initiative. (2011). Predicting MCI outcome with clinically available MRI and CSF biomarkers. Neurology, 77, 1619–1628. CrossRef Google Scholar PubMed
- Hodges, J.R., & Patterson, K. (1995). Is semantic memory consistently impaired early in the course of Alzheimer’s disease? Neuroanatomical and diagnostic implications. Neuropsychologia, 33, 441–459. CrossRef Google Scholar PubMed
- Hodges, J.R., Salmon, D.P., & Butters, N. (1992). Semantic memory impairment in Alzheimer’s disease: Failure of access or degraded knowledge? Neuropsychologia, 30, 301–314. CrossRef Google Scholar PubMed
- Hof, P.R., Vogt, B.A., Bouras, C., & Morrison, J.H. (1997). Atypical form of Alzheimer’s disease with prominent posterior cortical atrophy: A review of lesion distribution and circuit disconnection in cortical visual pathways. Vision Research, 37, 3609–3625. CrossRef Google Scholar PubMed
- Huber, S.J., Shuttleworth, E.C., Paulson, G.W., Bellchambers, M.J., & Clapp, L.E. (1986). Cortical vs subcortical dementia. Neuropsychological differences. Archives of Neurology, 43, 392–394. CrossRef Google Scholar PubMed
- Hyman, B.T., Damasio, A.R., Van Hoesen, G.W., & Barnes, C.L. (1984). Alzheimer’s disease: cell specific pathology isolates the hippocampal formation. Science, 225, 1168–1170. CrossRef Google Scholar PubMed
- Iba, M., McBride, J.D., Guo, J.L., Zhang, B., Trojanowski, J.Q., & Lee, V.M.Y. (2015). Tau pathology spread in PS19 tau transgenic mice following locus coeruleus (LC) injections of synthetic tau fibrils is determined by the LC’s afferent and efferent connections. Acta Neuropathologica, 130, 349–362. CrossRef Google Scholar PubMed
- Jack, C.R. Jr., Bennett, D.A., Blennow, K., Carrillo, M.C., Feldman, H.H., Frisoni, G.B., & Dubois, B. (2016). A/T/N: An unbiased descriptive classification scheme for Alzheimer disease biomarkers. Neurology, 87, 539–347. CrossRef Google Scholar PubMed
- Jack, C.R. Jr., Knopman, D.S., Chetelat, G., Dickson, D., Fagan, A.M., Frisoni, G.B., & Vos, S.J.B. (2016). Suspected non-Alzheimer disease pathophysiology – Concept and controversy. Nature Reviews Neurology, 12, 117–124. CrossRef Google Scholar PubMed
- Jack, C.R. Jr., Knopman, D.S., Jagust, W.J., Petersen, R.C., Weiner, M.W., Aisen, P.S., & Trojanowski, J.Q. (2013). Tracking pathophysiological processes in Alzheimer’s disease: an updated hypothetical model of dynamic biomarkers. Lancet Neurology, 12, 207–216. CrossRef Google Scholar PubMed
- Jack, C.R. Jr., Knopman, D.S., Jagust, W.J., Shaw, L.M., Aisen, P.S., & Weiner, M.W. (2010). Hypothetical model of dynamic biomarkers of the Alzheimer’s pathological cascade. Lancet Neurology, 9, 119–128. CrossRef Google Scholar PubMed
- Jacobs, D., Salmon, D.P., Tröster, A.I., & Butters, N. (1990). Intrusion errors in the figural memory of patients with Alzheimer’s and Huntington’s disease. Archives of Clinical Neuropsychology, 5, 49–57. CrossRef Google Scholar PubMed
- Jak, A.J., Bondi, M.W., Delano-Wood, L., Wierenga, C., Corey-Bloom, J., Salmon, D.P., & Delis, D.C. (2009). Quantification of five neuropsychological approaches to defining mild cognitive impairment. American Journal of Geriatric Psychiatry, 17, 368–375. CrossRef Google Scholar PubMed
- Jedynak, B.M., Lang, A., Liu, B., Katz, E., Zhang, Y., & Wyman, B.T., … Alzheimer’s Disease Neuroimaging Initiative. (2012). A computational neurodegenerative disease progression score: Method and results with the ADNI cohort. NeuroImage, 63, 1478–1486. CrossRef Google Scholar
- Jessen, F., Amariglio, R.E., van Boxtel, M., Breteler, M., Ceccaldi, M., & Chételat, G., . . . Subjective Cognitive Decline Initiative (SCD-I) Working Group. (2014). A conceptual framework for research on subjective cognitive decline in preclinical Alzheimer’s disease. Alzheimer’s & Dementia, 10, 844–852. CrossRef Google Scholar PubMed
- Johnson, J.K., Head, E., Kim, R., Starr, A., & Cotman, C.W. (1999). Clinical and pathological evidence for a frontal variant of Alzheimer disease. Archives of Neurology, 56, 1233–1239. CrossRef Google Scholar PubMed
- Katzman, R. (1976). The prevalence and malignancy of Alzheimer disease: A major killer. Archives of Neurology, 33, 217–218. CrossRef Google Scholar PubMed
- Katzman, R., & Kawas, C. (1994). The epidemiology of dementia and Alzheimer disease. In R.D. Terry, R. Katzman & K.L. Bick (Eds.), Alzheimer disease (pp. 105–122). New York: Raven Press. Google Scholar PubMed
- Knopman, D.S., Jack, C.R. Jr., Wiste, H.J., Weigand, S.D., Vemuri, P., Lowe, V.J., & Petersen, R.C. (2013). Brain injury biomarkers are not dependent on β-amyloid in normal elderly. Annals of Neurology, 73, 472–480. CrossRef Google Scholar
- Kraepelin, E. (1910). Psychiatrie: Ein Lehrbuch fur studierende und artzte. In Kraepelin E. (Ed), Handbook of psychiatry (8th ed., pp. 593–632). Leipzig: Barth. Google Scholar
- Lefleche, G., & Albert, M.S. (1995). Executive function deficits in mild Alzheimer’s disease. Neuropsychology, 9, 313–320. CrossRef Google Scholar
- Landau, S.M., Harvey, D., Madison, C.M., Reiman, E.M., Foster, N.L., Aisen, P.S., … Alzheimer’s Disease Neuroimaging Initiative. (2010). Comparing predictors of conversion and decline in mild cognitive impairment. Neurology, 75, 230–238. CrossRef Google Scholar PubMed
- La Rue, A., Matsuyama, S.S., McPherson, S., Sherman, J., & Jarvik, L.F. (1992). Cognitive performance in relatives of patients with probable Alzheimer disease: An age at onset effect? Journal of Clinical and Experimental Neuropsychology, 14, 533–538. CrossRef Google Scholar PubMed
- Mahandra, B. (1984). Dementia: A survey of the syndrome of dementia. Lancaster, England: MTP. Google Scholar
- Mathis, C.A., Wang, Y., Holt, D.P., Huang, G.-F., Debnath, M.L., & Klunk, W.E. (2003). Synthesis and evaluation of 11C-labeled 6-substituted 2-arylbenzothiazoles as amyloid imaging agents. Journal of Medicinal Chemistry, 46, 2740–2754. CrossRef Google Scholar PubMed
- Maurer, K., & Maurer, U. (2003). Alzheimer: The life of a physician and career of a disease. New York: Columbia University Press. Google Scholar
- McHugh, P.R., & Folstein, M.F. (1975). Psychiatric symptoms of Huntington’s chorea: A clinical and phenomenologic study. In D.F. Benson & D. Blumer (Eds.), Psychiatric aspects of neurological disease (pp. 267–285). New York: Raven Press. Google Scholar
