Prof Jeroen Geurts

Masterclass November 2017

01 Nov 2017

Prof Jeroen Geurts

Cognitive decline in MS: stuck in disease?

Hanneke Hulst, Anand Eijlers, Jeroen Geurts

Cognitive impairment in MS is nowadays recognized as one of the most disabling symptoms of the disease, affecting up to 70% of all patients.1 Deficits vary from patient to patient and can be present in all stages of the disease.2 Problems with information processing speed (‘cognitive slowing’) and memory are most often reported.3,4

In search of the underlying neurobiological mechanisms of cognitive decline in MS, several studies used advanced neuroimaging techniques to demonstrate structural (atrophy, gray matter lesions) and functional (activation, connectivity) changes in specific brain regions (e.g. thalamus, hippocampus, dorsolateral prefrontal cortex) that were strongly associated with cognitive impairment.5-12 Additionally, using these advanced neuroimaging measures cognitively preserved patients could be distinguished from cognitively impaired patients on a group level.13

In 2010, the functional reorganization hypothesis was introduced as an attempt to explain the functional MRI (fMRI) findings during cognitive paradigms in patients with MS.14 Increased activation of task-related brain regions as well as the recruitment of additional brain regions not normally involved in the task at hand were observed in cognitively preserved, but not in cognitively impaired MS patients. These changes were therefore interpreted as compensatory and beneficial, preserving normal cognitive functioning. In cognitively impaired patients this so-called compensatory mechanism was thought to be exhausted, leading to decreased brain activation and overt cognitive deficits. 8-11,13

In the years that followed, new insights were obtained from resting-state (no task) fMRI studies, demonstrating both increases and decreases in functional connectivity between brain regions at rest, which were both related to better cognitive performance.15-17 These findings added an extra level of complexity to the understanding of cognitive impairment in MS and was reason to revise the original hypothesis. The revised hypothesis postulated a decline in network efficiency as a potential underlying substrate of cognitive decline in MS, comprising changes in regional activation or connectivity between brain regions as well as changes in higher order network organization.18

And with the introduction of the revised hypothesis, another problem emerged: ‘how do we measure network efficiency?’ While this is currently still a matter of debate and no gold standard exist for measuring network efficiency, the investigation of brain functioning from a network perspective and especially the evaluation of network dynamics might be a step in the right direction. Different from static connectivity studies, this also takes into account dynamic changes in the way brain regions communicate with each other. An example of such a study was recently presented at the ECTRIMS congress in Paris (24-10-2017, Eijlers et al.) which showed that the position of the default-mode network, a group of brain regions primarily active during rest and involved in introspective processing, within the broader functional network has not only become more central, but also less dynamic in cognitively impaired MS patients during the resting state. This could indicate that the default-mode network is stuck in a highly central state, hampering the normal attenuation of this network during cognitive processing, which might lead to the observed deficits in cognitive functioning.

Understanding cognitive decline in patients with MS is highly complex and involves the interplay between structural brain damage and functional brain changes. A challenge for the near future would be to further increase our understanding of how this interplay evolves and whether rigidity of the network (i.e. being ‘stuck in disease’) is a contributing factor when it comes to cognitive decline in MS.   


  1. Rao SM, Leo GJ, Bernardin L, Unverzagt F (1991a): Cognitive dysfunction in multiple sclerosis. I. Frequency, patterns, and prediction. Neurology 41:685–691.
  2. Amato MP, Ponziani G, Siracusa G, Sorbi S (2001): Cognitive dysfunction in early-onset multiple sclerosis: a reappraisal after 10 years. Arch Neurol. 58:1602-6.
  3. Chiaravalloti ND, DeLuca J (2008): Cognitive impairment in multiple sclerosis. Lancet Neurol. 7:1139–1151.
  4. Benedict RH, Zivadinov R (2006): Predicting neuropsychological abnormalities in multiple sclerosis. J Neurol Sci. 15:67-72.
  5. Houtchens MK, Benedict RH, Killiany R, et al (2007): Thalamic atrophy and cognition in multiple sclerosis. Neurology 69:1213-1223.
  6. Sicotte NL, Kern KC, Giesser BS, et al (2008): Regional hippocampal atrophy in multiple sclerosis. Brain 131:1134-1141.
  7. Benedict RH, Ramasamy D, Munschauer F, Weinstock-Guttman B, Zivadinov R (2009): Memory impairment in multiple sclerosis: correlation with deep grey matter and mesial temporal atrophy. J Neurol Neurosurg Psychiatry 80:201-206. 
  8. Penner IK, Rausch M, Kappos L, Opwis K, Radü EW (2003): Analysis of impairment related functional architecture in MS patients during performance of different attention tasks. J Neurol. 250:461-72.
  9. Mainero C, Caramia F, Pozzilli C, et al (2004): fMRI evidence of brain reorganization during attention and memory tasks in multiple sclerosis. Neuroimage 21:858-867.
  10. Sweet LH, Rao SM, Primeau M, Durgerian S, Cohen RA (2006): Functional magnetic resonance imaging response to increased verbal working memory demands among patients with multiple sclerosis. Hum Brain Mapp. 27:28-36. 
  11. Rocca MA, Ceccarelli A, Rodegher M, et al (2010): Preserved brain adaptive properties in patients with benign multiple sclerosis. Neurology 74:142-149.
  12. Tona F, Petsas N, Sbardella E, et al (2014): Multiple sclerosis: altered thalamic resting-state functional connectivity and its effect on cognitive function. Radiology 271:814- 821.
  13. Hulst HE, Schoonheim MM, Roosendaal SD, Popescu V, Schweren LJ, van der Werf YD, Visser LH, Polman CH, Barkhof F, Geurts JJ (2012): Functional adaptive changes within the hippocampal memory system of patients with multiple sclerosis. Hum Brain Mapp. 33:2268-80.
  14. Schoonheim MM, Geurts JJ and Barkhof F (2010). The limits of functional reorganization in multiple sclerosis. Neurology 74: 1246–1247.
  15. Loitfelder M, Filippi M, Rocca M, Valsasina P, Ropele S, Jehna M, et al (2012): Abnormalities of resting state functional connectivity are related to sustained attention deficits in MS. PLoS One 7:e42862.
  16. Hawellek DJ, Hipp JF, Lewis CM, Corbetta M, Engel AK (2011). Increased functional connectivity indicates the severity of cognitive impairment in multiple sclerosis. Proc Natl Acad Sci U S A 108:19066–71.
    1. Sumowski JF, Wylie GR, Deluca J, Chiaravalloti N (2010). Intellectual enrichment is linked to cerebral efficiency in multiple sclerosis: functional magnetic resonance imaging evidence for cognitive reserve. Brain 133(Pt 2):362–74.
    2. Schoonheim MM, Meijer KA, Geurts JJ(2015): Network collapse and cognitive impairment in multiple sclerosis. Front Neurol. 14;6:82. 

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