Altered anterior default mode network dynamics in progressive multiple sclerosis

Abstract

Functional reorganization at the progressive stage of multiple sclerosis has received limited attention, despite the fact that functional changes are known to occur. Characterizing large-scale network dynamics at rest has the potential to provide new insights into the complexity of such functional alterations. In this case-control study, we explored the dynamic properties of large-scale functional networks during rest in 25 healthy controls and 32 patients with progressive multiple sclerosis, using the innovation-driven co-activation patterns. Thirty-five subjects also underwent a one-year follow-up examination. Partial least squares correlation analysis was applied to explore the relationship between functional dynamics and clinical disability. We observed a reduced dynamic engagement of the anterior default mode network and its coupling with the executive-control network in patients with progressive multiple sclerosis compared to controls, at baseline and follow-up. The global and motor disabilities were related to functional dynamics of subcortical, sensory-motor and posterior default mode network, while the cognitive disability was associated to the altered dynamics of anterior default mode, visual and temporal networks. These findings reveal that the anterior default mode functional recruitment and its interaction with other networks play a major role in the functional reorganization occurring during the progressive stage of multiple sclerosis. Also, the dynamic properties of large-scale functional networks are steady over one year and unveil the intricate relationship between brain function and clinical disability.

Hemodynamic Deconvolution Demystified: Sparsity-Driven Regularization at Work

“…for a large number of subjects. Previous findings based on iCAPs have for instance revealed organizational principles of brain function during rest (18) and sleep (102) in healthy controls, next to alterations in 22q11ds ( 103) and multiple sclerosis (104). Next to CAPs-inspired approaches, dynamic functional connectivity has recently been investigated with the use of cofluctuations and edgecentric techniques (105)(106)(107)(108)(109).…”

“…In addition, decoding of the deconvolved spontaneous events allows to decipher the flow of spontaneous thoughts and actions across different cognitive and sensory domains while at rest (18,22,23). Beyond findings on healthy subjects, deconvolution techniques have also proven their utility in clinical conditions to characterize functional alterations of patients with a progressive stage of multiple sclerosis at rest (24), to find functional signatures of prodromal psychotic symptoms and anxiety at rest on patients suffering from schizophrenia 25), to detect the foci of interictal events in epilepsy patients without an EEG recording (17,26), or to study functional dissociations observed during nonrapid eye movement sleep that are associated with reduced consolidation of information and impaired consciousness (27).…”

Hemodynamic Deconvolution Demystified: Sparsity-Driven Regularization at Work

“…In addition, decoding of the deconvolved spontaneous events allows to decipher the flow of spontaneous thoughts and actions across different cognitive and sensory domains while at rest (Karahanoglu and Ville 2015;Gonzalez-Castillo et al 2019;Tan et al 2017). Beyond findings on healthy subjects, deconvolution techniques have also proven its utility in clinical conditions to characterize functional alterations of patients with a progressive stage of multiple sclerosis at rest (Bommarito et al 2020), to find functional signatures of prodromal psychotic symptoms and anxiety at rest on patients suffering from schizophrenia (Zöller et al 2019), to detect the foci of interictal events in epilepsy patients without an EEG recording (Lopes et al 2012;, or to study functional dissociations observed during non-rapid eye movement sleep that are associated with reduced consolidation of information and impaired consciousness (Tarun et al 2020).…”