Contribution of the cerebellum to cognitive performance in children and adolescents with multiple sclerosis

Multiple Sclerosis

Volumn 22, Issue 5, 2016, Pages 599-607

  Weier, Katrin ^a   Till, Christine ^b   Fonov, Vladimir ^a   Yeh, E Ann ^c,e   Arnold, Douglas L ^a   Banwell, Brenda ^d   Collins, D Louis ^a  

^a MCGILL UNIVERSITY   (Canada)

^b YORK UNIVERSITY   (Canada)

^c HOSPITAL FOR SICK CHILDREN RESEARCH INSTITUTE   (Canada)

^d UNIVERSITY OF PENNSYLVANIA   (United States)

^e UNIVERSITY OF TORONTO   (Canada)

Author keywords

Cerebellum; cognition; multiple sclerosis; pediatric; volumetric MRI

Indexed keywords

ADOLESCENT; ARTICLE; ATTENTION; BRAIN SIZE; CEREBELLUM; CHILD; CLINICAL ARTICLE; COGNITION; CONTROLLED STUDY; DISEASE DURATION; EXPANDED DISABILITY STATUS SCALE; FEMALE; HUMAN; INTELLIGENCE; JUVENILE; LANGUAGE ABILITY; MALE; MOTOR PERFORMANCE; MULTIPLE SCLEROSIS; NEUROPSYCHOLOGICAL TEST; NUCLEAR MAGNETIC RESONANCE IMAGING; ONSET AGE; VISUOMOTOR COORDINATION; ADOLESCENT DISEASE; BEERY-BUKTENICA DEVELOPMENTAL TEST OF VISUAL-MOTOR INTEGRATION; INTELLIGENCE QUOTIENT; LANGUAGE; PEGBOARD TEST; SCORING SYSTEM; SENSORIMOTOR INTEGRATION; SPEECH TEST; SYMBOL DIGIT MODALITIES TEST; TRAIL MAKING TEST; WECHSLER INTELLIGENCE SCALE; COGNITIVE DEFECT; DIAGNOSTIC IMAGING; PATHOPHYSIOLOGY; PHYSIOLOGY; PROCEDURES;

ADOLESCENT; CEREBELLUM; COGNITION DISORDERS; FEMALE; HUMANS; INTELLIGENCE; MAGNETIC RESONANCE IMAGING; MALE; MULTIPLE SCLEROSIS; NEUROPSYCHOLOGICAL TESTS;

EID: 84961696482     PISSN: 13524585     EISSN: 14770970     Source Type: Journal    
DOI: 10.1177/1352458515595132     Document Type: Article

References (35)

