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Clinical Focus: Neurological & Psychiatric Disorders - Original Research

Multiple brain networks support processing speed abilities of patients with multiple sclerosis

, , , , &
Pages 523-532 | Received 14 Jun 2019, Accepted 01 Sep 2019, Published online: 16 Sep 2019
 

ABSTRACT

Objectives: Many people affected by multiple sclerosis (MS) experience cognitive impairment, especially decreases in information processing speed (PS). Neural disconnection is thought to represent the neural marker of this symptom, although the role played by alterations of specific functional brain networks still remains unclear. The aim is to investigate and compare patterns of association between PS-demanding cognitive performance and functional connectivity across two MS phenotypes.

Methods: Forty patients with relapsing-remitting MS (RRMS) and 25 with secondary progressive MS (SPMS) had neuropsychological and MRI assessments. Multiple regression models were used to investigate the relationship between performance on tests of visuomotor and verbal PS, and on the verbal fluency tests, and functional connectivity of four cognitive networks, i.e. left and right frontoparietal, salience and default-mode, and two control networks, i.e. visual and sensorimotor.

Results: Patients with SPMS were older and had longer disease history than patients with RRMS and presented with worse overall clinical conditions: higher disease severity, total lesion volume, and cognitive impairment rates. However, in both patient samples, cognitive performance across tests was negatively correlated with functional connectivity of the salience and default-mode networks, and positively with connectivity of the left frontoparietal network. Only the visuomotor PS scores of the RRMS group were also associated with connectivity of the sensorimotor network.

Conclusions: PS-demanding cognitive performance in patients with MS appears mainly associated with strength of functional connectivity of frontal networks involved in the evaluation and manipulation of information, as well as the default mode network. These results are in line with the hypothesis that multiple neural networks are needed to support normal cognitive performance across MS phenotypes. However, different PS measures showed partially different patterns of association with functional connectivity. Therefore, further investigations are needed to clarify the contribution of inter-network communication to specific cognitive deficits due to MS.

Acknowledgments

The authors thank the team in the MRI unit at IRCCS Fondazione Ospedale San Camillo, Venice, Italy, and all the patients who took part in this study. This is a summary of independent research carried out at the NIHR Sheffield Biomedical Research Center (Translational Neuroscience). The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health.

Declaration of interest

The authors have no disclosures regarding financial benefits related to this study.

Data availability

The authors have no permission from participants to share their research data with others not members of the research team and their collaborators.

Reviewer disclosures

Peer reviewers on this manuscript have received an honorarium from Postgraduate Medicine for their review work but have no other relevant financial relationships to disclose.

Additional information

Funding

This study was partially funded by core funding (Ricerca corrente 2012, Linea di Ricerca 2) by the Ministry of Health to the IRCCS Fondazione Ospedale San Camillo, Venice, Italy.

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