- McKeith, I.G., Boeve, B.F., Dickson, D.W., Halliday, G., Taylor, J.P., Weintraub, D., & Kosaka, K. (2017). Diagnosis and management of dementia with Lewy bodies: Fourth consensus report of the DLB Consortium. Neurology, 89, 88–100. CrossRef Google Scholar PubMed
- McKhann, G., Drachman, D., Folstein, M., Katzman, R., Price, D., & Stadlan, M. (1984). Clinical diagnosis of Alzheimer’s disease: report of the NINCD-ADRDA work group. Neurology, 34, 939–944. CrossRef Google Scholar PubMed
- McKhann, G.M., Knopman, D.S., Chertkow, H., Hyman, B.T., Jack, C.R. Jr., Kawas, C.H., & Phelps, C.H. (2011). The diagnosis of dementia due to Alzheimer’s disease: Recommendations from the National Institute on Aging – Alzheimer’s Association workgroup. Alzheimer’s & Dementia, 7, 263–269. CrossRef Google Scholar
- Mendez, M.F., Ghajarania, M., & Perryman, K.M. (2002). Posterior cortical atrophy: Clinical characteristics and differences compared to Alzheimer’s disease. Dementia and Geriatric Cognitive Disorders, 14, 33–40. CrossRef Google Scholar PubMed
- Mesulam, M., Wicklund, A., Johnson, N., Rogalski, E., Leger, G.C., Rademaker, A., & Bigio, E.H. (2008). Alzheimer and frontotemporal pathology in subsets of primary progressive aphasia. Annals of Neurology, 63, 709–719. CrossRef Google Scholar PubMed
- Miller, E. (1971). On the nature of the memory disorder in presenile dementia. Neuropsychologia, 9, 75–81. CrossRef Google Scholar PubMed
- Miller, E. (1973). Short- and long-term memory in patients with presenile dementia (Alzheimer’s disease). Psychological Medicine, 3, 221–224. CrossRef Google Scholar
- Miller, E. (1975). Impaired recall and the memory disturbance in presenile dementia. British Journal of Social and Clinical Psychology, 14, 73–79. CrossRef Google Scholar PubMed
- Miller, E. (1978). Retrieval from long-term memory in presenile dementia: two tests of an hypothesis. British Journal of Social and Clinical Psychology, 17, 143–148. CrossRef Google Scholar PubMed
- Musiek, E.S., & Holtzman, D.M. (2015). Three dimensions of the amyloid hypothesis: Time, space and ‘wingmen’. Nature Neuroscience, 18, 800–806. CrossRef Google Scholar
- Nebes, R. (1989). Semantic memory in Alzheimer’s disease. Psychological Bulletin, 106, 377–394. CrossRef Google Scholar PubMed
- Nelson, P.T., Head, E., Schmitt, F.A., Davis, P.R., Neitner, J.H., Jicha, G.A., & Scheff, S.W. (2011). Alzheimer’s disease is not “brain aging”: Neuropathological, genetic, and epidemiological human studies. Acta Neuropathologica, 121, 571–587. CrossRef Google Scholar
- Nestor, P.J., Caine, D., Fryer, T.D., Clarke, J., & Hodges, J.R. (2003). The topography of metabolic deficits in posterior cortical atrophy (the visual variant of Alzheimer’s disease) with FDG-PET. Journal of Neurology, Neurosurgery, and Psychiatry, 74, 1521–1529. CrossRef Google Scholar PubMed
- Norton, L.E., Bondi, M.W., Salmon, D.P., & Goodglass, H. (1997). Deterioration of generic knowledge in patients with Alzheimer’s disease: Evidence from the Number Information Test. Journal of Clinical and Experimental Neuropsychology, 19, 857–866. CrossRef Google Scholar PubMed
- Parasuraman, R., & Haxby, J.V. (1993). Attention and brain function in Alzheimer’s disease. Neuropsychology, 7, 242–272. CrossRef Google Scholar
- Perry, R.J., & Hodges, J.R. (1999). Attention and executive deficits in Alzheimer’s disease: A critical review. Brain, 122, 383–404. CrossRef Google Scholar PubMed
- Petersen, R.C. (2009). Early diagnosis of Alzheimer disease: Is MCI too late? Current Alzheimer Research, 6, 324–330. CrossRef Google Scholar PubMed
- Petersen, R.C. (2004). Mild cognitive impairment as a diagnostic entity. Journal of Internal Medicine, 256, 183–194. CrossRef Google Scholar PubMed
- Petersen, R.C., Knopman, D.S., Boeve, B.F., Geda, Y.E., Ivnik, R.J., Smith, G.E., & Jack, C.R. Jr. (2009). Mild cognitive impairment: Ten years later. Archives of Neurology, 66, 1447–1455. CrossRef Google Scholar PubMed
- Petersen, R.C., & Morris, J.C. (2005). Mild cognitive impairment as a clinical entity and treatment target. Archives of Neurology, 62, 1160–1163. CrossRef Google Scholar PubMed
- Petersen, R.C., Smith, G.E., Ivnik, R.J., Tangalos, E.G., Schaid, D.J., Thibodeau, S.N., & Kurland, L.T. (1995). Apolipoprotein E status as a predictor of the development of Alzheimer’s disease in memory-impaired individuals. Journal of the American Medical Association, 273, 1274–1278. CrossRef Google Scholar PubMed
- Petersen, R.C., Smith, G.E., Waring, S.C., Ivnik, R.J., Tangalos, E.G., & Kokmen, E. (1999). Mild cognitive impairment: Clinical characterization and outcome. Archives of Neurology, 56, 303–308. CrossRef Google Scholar PubMed
- Petersen, R.C., Thomas, R.G., Grundman, M., Bennett, D., Doody, R., Ferris, S., & Thal, L.J. (2005). Vitamin E and donepezil for the treatment of mild cognitive impairment. New England Journal of Medicine, 352, 2379–2388. CrossRef Google Scholar PubMed
- Rascovsky, K., Hodges, J.R., Knopman, D., Mendez, M.F., Kramer, J.H., Neuhaus, J., & Miller, B.L. (2011). Sensitivity of revised diagnostic criteria for the behavioural variant of frontotemporal dementia. Brain, 134, 2456–2477. CrossRef Google Scholar PubMed
- Rascovsky, K., Salmon, D.P., Hansen, L.A., Thal, L.J., & Galasko, D. (2007). Disparate phonemic and semantic fluency deficits in autopsy-confirmed frontotemporal dementia and Alzheimer’s disease. Neuropsychology, 21, 20–30. CrossRef Google Scholar
- Rathore, S., Habes, M., Iftikhar, M.A., Shacklett, A., & Davatzikos, C. (2017). A review on neuroimaging-based classification studies and associated feature extraction methods for Alzheimer’s disease and its prodromal stages. NeuroImage, 155, 530–548. CrossRef Google Scholar PubMed
- Reed, T., Carmelli, D., Swan, G.E., Breitner, J.C.S., Welsh, K.A., Jarvik, G.P., & Auwerx, J. (1994). Lower cognitive performance in normal older adult male twins carrying the apolipoprotein E ε4 allele. Archives of Neurology, 51, 1189–1192. CrossRef Google Scholar
- Renner, J.A., Burns, J.M., Hou, C.E., McKeel, D.W. Jr., Storandt, M., & Morris, J.C. (2004). Progressive posterior cortical dysfunction: a clinicopathologic series. Neurology, 63, 1175–1180. CrossRef Google Scholar PubMed
- Richard, E., Schmand, B.A., Eikelenboom, P., & Van Gool, W.A., Alzheimer’s Disease Neuroimaging Initiative. (2013). MRI and cerebrospinal fluid biomarkers for predicting progression to Alzheimer’s disease in patients with mild cognitive impairment: a diagnostic accuracy study. BMJ Open, 3, e002541. CrossRef Google Scholar PubMed
