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

Riccardo Manca, Micaela Mitolo, Maria Rosaria Stabile, Francesca Bevilacqua, Basil Sharrack, Annalena Venneri

Research output: Contribution to journalArticle

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.

Original languageEnglish
Pages (from-to)523-532
Number of pages10
JournalPostgraduate Medicine
Volume131
Issue number7
DOIs
Publication statusPublished - Oct 3 2019

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Aptitude
Multiple Sclerosis
Brain
Chronic Progressive Multiple Sclerosis
Phenotype
Relapsing-Remitting Multiple Sclerosis
Automatic Data Processing
Communication

Keywords

  • cognition
  • default mode
  • disconnection
  • functional connectivity
  • MS phenotypes
  • salience

ASJC Scopus subject areas

  • Medicine(all)

Cite this

Multiple brain networks support processing speed abilities of patients with multiple sclerosis. / Manca, Riccardo; Mitolo, Micaela; Stabile, Maria Rosaria; Bevilacqua, Francesca; Sharrack, Basil; Venneri, Annalena.

In: Postgraduate Medicine, Vol. 131, No. 7, 03.10.2019, p. 523-532.

Research output: Contribution to journalArticle

Manca, Riccardo ; Mitolo, Micaela ; Stabile, Maria Rosaria ; Bevilacqua, Francesca ; Sharrack, Basil ; Venneri, Annalena. / Multiple brain networks support processing speed abilities of patients with multiple sclerosis. In: Postgraduate Medicine. 2019 ; Vol. 131, No. 7. pp. 523-532.
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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.",
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