Machine Learning/Network Science Poster Presentation

P0008 - Divergent patterns of ventral attention network centrality relate to cognitive conversion in MS (ID 473)

  • M. Huiskamp
  • M. Huiskamp
  • A. Eijlers
  • T. Broeders
  • I. Dekker
  • B. Uitdehaag
  • F. Barkhof
  • A. Wink
  • J. Geurts
  • H. Hulst
  • M. Schoonheim
Presentation Number
Presentation Topic
Machine Learning/Network Science



Cognitive impairment (CI) is common in multiple sclerosis (MS), but due to a lack of longitudinal data it remains unclear which mechanisms relate to conversion to mild or even severe CI. Previous cross-sectional work has suggested the importance of cognition-related resting-state networks, such as the default-mode and attention networks.


To characterize the functional network changes related to conversion to CI in a large sample of MS patients over a period of 5 years.


A total of 233 MS patients and 59 healthy controls (HC), all part of the Amsterdam MS cohort, underwent extensive neuropsychological testing and resting-state fMRI at baseline and follow-up (mean time-interval 4.9±0.9 years). At baseline, MS patients were categorized as being cognitively impaired (scoring ≤-2 SD on ≥2 domains, N=74), mildly impaired (MCI, being impaired on 1 domain or scoring between -1.5 and -2SD on ≥2 domains, N=33) or preserved (CP, not fulfilling the CI or MCI criteria, N=126). In addition, these groups were categorized according to the group to which they converted at follow-up (e.g. CP to CI). Network function was quantified using eigenvector centrality, a measure of network importance, which was averaged over established resting-state networks at both time-points. Correlations with brain volumes were calculated.


Over time, 26.2% of CP patients deteriorated and developed MCI (66.7%) or CI (33.3%) and 73.8% remained CP. 23.5% of MCI patients, progressed to CI. Centrality analysis showed that patients who were CI at baseline demonstrated a higher cross-sectional DMN centrality compared to controls (P=.05). Longitudinally, patients who remained CP and CP-to-MCI converters showed increasing ventral attention network (VAN) centrality over time time (P=.017 and .008, respectively), , whereas in the MCI and CI converter groups this increase was absent. Patients with less severe deep gray matter atrophy at baseline showed stronger increases in VAN centrality over time.


We showed that conversion from intact cognition to impairment in MS is related to an increase in centrality of the VAN, which is absent when overt impairment has manifested, then shifting towards DMN dysfunction. As the ventral attention network is known to normally relay information to the DMN, our results suggest that developing cognitive impairment is related to a progressive loss of control over the DMN by means of VAN dysfunction.