- Rosser, A., & Hodges, J.R. (1994). Initial letter and semantic category fluency in Alzheimer’s disease, Huntington’s disease, and progressive supranuclear palsy. Journal of Neurology, Neurosurgery, and Psychiatry, 57, 1389–1394. CrossRef Google Scholar PubMed
- Rouleau, I., Salmon, D.P., Butters, N., Kennedy, C., & McGuire, K. (1992). Quantitative and qualitative analyses of clock drawings in Alzheimer’s and Huntington’s disease. Brain and Cognition, 18, 70–87. CrossRef Google Scholar PubMed
- Ryan, N.S., Keihaninejad, S., Shakespeare, T.J., Lehmann, M., Crutch, S.J., Malone, I.B., & Fox, N.C. (2013). Magnetic resonance imaging evidence for presymptomatic change in thalamus and caudate in familial Alzheimer’s disease. Brain, 136, 1399–1414. CrossRef Google Scholar PubMed
- Salmon, D.P., & Bondi, M.W. (2009). Neuropsychological assessment of dementia. Annual Review of Psychology, 60, 257–282. CrossRef Google Scholar PubMed
- Salmon, D.P., Heindel, W.C., & Lange, K.L. (1999). Differential decline in word generation from phonemic and semantic categories during the course of Alzheimer’s disease: Implications for the integrity of semantic memory. Journal of the International Neuropsychological Society, 5, 692–703. CrossRef Google Scholar PubMed
- Salmon, D.P., Kwo-on-Yuen, P.F., Heindel, W., Butters, N., & Thal, L.J. (1989). Differentiation of Alzheimer’s disease and Huntington’s disease with the Dementia Rating Scale. Archives of Neurology, 46, 1204–1208. CrossRef Google Scholar PubMed
- Salmon, D.P., Thomas, R.G., Pay, M.M., Booth, A., Hofstetter, C.R., Thal, L.J., & Kaltzman, R. (2002). Alzheimer’s disease can be accurately diagnosed in very mildly impaired individuals. Neurology, 59, 1022–1028. CrossRef Google Scholar PubMed
- Sheline, Y.I., Morris, J.C., Snyder, A.Z., Price, J.L., Yan, Z., D’Angelo, G., & Mintun, M.A. (2010). APOE4 allele disrupts resting state fMRI connectivity in the absence of amyloid plaques or decreased CSF Aβ42. Journal of Neuroscience, 30, 17035–17040. CrossRef Google Scholar PubMed
- Sims, R., & Williams, J. (2016). Defining the genetic architecture of Alzheimer’s disease: Where next? Neurodegenerative Diseases, 16, 6–11. CrossRef Google Scholar PubMed
- Small, B.J., Fratiglioni, L., Viitanen, M., Winblad, B., & Bäckman, L. (2000). The course of cognitive impairment in preclinical Alzheimer disease: three- and six-year follow-up of a population based sample. Archives of Neurology, 57, 839–844. CrossRef Google Scholar
- Smith, G.E., & Bondi, M.W. (2013). Mild cognitive impairment and dementia: Definitions, diagnosis, and treatment. New York: Oxford University Press. Google Scholar
- Snowdon, D.A., Kemper, S.J., Mortimer, J.A., Greiner, L.H., Wekstein, D.R., & Markesbery, W.R. (1996). Linguistic ability in early life and cognitive function and Alzheimer’s disease in late life. Findings from the Nun Study. Journal of the American Medical Association, 275, 528–532. CrossRef Google Scholar PubMed
- Sperling, R.A., Aisen, P.S., Beckett, L.A., Bennett, D.A., Craft, S., Fagan, A.M., & Phelps, C.H. (2011). Toward defining the preclinical stages of Alzheimer’s disease: Recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimer’s & Dementia, 7, 280–292. CrossRef Google Scholar PubMed
- Squire, L.R. (1987). Memory and brain. New York: Oxford University Press. Google Scholar PubMed
- Stelzmann, R.A., Schnitzlein, N., & Murtagh, F.R. (1995). An English translation of Alzheimer’s paper, “über eine eigenartige Erkankung der Hirnrinde.”. Clinical Anatomy, 8, 429–431. CrossRef Google Scholar
- Storandt, M., Botwinick, J., Danziger, W.L., Berg, L., & Hughes, C.P. (1984). Psychometric differentiation of mild senile dementia of the Alzheimer type. Archives of Neurology, 41, 497–499. CrossRef Google Scholar PubMed
- Strittmatter, W.J., Saunders, A.M., Schmechel, D., Pericak-Vance, M., Enghild, J., Salvesen, G.S., & Roses, A.D. (1993). Apolipoprotein-E -- High-avidity binding to B-amyloid and increased frequency of type 4 allele in late-onset familial Alzheimer disease. Proceedings of the National Academy of Sciences of the United States of America, 90, 9649–9653. Google Scholar
- Tenovuo, O., Kemppainen, N., Aalto, S., Nagren, K., & Rinne, J.O. (2008). Posterior cortical atrophy: A rare form of dementia with in vivo evidence of amyloid-beta accumulation. Journal of Alzheimer’s Disease, 15, 351–355. CrossRef Google Scholar PubMed
- Weiner, M.W., Veitch, D.P., Aisen, P.S., Beckett, L.A., Cairns, N.J., Green, R.C., & Trojanowski, J.Q. (2013). The Alzheimer’s Disease Neuroimaging Initiative: A review of papers published since its inception. Alzheimer’s & Dementia, 9, e111–e194. CrossRef Google Scholar
- Winblad, B., Palmer, K., Kivipelto, M., Jelic, V., Fratiglioni, L., Wahlund, L.O., & Petersen, R.C. (2004). Mild cognitive impairment–beyond controversies, towards a consensus: Report of the Inter-national Working Group on Mild Cognitive Impairment. Journal of Internal Medicine, 256, 240–246. CrossRef Google Scholar
- Wirth, M., Madison, C.M., Rabinovici, G.D., Oh, H., Landau, S.M., & Jagust, W.J. (2013). Alzheimer’s disease neurodegenerative biomarkers are associated with decreased cognitive function but not β-Amyloid in cognitively normal older individuals. Journal of Neuroscience, 33, 5553–5563. CrossRef Google Scholar
- World Health Organization. (1992). International Classification of Diseases (10th Edition, Geneva, Switzerland: WHO. Google Scholar PubMed
The neuropsychological aspects of multiple sclerosis (MS) have evolved over the past three decades. What was once thought to be a rare occurrence, cognitive dysfunctionis now viewed as one of the most disabling symptoms of the disease, with devastating effects on patients’ quality of life. This selective review will highlight majorinnovations and scientific discoveries in the areas of neuropathology, neuroimaging, diagnosis, and treatment that pertain to our understanding of the neuropsychologicalaspects of MS. Specifically, we focus on the recent discovery that MS produces pathogical lesions of gray matter (GM) that have consequences for cognitive functions.Methods for imaging these GM lesions in MS are discussed along with multimodal imaging studies that integrate structural and functional imaging methods to providea better understanding of the relationship between cognitive test performance and functional reserve. Innovations in the screening and comprehensive assessment ofcognitive disorders are presented along with recent research that examines cognitive dysfunction in pediatric MS. Results of innovative outcome studies in cognitiverehabilitation are discussed. Finally, we highlight trends for potential future innovations over the next decade. (JINS, 2017, 23,832–842)