1. Till C, Ghassemi R, Aubert-Broche B, et al. MRI correlates of cognitive impairment in childhood-onset multiple sclerosis. Neuropsychology 2011; 25: 319-332.
2. Amato MP, Goretti B, Ghezzi A, et al. Cognitive and psychosocial features of childhood and juvenile MS. Neurology 2008; 70: 1891-1897.
3. Till C, Racine N, Araujo D, et al. Changes in cognitive performance over a 1-year period in children and adolescents with multiple sclerosis. Neuropsychology 2013; 27: 210-219.
4. Amato MP, Goretti B, Ghezzi A, et al. Neuropsychological features in childhood and juvenile multiple sclerosis: five-year follow-up. Neurology 2014; 83: 1432-1438.
5. Hosseini B, Flora DB, Banwell BL, et al. Age of onset as a moderator of cognitive decline in pediatric-onset multiple sclerosis. JINS 2014; 20: 796-804.
6. Koziol LF, Budding D, Andreasen N, et al. Consensus paper: the cerebellum's role in movement and cognition. Cerebellum 2014; 13: 151-177.
7. Schmahmann JD, Sherman JC,. The cerebellar cognitive affective syndrome. Brain 1998; 121: 561-579.
8. Weier K, Penner IK, Magon S, et al. Cerebellar abnormalities contribute to disability including cognitive impairment in multiple sclerosis. PloS one 2014; 9: e86916.
9. Anderson VM, Wheeler-Kingshott CA, Abdel-Aziz K, et al. A comprehensive assessment of cerebellar damage in multiple sclerosis using diffusion tractography and volumetric analysis. Mult Scler 2011; 17: 1079-1087.
10. Ghassemi R, Narayanan S, Banwell B, et al. Quantitative determination of regional lesion volume and distribution in children and adults with relapsing-remitting multiple sclerosis. PloS one 2014; 9: e85741.
11. Polman CH, Reingold SC, Edan G, et al. Diagnostic criteria for multiple sclerosis: 2005 revisions to the "McDonald Criteria". Ann Neurol 2005; 58: 840-846.
12. Kurtzke JF,. Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology 1983; 33: 1444-1452.
13. Wechsler D,. Wechsler abbreviated scale of intelligence. New York, NY: The Psychological Corporation, Harcourt Brace & Company, 1999.
14. Reitan RM,. A manual for the administrating and scoring of the Trail Making Test. Indianapolis, IN: Indiana University Press, 1959.
15. Smith A,. Symbol digits modalities test. Los Angeles, CA: Western Psychological Services, 1982.
16. Beery K,. The Beery-Buktenica developmental test of visual-motor integration. Parsippany, NJ: Modern Curriculum Press, 1997.
17. Stoodley CJ, Schmahmann JD,. Functional topography in the human cerebellum: a meta-analysis of neuroimaging studies. Neuroimage 2009; 44: 489-501.
18. Weier K, Fonov V, Lavoie K, et al. Rapid automatic segmentation of the human cerebellum and its lobules (RASCAL)-implementation and application of the patch-based label-fusion technique with a template library to segment the human cerebellum. Hum Brain Mapp 2014; 35: 5026-5039.
19. Ghassemi R, Antel SB, Narayanan S, et al. Lesion distribution in children with clinically isolated syndromes. Ann Neurol 2008; 63: 401-405.
20. Eskildsen SF, Coupe P, Fonov V, et al. BEaST: brain extraction based on nonlocal segmentation technique. Neuroimage 2012; 59: 2362-2373.
21. Zijdenbos A, Evans A, Riahi F, et al. Automatic quantification of multiple sclerosis lesion volume using stereotaxic space. In: Höhne K, Kikinis R, (eds) Visualization in biomedical computing. Berlin, Heidelberg: Springer, 1996, pp. 439-448.
22. Evans AC, and Brain Development Cooperative G. The NIH MRI study of normal brain development. Neuroimage 2006; 30: 184-202.
23. Timmann D, Drepper J, Frings M, et al. The human cerebellum contributes to motor, emotional and cognitive associative learning. A review. Cortex 2010; 46: 845-857.
24. Wang SS, Kloth AD, Badura A,. The cerebellum, sensitive periods, and autism. Neuron 2014; 83: 518-532.
25. Allin M, Matsumoto H, Santhouse AM, et al. Cognitive and motor function and the size of the cerebellum in adolescents born very pre-term. Brain 2001; 124: 60-66.
26. Steinlin M, Imfeld S, Zulauf P, et al. Neuropsychological long-term sequelae after posterior fossa tumour resection during childhood. Brain 2003; 126: 1998-2008.
27. Cerasa A, Passamonti L, Valentino P, et al. Cerebellar-parietal dysfunctions in multiple sclerosis patients with cerebellar signs. Exp Neurol 2012; 237: 418-426.
28. Riva D, Giorgi C,. The cerebellum contributes to higher functions during development: evidence from a series of children surgically treated for posterior fossa tumours. Brain 2000; 123: 1051-1061.
29. Stoodley CJ, Schmahmann JD,. Evidence for topographic organization in the cerebellum of motor control versus cognitive and affective processing. Cortex 2010; 46: 831-844.
30. Ghezzi A, Goretti B, Portaccio E, et al. Cognitive impairment in pediatric multiple sclerosis. Neurol Sci 2010; 31: S215-S218.
31. Forn C, Belenguer A, Belloch V, et al. Anatomical and functional differences between the Paced Auditory Serial Addition Test and the Symbol Digit Modalities Test. J Clin Exp Neuropsychol 2011; 33: 42-50.
32. Batista S, Zivadinov R, Hoogs M, et al. Basal ganglia, thalamus and neocortical atrophy predicting slowed cognitive processing in multiple sclerosis. J Neurol 2012; 259: 139-146.
33. Haier RJ, Jung RE, Yeo RA, et al. Structural brain variation and general intelligence. Neuroimage 2004; 23: 425-433.
34. Henry RG, Shieh M, Okuda DT, et al. Regional grey matter atrophy in clinically isolated syndromes at presentation. J Neurol Neurosurg Psychiatry 2008; 79: 1236-1244.
35. Rothman KJ,. No adjustments are needed for multiple comparisons. Epidemiology 1990; 1: 43-46.