Brain networks in multiple sclerosis and glioma: the road towards individualized care

This thesis describes how the brain responds to damage in two neurological diseases. By studying both MS and glioma, it was found that although both diseases show specific characteristics, patterns of altered brain activity, connectivity and networks were partially overlapping, which increased our knowledge on the overall reaction of the brain to neurological damage and its relation to cognitive (dys)functioning. A wide range of methods were used to show alterations in brain activity, connectivity and networks in patients with MS and glioma that are clearly relevant for cognition. An important take home message that can be deducted from this thesis is that structural and functional connectivity do not quantify the same conceptual construct, while there is clinically relevant information in their (altered) interrelations. In MS, structural and functional damage should be considered as separately timed processes, where altered coupling between the two is related to cognitive impairment. In glioma, the tumor causes structural and functional alterations that can be seen throughout the brain, not only in the location of the tumor itself. More specifically, across disorders, it seems that activity seems to be affected mainly locally which may coincide with hyperconnectivity of specific regions, whereas functional network topology patterns seem to predominantly show more global differences when compared to healthy controls. Additionally, intrinsic brain network characteristics, i.e. brain network characteristics of healthy controls, may indicate disease severity which contributes to our understanding of the relationship between normal brain functioning and neurological diseases. Longitudinally, global functional network measures can provide additional predictive value for cognitive decline. Unfortunately, such longitudinal data remains rare, therefore computational modeling can be deployed when sufficiently optimized. By doing so, crucial information on which measures could be used to predict future cognitive decline can be gained and with that take some of the uncertainty away for patients that direly need some security with regard to their individual disease process

Brain networks in multiple sclerosis and glioma: the road towards individualized care

This thesis describes how the brain responds to damage in two neurological diseases. By studying both MS and glioma, it was found that although both diseases show specific characteristics, patterns of altered brain activity, connectivity and networks were partially overlapping, which increased our knowledge on the overall reaction of the brain to neurological damage and its relation to cognitive (dys)functioning. A wide range of methods were used to show alterations in brain activity, connectivity and networks in patients with MS and glioma that are clearly relevant for cognition. An important take home message that can be deducted from this thesis is that structural and functional connectivity do not quantify the same conceptual construct, while there is clinically relevant information in their (altered) interrelations. In MS, structural and functional damage should be considered as separately timed processes, where altered coupling between the two is related to cognitive impairment. In glioma, the tumor causes structural and functional alterations that can be seen throughout the brain, not only in the location of the tumor itself. More specifically, across disorders, it seems that activity seems to be affected mainly locally which may coincide with hyperconnectivity of specific regions, whereas functional network topology patterns seem to predominantly show more global differences when compared to healthy controls. Additionally, intrinsic brain network characteristics, i.e. brain network characteristics of healthy controls, may indicate disease severity which contributes to our understanding of the relationship between normal brain functioning and neurological diseases. Longitudinally, global functional network measures can provide additional predictive value for cognitive decline. Unfortunately, such longitudinal data remains rare, therefore computational modeling can be deployed when sufficiently optimized. By doing so, crucial information on which measures could be used to predict future cognitive decline can be gained and with that take some of the uncertainty away for patients that direly need some security with regard to their individual disease process

Understanding global brain network alterations in glioma patients

INTRODUCTION: Glioma patients show increased global brain network clustering relating to poorer cognition and epilepsy. However, it is unclear whether this increase is spatially widespread, localized in the (peri)tumor region only, or decreases with distance from the tumor. MATERIALS AND METHODS: Weighted global and local brain network clustering was determined in 71 glioma patients and 53 controls using magnetoencephalography. Tumor clustering was determined by averaging local clustering of regions overlapping with the tumor, and vice versa for non-tumor regions. Euclidean distance was determined from the tumor centroid to the centroids of other regions. RESULTS: Patients showed higher global clustering compared to controls. Clustering of tumor and non-tumor regions did not differ and local clustering was not associated with distance from the tumor. Post-hoc analyses revealed that in the patient group, tumors were located more often in regions with higher clustering in controls, but it seemed that tumors of patients with high global clustering were located more often in regions with lower clustering in controls. CONCLUSIONS: Glioma patients show non-local network disturbances. Tumors of patients with high global clustering may have a preferred localization, namely regions with lower clustering in controls, suggesting that tumor localization relates to the extent of network disruption