- Akbar, N., Banwell, B., Sled, J.G., Binns, M.A., Doesburg, S.M., Rypma, B., & Till, C. (2016). Brain activation patterns and cognitive processing speed in patients with pediatric-onset multiple sclerosis. Journal of Clinical and Experimental Neuropsychology, 38(4), 393–403. doi: 10.1080/13803395.2015.1119255 CrossRef Google Scholar PubMed
- Amato, M.P., Bartolozzi, M.L., Zipoli, V., Portaccio, E., Mortilla, M., Guidi, L., & De Stefano, N. (2004). Neocortical volume decrease in relapsing-remitting MS patients with mild cognitive impairment. Neurology, 63(1), 89–93. CrossRef Google Scholar PubMed
- Amato, M.P., Goretti, B., Ghezzi, A., Hakiki, B., Niccolai, C., & Lori, S., . . . MS Study Group of the Italian Neurological Society. (2014). Neuropsychological features in childhood and juvenile multiple sclerosis: Five-year follow-up. Neurology, 83(16), 1432–1438. doi: 10.1212/WNL.0000000000000885 CrossRef Google Scholar PubMed
- Arnett, P.A., Rao, S.M., Bernardin, L., Grafman, J., Yetkin, F.Z., & Lobeck, L. (1994). Relationship between frontal lobe lesions and Wisconsin Card Sorting Test performance in patients with multiple sclerosis. Neurology, 44(3 Pt 1), 420–425. CrossRef Google Scholar PubMed
- Audoin, B., Zaaraoui, W., Reuter, F., Rico, A., Malikova, I., Confort-Gouny, S., & Ranjeva, J.P. (2010). Atrophy mainly affects the limbic system and the deep grey matter at the first stage of multiple sclerosis. Journal of Neurology, Neurosurgery, and Psychiatry, 81(6), 690–695. doi: 10.1136/jnnp.2009.188748 CrossRef Google Scholar PubMed
- Barcellos, L.F., Bellesis, K.H., Shen, L., Shao, X., Chinn, T., Frndak, S., & Benedict, R.H. (2017). Remote assessment of verbal memory in MS patients using the California Verbal Learning Test. Multiple Sclerosis, 1352458517694087. doi: 10.1177/1352458517694087 Google Scholar PubMed
- Batista, S., Zivadinov, R., Hoogs, M., Bergsland, N., Heininen-Brown, M., Dwyer, M.G., & Benedict, R.H. (2012). Basal ganglia, thalamus and neocortical atrophy predicting slowed cognitive processing in multiple sclerosis. Jorunal of Neurology, 259(1), 139–146. doi: 10.1007/s00415-011-6147-1 CrossRef Google Scholar PubMed
- Beatty, W.W., & Goodkin, D.E. (1990). Screening for cognitive impairment in multiple sclerosis. An evaluation of the Mini-Mental State Examination. Archives of Neurology, 47(3), 297–301. CrossRef Google Scholar PubMed
- Benedict, R.H., Amato, M.P., Boringa, J., Brochet, B., Foley, F., Fredrikson, S., & Langdon, D. (2012). Brief International Cognitive Assessment for MS (BICAMS): International standards for validation. BMC Neurology, 12, 55. doi: 10.1186/1471-2377-12-55 CrossRef Google Scholar PubMed
- Benedict, R.H., Carone, D.A., & Bakshi, R. (2004). Correlating brain atrophy with cognitive dysfunction, mood disturbances, and personality disorder in multiple sclerosis. Journal of Neuroimaging, 14(3 Suppl), 36S–45S. doi: 10.1177/1051228404266267 CrossRef Google Scholar PubMed
- Benedict, R.H., Cookfair, D., Gavett, R., Gunther, M., Munschauer, F., Garg, N., &Weinstock-Guttman, B. (2006). Validity of the minimal assessment of cognitive function in multiple sclerosis (MACFIMS). Journal of the International Neuropsychological Society, 12(4), 549–558. CrossRef Google Scholar
- Benedict, R.H., DeLuca, J., Phillips, G., LaRocca, N., Hudson, L.D., Rudick, R., & Multiple Sclerosis Outcome Assessments Consortium. (2017). Validity of the Symbol Digit Modalities Test as a cognition performance outcome measure for multiple sclerosis. Multiple Sclerosis, 1352458517690821. doi: 10.1177/1352458517690821 Google Scholar PubMed
- Benedict, R.H., Fischer, J.S., Archibald, C.J., Arnett, P.A., Beatty, W.W., Bobholz, J., & Munschauer, F. (2002). Minimal neuropsychological assessment of MS patients: A consensus approach. The Clinical neuropsychologist, 16(3), 381–397. doi: 10.1076/clin.16.3.381.13859 CrossRef Google Scholar PubMed
- Benedict, R.H., Morrow, S.A., Weinstock Guttman, B., Cookfair, D., & Schretlen, D.J. (2010). Cognitive reserve moderates decline in information processing speed in multiple sclerosis patients. Journal of the International Neuropsychological Society, 16(5), 829–835. doi: 10.1017/S1355617710000688 CrossRef Google Scholar PubMed
- Benedict, R.H., Ramasamy, D., Munschauer, F., Weinstock-Guttman, B., & Zivadinov, R. (2009). Memory impairment in multiple sclerosis: Correlation with deep grey matter and mesial temporal atrophy. Journal of Neurology, Neurosurgery, and Psychiatry, 80(2), 201–206. doi: 10.1136/jnnp.2008.148403 CrossRef Google Scholar PubMed
- Benedict, R.H., Rodgers, J.D., Emmert, N., Kininger, R., & Weinstock-Guttman, B. (2014). Negative work events and accommodations in employed multiple sclerosis patients. Multiple Sclerosis, 20(1), 116–119. doi: 10.1177/1352458513494492 CrossRef Google Scholar PubMed
- Bergsland, N., Horakova, D., Dwyer, M.G., Dolezal, O., Seidl, Z.K., Vaneckova, M., & Zivadinov, R. (2012). Subcortical and cortical gray matter atrophy in a large sample of patients with clinically isolated syndrome and early relapsing-remitting multiple sclerosis. AJNR American Journal of Neuroradiology, 33(8), 1573–1578. doi: 10.3174/ajnr.A3086 CrossRef Google Scholar
- Bo, L., Vedeler, C.A., Nyland, H., Trapp, B.D., & Mork, S.J. (2003). Intracortical multiple sclerosis lesions are not associated with increased lymphocyte infiltration. Multiple Sclerosis, 9(4), 323–331. CrossRef Google Scholar
- Bobholz, J.A., Rao, S.M., Lobeck, L., Elsinger, C., Gleason, A., Kanz, J., & Maas, E. (2006). fMRI study of episodic memory in relapsing-remitting MS: Correlation with T2 lesion volume. Neurology, 67(9), 1640–1645. doi: 10.1212/01.wnl.0000242885.71725.76 CrossRef Google Scholar PubMed
- Bodini, B., Khaleeli, Z., Cercignani, M., Miller, D.H., Thompson, A.J., & Ciccarelli, O. (2009). Exploring the relationship between white matter and gray matter damage in early primary progressive multiple sclerosis: An in vivo study with TBSS and VBM. Human Brain Mapping, 30(9), 2852–2861. doi: 10.1002/hbm.20713 CrossRef Google Scholar
- Bodini, B., Veronese, M., Garcia-Lorenzo, D., Battaglini, M., Poirion, E., Chardain, A., & Stankoff, B. (2016). Dynamic imaging of individual remyelination profiles in multiple sclerosis. Annals of Neurology. [Epub ahead of print]. doi: 10.1002/ana.24620 CrossRef Google Scholar
- Calabrese, M., Agosta, F., Rinaldi, F., Mattisi, I., Grossi, P., Favaretto, A., & Filippi, M. (2009). Cortical lesions and atrophy associated with cognitive impairment in relapsing-remitting multiple sclerosis. Archives of Neurology, 66(9), 1144–1150. doi: 10.1001/archneurol.2009.174 CrossRef Google Scholar PubMed
- Calabrese, M., & Gallo, P. (2009). Magnetic resonance evidence of cortical onset of multiple sclerosis. Multiple Sclerosis, 15(8), 933–941. doi: 10.1177/1352458509106510 CrossRef Google Scholar PubMed
- Carone, D.A., Benedict, R.H., Munschauer, F.E. III, Fishman, I., & Weinstock-Guttman, B. (2005). Interpreting patient/informant discrepancies of reported cognitive symptoms in MS. Journal of the International Neuropsychological Society, 11(5), 574–583. doi: 10.1017/S135561770505068X CrossRef Google Scholar PubMed
- Charcot, J.M. (1877). Lectures on the diseases of the nervous system delivered at La Salpetriere. London: New Sydenham Society. Google Scholar
- Charvet, L.E., Cersosimo, B., Schwarz, C., Belman, A., & Krupp, L.B. (2016). Behavioral symptoms in pediatric multiple sclerosis: Relation to fatigue and cognitive impairment. Journal of Child Neurology, 31(8), 1062–1067. doi: 10.1177/0883073816636227 CrossRef Google Scholar PubMed
- Charvet, L.E., O’Donnell, E.H., Belman, A.L., Chitnis, T., Ness, J.M., & Parrish, J., . . . Centers, US Network of Pediatric MS Centers. (2014). Longitudinal evaluation of cognitive functioning in pediatric multiple sclerosis: Report from the US Pediatric Multiple Sclerosis Network. Multiple Sclerosis, 20(11), 1502–1510. doi: 10.1177/1352458514527862 CrossRef Google Scholar PubMed
- Charvet, L.E., Shaw, M., Frontario, A., Langdon, D., & Krupp, L. (2017). Cognitive impairment in pediatric-onset multiple sclerosis is detected by the Brief International Cognitive Assessment for Multiple Sclerosis and computerized cognitive testing. Multiple Sclerosis. [Epub ahead of print]. doi: 10.1177/1352458517701588 CrossRef Google Scholar
- Chiaravalloti, N.D., Genova, H.M., & DeLuca, J. (2015). Cognitive rehabilitation in multiple sclerosis: The role of plasticity. Frontirs in Neurology, 6, 67. doi: 10.3389/fneur.2015.00067 Google Scholar PubMed
- Chiaravalloti, N.D., Moore, N.B., Nikelshpur, O.M., & DeLuca, J. (2013). An RCT to treat learning impairment in multiple sclerosis: The MEMREHAB trial. Neurology, 81(24), 2066–2072. doi: 10.1212/01.wnl.0000437295.97946.a8 CrossRef Google Scholar PubMed
- Damjanovic, D., Valsasina, P., Rocca, M.A., Stromillo, M.L., Gallo, A., Enzinger, C., & Filippi, M. (2017). Hippocampal and deep gray matter nuclei atrophy is relevant for explaining cognitive impairment in MS: A multicenter study. AJNR American Journal of Neuroradiology, 38(1), 18–24. doi: 10.3174/ajnr.A4952 CrossRef Google Scholar PubMed
- das Nair, R., Martin, K.J., & Lincoln, N.B. (2016). Memory rehabilitation for people with multiple sclerosis. The Cochrane Database of Systematic Reviews, 3, CD008754. doi: 10.1002/14651858.CD008754.pub3 Google Scholar PubMed
- DeLuca, J., Barbieri-Berger, S., & Johnson, S.K. (1994). The nature of memory impairments in multiple sclerosis: Acquisition versus retrieval. Journal of Clinical and Experimental Neuropsychology, 16(2), 183–189. doi: 10.1080/01688639408402629 CrossRef Google Scholar PubMed
- DeLuca, J., Leavitt, V.M., Chiaravalloti, N., & Wylie, G. (2013). Memory impairment in multiple sclerosis is due to a core deficit in initial learning. Journal of Neurology, 260(10), 2491–2496. doi: 10.1007/s00415–013-6990-3 CrossRef Google Scholar PubMed
- Feinstein, A., O’Connor, P., Akbar, N., Moradzadeh, L., Scott, C.J., & Lobaugh, N.J. (2010). Diffusion tensor imaging abnormalities in depressed multiple sclerosis patients. Multiple Sclerosis, 16(2), 189–196. doi: 10.1177/1352458509355461 CrossRef Google Scholar PubMed
- Feinstein, A., Roy, P., Lobaugh, N., Feinstein, K., O’Connor, P., & Black, S. (2004). Structural brain abnormalities in multiple sclerosis patients with major depression. Neurology, 62(4), 586–590. CrossRef Google Scholar PubMed
- Fisher, E., Lee, J.C., Nakamura, K., & Rudick, R.A. (2008). Gray matter atrophy in multiple sclerosis: A longitudinal study. Annals of Neurology, 64(3), 255–265. doi: 10.1002/ana.21436 CrossRef Google Scholar PubMed
- Folstein, M.F., Folstein, S.E., & McHugh, P.R. (1975). “Mini-mental state”. A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12(3), 189–198. CrossRef Google Scholar PubMed
- Geurts, J.J., Bo, L., Pouwels, P.J., Castelijns, J.A., Polman, C.H., & Barkhof, F. (2005). Cortical lesions in multiple sclerosis: Combined postmortem MR imaging and histopathology. AJNR American Journal of Neuroradiology, 26(3), 572–577. Google Scholar PubMed
- Geurts, J.J., Bo, L., Roosendaal, S.D., Hazes, T., Daniels, R., Barkhof, F., & van der Valk, P. (2007). Extensive hippocampal demyelination in multiple sclerosis. Journal of Neuropathology and Experimental Neurology, 66(9), 819–827. doi: 10.1097/nen.0b013e3181461f54 CrossRef Google Scholar PubMed
- Geurts, J.J., Calabrese, M., Fisher, E., & Rudick, R.A. (2012). Measurement and clinical effect of grey matter pathology in multiple sclerosis. Lancet Neurology, 11(12), 1082–1092. doi: 10.1016/S1474-4422(12)70230-2 CrossRef Google Scholar PubMed
- Geurts, J.J., Pouwels, P.J., Uitdehaag, B.M., Polman, C.H., Barkhof, F., & Castelijns, J.A. (2005). Intracortical lesions in multiple sclerosis: Improved detection with 3D double inversion-recovery MR imaging. Radiology, 236(1), 254–260. doi: 10.1148/radiol.2361040450 CrossRef Google Scholar PubMed
- Geurts, J.J., Roosendaal, S.D., Calabrese, M., Ciccarelli, O., Agosta, F., Chard, D.T., & Group, M.S. (2011). Consensus recommendations for MS cortical lesion scoring using double inversion recovery MRI. Neurology, 76(5), 418–424. doi: 10.1212/WNL.0b013e31820a0cc4 CrossRef Google Scholar PubMed
- Gilmore, C.P., DeLuca, G.C., Bo, L., Owens, T., Lowe, J., Esiri, M.M., & Evangelou, N. (2009). Spinal cord neuronal pathology in multiple sclerosis. Brain Pathology, 19(4), 642–649. doi: 10.1111/j.1750-3639.2008.00228.x CrossRef Google Scholar PubMed
- Gilmore, C.P., Donaldson, I., Bo, L., Owens, T., Lowe, J., & Evangelou, N. (2009). Regional variations in the extent and pattern of grey matter demyelination in multiple sclerosis: A comparison between the cerebral cortex, cerebellar cortex, deep grey matter nuclei and the spinal cord. Journal of Neurology, Neurosurgery, and Psychiatry, 80(2), 182–187. doi: 10.1136/jnnp.2008.148767 CrossRef Google Scholar PubMed
- Gilmore, C.P., Geurts, J.J., Evangelou, N., Bot, J.C., van Schijndel, R.A., Pouwels, P.J., & Bo, L. (2009). Spinal cord grey matter lesions in multiple sclerosis detected by post-mortem high field MR imaging. Multiple Sclerosis, 15(2), 180–188. doi: 10.1177/1352458508096876 CrossRef Google Scholar PubMed
- Haider, L., Simeonidou, C., Steinberger, G., Hametner, S., Grigoriadis, N., Deretzi, G., & Frischer, J.M. (2014). Multiple sclerosis deep grey matter: The relation between demyelination, neurodegeneration, inflammation and iron. Journal of Neurology, Neurosurgery, and Psychiatry, 85(12), 1386–1395. doi: 10.1136/jnnp-2014-307712 CrossRef Google Scholar PubMed
- Houtchens, M.K., Benedict, R.H., Killiany, R., Sharma, J., Jaisani, Z., Singh, B., & Bakshi, R. (2007). Thalamic atrophy and cognition in multiple sclerosis. Neurology, 69(12), 1213–1223. doi: 10.1212/01.wnl.0000276992.17011.b5 CrossRef Google Scholar PubMed
- Howell, O.W., Reeves, C.A., Nicholas, R., Carassiti, D., Radotra, B., Gentleman, S.M., & Reynolds, R. (2011). Meningeal inflammation is widespread and linked to cortical pathology in multiple sclerosis. Brain, 134(Pt 9), 2755–2771. doi: 10.1093/brain/awr182 CrossRef Google Scholar PubMed
- Huitinga, I., De Groot, C.J., Van der Valk, P., Kamphorst, W., Tilders, F.J., & Swaab, D.F. (2001). Hypothalamic lesions in multiple sclerosis. Journal of Neuropathology and Experimental Neurology, 60(12), 1208–1218. CrossRef Google Scholar PubMed
- Kilsdonk, I.D., Jonkman, L.E., Klaver, R., van Veluw, S.J., Zwanenburg, J.J., Kuijer, J.P., & Geurts, J.J. (2016). Increased cortical grey matter lesion detection in multiple sclerosis with 7 T MRI: A post-mortem verification study. Brain, 139(Pt 5), 1472–1481. doi: 10.1093/brain/aww037 CrossRef Google Scholar
- Koini, M., Filippi, M., Rocca, M.A., Yousry, T., Ciccarelli, O., & Tedeschi, G., . . . MAGNIMS fMRI Study Group. (2016). Correlates of executive functions in multiple sclerosis based on structural and functional MR imaging: Insights from a multicenter study. Radiology, 280(3), 869–879. doi: 10.1148/radiol.2016151809 CrossRef Google Scholar PubMed
- Kooi, E.J., Strijbis, E.M., van der Valk, P., & Geurts, J.J. (2012). Heterogeneity of cortical lesions in multiple sclerosis: Clinical and pathologic implications. Neurology, 79(13), 1369–1376. doi: 10.1212/WNL.0b013e31826c1b1c CrossRef Google Scholar PubMed
- Krupp, L.B., Christodoulou, C., Melville, P., Scherl, W.F., MacAllister, W.S., & Elkins, L.E. (2004). Donepezil improved memory in multiple sclerosis in a randomized clinical trial. Neurology, 63(9), 1579–1585. CrossRef Google Scholar
- Krupp, L.B., Christodoulou, C., Melville, P., Scherl, W.F., Pai, L.Y., Muenz, L.R., & Wishart, H. (2011). Multicenter randomized clinical trial of donepezil for memory impairment in multiple sclerosis. Neurology, 76(17), 1500–1507. doi: 10.1212/WNL.0b013e318218107a CrossRef Google Scholar PubMed
- Kutzelnigg, A., Faber-Rod, J.C., Bauer, J., Lucchinetti, C.F., Sorensen, P.S., Laursen, H., & Lassmann, H. (2007). Widespread demyelination in the cerebellar cortex in multiple sclerosis. Brain Pathology, 17(1), 38–44. doi: 10.1111/j.1750-3639.2006.00041.x CrossRef Google Scholar PubMed
- Kutzelnigg, A., Lucchinetti, C.F., Stadelmann, C., Bruck, W., Rauschka, H., Bergmann, M., & Lassmann, H. (2005). Cortical demyelination and diffuse white matter injury in multiple sclerosis. Brain, 128(Pt 11), 2705–2712. doi: 10.1093/brain/awh641 CrossRef Google Scholar PubMed
- Langdon, D. (2016). A useful annual review of cognition in relapsing MS is beyond most neurologists - NO. Multiple Sclerosis, 22(6), 728–730. doi: 10.1177/1352458516640610 CrossRef Google Scholar
- Magliozzi, R., Howell, O., Vora, A., Serafini, B., Nicholas, R., Puopolo, M., & Aloisi, F. (2007). Meningeal B-cell follicles in secondary progressive multiple sclerosis associate with early onset of disease and severe cortical pathology. Brain, 130(Pt 4), 1089–1104. doi: 10.1093/brain/awm038 CrossRef Google Scholar PubMed
- Mainero, C., Louapre, C., Govindarajan, S.T., Gianni, C., Nielsen, A.S., Cohen-Adad, J., & Kinkel, R.P. (2015). A gradient in cortical pathology in multiple sclerosis by in vivo quantitative 7 T imaging. Brain, 138(Pt 4), 932–945. doi: 10.1093/brain/awv011 CrossRef Google Scholar PubMed
- Mike, A., Glanz, B.I., Hildenbrand, P., Meier, D., Bolden, K., Liguori, M., & Guttmann, C.R. (2011). Identification and clinical impact of multiple sclerosis cortical lesions as assessed by routine 3T MR imaging. AJNR American Journal of Neuroradiology, 32(3), 515–521. doi: 10.3174/ajnr.A2340 CrossRef Google Scholar PubMed
- Minagar, A., Barnett, M.H., Benedict, R.H., Pelletier, D., Pirko, I., Sahraian, M.A., & Zivadinov, R. (2013). The thalamus and multiple sclerosis: Modern views on pathologic, imaging, and clinical aspects. Neurology, 80(2), 210–219. doi: 10.1212/WNL.0b013e31827b910b CrossRef Google Scholar PubMed
- Morrow, S.A., Jurgensen, S., Forrestal, F., Munchauer, F.E., & Benedict, R.H. (2011). Effects of acute relapses on neuropsychological status in multiple sclerosis patients. Journal of Neurology, 258(9), 1603–1608. doi: 10.1007/s00415-011-5975-3 CrossRef Google Scholar PubMed
- Morrow, S.A., Smerbeck, A., Patrick, K., Cookfair, D., Weinstock-Guttman, B., & Benedict, R.H. (2013). Lisdexamfetamine dimesylate improves processing speed and memory in cognitively impaired MS patients: A phase II study. Journal of Neurology, 260(2), 489–497. doi: 10.1007/s00415-012-6663-7 CrossRef Google Scholar PubMed
- Morrow, S.A., Weinstock-Guttman, B., Munschauer, F.E., Hojnacki, D., & Benedict, R.H. (2009). Subjective fatigue is not associated with cognitive impairment in multiple sclerosis: Cross-sectional and longitudinal analysis. Multiple Sclerosis, 15(8), 998–1005. doi: 10.1177/1352458509106213 CrossRef Google Scholar
- Nelson, F., Akhtar, M.A., Zuniga, E., Perez, C.A., Hasan, K.M., Wilken, J., & Steinberg, J.L. (2017). Novel fMRI working memory paradigm accurately detects cognitive impairment in multiple sclerosis. Multiple Sclerosis, 23(6), 836–847. doi: 10.1177/1352458516666186 CrossRef Google Scholar PubMed
- Nelson, F., Datta, S., Garcia, N., Rozario, N.L., Perez, F., Cutter, G., & Wolinsky, J.S. (2011). Intracortical lesions by 3T magnetic resonance imaging and correlation with cognitive impairment in multiple sclerosis. Multiple Sclerosis, 17(9), 1122–1129. doi: 10.1177/1352458511405561 CrossRef Google Scholar PubMed
- Nelson, F., Poonawalla, A., Datta, S., Wolinsky, J., & Narayana, P. (2014). Is 3D MPRAGE better than the combination DIR/PSIR for cortical lesion detection at 3T MRI? Multiple Sclerosis and Related Disorders, 3(2), 253–257. doi: 10.1016/j.msard.2013.10.002 CrossRef Google Scholar
- Nelson, F., Poonawalla, A., Hou, P., Wolinsky, J.S., & Narayana, P.A. (2008). 3D MPRAGE improves classification of cortical lesions in multiple sclerosis. Multiple Sclerosis, 14(9), 1214–1219. doi: 10.1177/1352458508094644 CrossRef Google Scholar PubMed
- Nelson, F., Poonawalla, A.H., Hou, P., Huang, F., Wolinsky, J.S., & Narayana, P.A. (2007). Improved identification of intracortical lesions in multiple sclerosis with phase-sensitive inversion recovery in combination with fast double inversion recovery MR imaging. AJNR American Journal of Neuroradiology, 28(9), 1645–1649. doi: 10.3174/ajnr.A0645 CrossRef Google Scholar PubMed
- Nielsen, A.S., Kinkel, R.P., Tinelli, E., Benner, T., Cohen-Adad, J., & Mainero, C. (2012). Focal cortical lesion detection in multiple sclerosis: 3 Tesla DIR versus 7 Tesla FLASH-T2. Journal of Magnetic Resonance Imaging, 35(3), 537–542. doi: 10.1002/jmri.22847 CrossRef Google Scholar PubMed
- O’Brien, A., Gaudino-Goering, E., Shawaryn, M., Komaroff, E., Moore, N.B., & DeLuca, J. (2007). Relationship of the Multiple Sclerosis Neuropsychological Questionnaire (MSNQ) to functional, emotional, and neuropsychological outcomes. Archives of Clinical Neuropsychology, 22(8), 933–948. doi: 10.1016/j.acn.2007.07.002 CrossRef Google Scholar PubMed
- Pardini, M., Uccelli, A., Grafman, J., Yaldizli, O., Mancardi, G., & Roccatagliata, L. (2014). Isolated cognitive relapses in multiple sclerosis. Journal of Neurology, Neurosurgery, and Psychiatry, 85(9), 1035–1037. doi: 10.1136/jnnp2013-307275 CrossRef Google Scholar PubMed
- Peterson, J.W., Bo, L., Mork, S., Chang, A., & Trapp, B.D. (2001). Transected neurites, apoptotic neurons, and reduced inflammation in cortical multiple sclerosis lesions. Annals of Neurology, 50(3), 389–400. CrossRef Google Scholar PubMed
- Popescu, V., Klaver, R., Voorn, P., Galis-de Graaf, Y., Knol, D.L., Twisk, J.W., & Geurts, J.J. (2015). What drives MRI-measured cortical atrophy in multiple sclerosis? Multiple Sclerosis, 21(10), 1280–1290. doi: 10.1177/1352458514562440 CrossRef Google Scholar PubMed
- Preziosa, P., Rocca, M.A., Pagani, E., Stromillo, M.L., Enzinger, C., Gallo, A., & Group, M.S. (2016). Structural MRI correlates of cognitive impairment in patients with multiple sclerosis: A Multicenter Study. Human Brain Mapping, 37(4), 1627–1644. doi: 10.1002/hbm.23125 CrossRef Google Scholar PubMed
- Rao, S.M. (1991). A manual for the brief, repeatable battery of neuropsychological tests in multiple sclerosis. New York: National Multiple Sclerosis Society. Google Scholar
- Rao, S.M. (1995). Neuropsychology of multiple sclerosis. Current Opinion in Neurology, 8(3), 216–220. CrossRef Google Scholar PubMed
- Rao, S.M., Glatt, S., Hammeke, T.A., McQuillen, M.P., Khatri, B.O., Rhodes, A.M., & Pollard, S. (1985). Chronic progressive multiple sclerosis. Relationship between cerebral ventricular size and neuropsychological impairment. Archives of Neurology, 42(7), 678–682. CrossRef Google Scholar PubMed
- Rao, S.M., Leo, G.J., Bernardin, L., & Unverzagt, F. (1991). Cognitive dysfunction in multiple sclerosis. I. Frequency, patterns, and prediction. Neurology, 41(5), 685–691. CrossRef Google Scholar PubMed
- Rao, S.M., Leo, G.J., Ellington, L., Nauertz, T., Bernardin, L., & Unverzagt, F. (1991). Cognitive dysfunction in multiple sclerosis. II. Impact on employment and social functioning. Neurology, 41(5), 692–696. Google Scholar PubMed
- Rao, S.M., Leo, G.J., Haughton, V.M., St Aubin-Faubert, P., & Bernardin, L. (1989). Correlation of magnetic resonance imaging with neuropsychological testing in multiple sclerosis. Neurology, 39(2 Pt 1), 161–166. CrossRef Google Scholar PubMed
- Rao, S.M., Leo, G.J., & St Aubin-Faubert, P. (1989). On the nature of memory disturbance in multiple sclerosis. Journal of Clinical and Experimental Neuropsychology, 11(5), 699–712. doi: 10.1080/01688638908400926 CrossRef Google Scholar PubMed
- Rao, S.M., Losinski, G., Mourany, L., Schindler, D., Mamone, B., Reece, C., & Alberts, J. (2017). Processing speed test: Validation of a self-administered, iPad(R)-based tool for screening cognitive dysfunction in a clinic setting. Multiple Sclerosis, 1352458516688955. doi: 10.1177/1352458516688955 Google Scholar
- Rao, S.M., St Aubin-Faubert, P., & Leo, G.J. (1989). Information processing speed in patients with multiple sclerosis. Journal of Clinical and Experimental Neuropsychology, 11(4), 471–477. doi: 10.1080/01688638908400907 CrossRef Google Scholar PubMed
- Ricreflli, G., Rocca, M.A., Pagani, E., Rodegher, M.E., Rossi, P., Falini, A., & Filippi, M. (2011). Cognitive impairment in multiple sclerosis is associated to different patterns of gray matter atrophy according to clinical phenotype. Human Brain Mapping, 32(10), 1535–1543. doi: 10.1002/hbm.21125 CrossRef Google Scholar PubMed
- Rocca, M.A., Absinta, M., Amato, M.P., Moiola, L., Ghezzi, A., Veggiotti, P., & Filippi, M. (2014). Posterior brain damage and cognitive impairment in pediatric multiple sclerosis. Neurology, 82(15), 1314–1321. doi: 10.1212/WNL.0000000000000309 CrossRef Google Scholar PubMed
- Rocca, M.A., Pravata, E., Valsasina, P., Radaelli, M., Colombo, B., Vacchi, L., & Filippi, M. (2015). Hippocampal-DMN disconnectivity in MS is related to WM lesions and depression. Human Brain Mapping, 36(12), 5051–5063. doi: 10.1002/hbm.22992 CrossRef Google Scholar
- Romero, K., Shammi, P., & Feinstein, A. (2015). Neurologists accuracy in predicting cognitive impairment in multiple sclerosis. Multiple Sclerosis and Related Disorders, 4(4), 291–295. doi: 10.1016/j.msard.2015.05.009 CrossRef Google Scholar PubMed
- Roosendaal, S.D., Moraal, B., Pouwels, P.J., Vrenken, H., Castelijns, J.A., Barkhof, F., &Geurts, J.J. (2009). Accumulation of cortical lesions in MS: Relation with cognitive impairment. Multiple Sclerosis, 15(6), 708–714. doi: 10.1177/1352458509102907 CrossRef Google Scholar PubMed
- Roosendaal, S.D., Moraal, B., Vrenken, H., Castelijns, J.A., Pouwels, P.J., Barkhof, F., &Geurts, J.J. (2008). In vivo MR imaging of hippocampal lesions in multiple sclerosis. Journal of Magnetic Resonance Imaging, 27(4), 726–731. doi: 10.1002/jmri.21294 CrossRef Google Scholar PubMed
- Roy, S., Schwartz, C.E., Duberstein, P., Dwyer, M.G., Zivadinov, R., Bergsland, N., & Benedict, R.H. (2016). Synergistic Effects of Reserve and Adaptive Personality in Multiple Sclerosis. Journal of the International Neuropsychological Society, 22(9), 920–927. doi: 10.1017/S1355617716000333 CrossRef Google Scholar PubMed
- Sandroff, B.M., Motl, R.W., Scudder, M.R., & DeLuca, J. (2016). Systematic, evidence-based review of exercise, physical activity, and physical fitness effects on cognition in persons with multiple sclerosis. Neuropsychology Review, 26(3), 271–294. doi: 10.1007/s11065-016-9324-2 CrossRef Google Scholar PubMed
- Sandroff, B.M., Schwartz, C.E., & DeLuca, J. (2016). Measurement and maintenance of reserve in multiple sclerosis. Journal of Neurology, 263(11), 2158–2169. doi: 10.1007/s00415-016-8104-5 CrossRef Google Scholar PubMed
- Sandry, J., Akbar, N., Zuppichini, M., & DeLuca, J. (2016). Cognitive rehabilitation in multiple sclerosis. In M.-K. Sun (Ed.), Research progress in Alzheimer’s disease and Dementia, (Vol. 6, pp. 195–233). New York: Nova Science Publisher. Google Scholar
- Schoonheim, M.M., Popescu, V., Rueda Lopes, F.C., Wiebenga, O.T., Vrenken, H., Douw, L., & Barkhof, F. (2012). Subcortical atrophy and cognition: Sex effects in multiple sclerosis. Neurology, 79(17), 1754–1761. doi: 10.1212/WNL.0b013e3182703f46 CrossRef Google Scholar PubMed
- Seewann, A., Vrenken, H., Kooi, E.J., van der Valk, P., Knol, D.L., Polman, C.H., & Geurts, J.J. (2011). Imaging the tip of the iceberg: Visualization of cortical lesions in multiple sclerosis. Multiple Sclerosis, 17(10), 1202–1210. doi: 10.1177/1352458511406575 CrossRef Google Scholar PubMed
- Sethi, V., Yousry, T.A., Muhlert, N., Ron, M., Golay, X., Wheeler-Kingshott, C., & Chard, D.T. (2012). Improved detection of cortical MS lesions with phase-sensitive inversion recovery MRI. Journal of Neurology, Neurosurgery, and Psychiatry, 83(9), 877–882. doi: 10.1136/jnnp-2012-303023 CrossRef Google Scholar PubMed
- Simons, D.J., Boot, W.R., Charness, N., Gathercole, S.E., Chabris, C.F., Hambrick, D.Z., &Stine-Morrow, E.A. (2016). Do “brain-training” programs work? Psychological Science in the Public Interest, 17(3), 103–186. doi: 10.1177/1529100616661983 CrossRef Google Scholar PubMed
- Sivaraman, I., & Moodley, M. (2016). Multiple sclerosis in the very young: A case report and review of the literature. Neurodegenerative Disease Management, 6(1), 31–36. doi: 10.2217/nmt.15.70 CrossRef Google Scholar PubMed
- Smith, A. (1982). Symbol Digit Modalities Test: Manual. Los Angeles: Western Psychological Services. Google Scholar
- Steenwijk, M.D., Geurts, J.J., Daams, M., Tijms, B.M., Wink, A.M., Balk, L.J., & Pouwels, P.J. (2016). Cortical atrophy patterns in multiple sclerosis are non-random and clinically relevant. Brain, 139(Pt 1), 115–126. doi: 10.1093/brain/awv337 CrossRef Google Scholar PubMed
- Stuifbergen, A.K., Becker, H., Perez, F., Morison, J., Kullberg, V., & Todd, A. (2012). A randomized controlled trial of a cognitive rehabilitation intervention for persons with multiple sclerosis. Clinical Rehabilitation, 26(10), 882–893. doi: 10.1177/0269215511434997 CrossRef Google Scholar PubMed
- Sumowski, J.F., Chiaravalloti, N., Wylie, G., & Deluca, J. (2009). Cognitive reserve moderates the negative effect of brain atrophy on cognitive efficiency in multiple sclerosis. Journal of the International Neuropsychological Society, 15(4), 606–612. doi: 10.1017/S1355617709090912 CrossRef Google Scholar PubMed
- Till, C., Racine, N., Araujo, D., Narayanan, S., Collins, D.L., Aubert-Broche, B., & Banwell, B. (2013). Changes in cognitive performance over a 1-year period in children and adolescents with multiple sclerosis. Neuropsychology, 27(2), 210–219. doi: 10.1037/a0031665 CrossRef Google Scholar
- Tillema, J.M., Hulst, H.E., Rocca, M.A., Vrenken, H., Steenwijk, M.D., & Damjanovic, D., . . . MAGNIMS Study Group. (2016). Regional cortical thinning in multiple sclerosis and its relation with cognitive impairment: A multicenter study. Multiple Sclerosis, 22(7), 901–909. doi: 10.1177/1352458515607650 CrossRef Google Scholar PubMed
- van Horssen, J., Brink, B.P., de Vries, H.E., van der Valk, P., & Bo, L. (2007). The blood-brain barrier in cortical multiple sclerosis lesions. Journal of Neuropathology and Experimental Neurology, 66(4), 321–328. doi: 10.1097/nen.0b013e318040b2de CrossRef Google Scholar PubMed
- Vercellino, M., Masera, S., Lorenzatti, M., Condello, C., Merola, A., Mattioda, A., & Cavalla, P. (2009). Demyelination, inflammation, and neurodegeneration in multiple sclerosis deep gray matter. Journal of Neuropathology and Experimental Neurology, 68(5), 489–502. doi: 10.1097/NEN.0b013e3181a19a5a CrossRef Google Scholar PubMed
- Vercellino, M., Plano, F., Votta, B., Mutani, R., Giordana, M.T., & Cavalla, P. (2005). Grey matter pathology in multiple sclerosis. Journal of Neuropathology and Experimental Neurology, 64(12), 1101–1107. CrossRef Google Scholar PubMed
- Wegner, C., Esiri, M.M., Chance, S.A., Palace, J., & Matthews, P.M. (2006). Neocortical neuronal, synaptic, and glial loss in multiple sclerosis. Neurology, 67(6), 960–967. doi: 10.1212/01.wnl.0000237551.26858.39 CrossRef Google Scholar PubMed
- Zivadinov, R., Havrdova, E., Bergsland, N., Tyblova, M., Hagemeier, J., Seidl, Z., & Horakova, D. (2013). Thalamic atrophy is associated with development of clinically definite multiple sclerosis. Radiology, 268(3), 831–841. doi: 10.1148/radiol.13122424 CrossRef Google Scholar PubMed