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Multiple brain networks support processing speed abilities of patients with multiple sclerosis.
Postgrad Med. 2019 Sep; 131(7):523-532.PM

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.

Authors+Show Affiliations

Department of Neuroscience, University of Sheffield , Sheffield , UK.IRCCS Istituto delle Scienze Neurologiche di Bologna, Diagnostica Funzionale Neuroradiologica , Bologna , Italy.IRCCS Fondazione Ospedale San Camillo , Venice , Italy.IRCCS Fondazione Ospedale San Camillo , Venice , Italy.Academic Department of Neuroscience, Sheffield Teaching Hospital, NHS Foundation Trust , Sheffield , UK.Department of Neuroscience, University of Sheffield , Sheffield , UK.

Pub Type(s)

Journal Article

Language

eng

PubMed ID

31478421

Citation

Manca, Riccardo, et al. "Multiple Brain Networks Support Processing Speed Abilities of Patients With Multiple Sclerosis." Postgraduate Medicine, vol. 131, no. 7, 2019, pp. 523-532.
Manca R, Mitolo M, Stabile MR, et al. Multiple brain networks support processing speed abilities of patients with multiple sclerosis. Postgrad Med. 2019;131(7):523-532.
Manca, R., Mitolo, M., Stabile, M. R., Bevilacqua, F., Sharrack, B., & Venneri, A. (2019). Multiple brain networks support processing speed abilities of patients with multiple sclerosis. Postgraduate Medicine, 131(7), 523-532. https://doi.org/10.1080/00325481.2019.1663706
Manca R, et al. Multiple Brain Networks Support Processing Speed Abilities of Patients With Multiple Sclerosis. Postgrad Med. 2019;131(7):523-532. PubMed PMID: 31478421.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Multiple brain networks support processing speed abilities of patients with multiple sclerosis. AU - Manca,Riccardo, AU - Mitolo,Micaela, AU - Stabile,Maria Rosaria, AU - Bevilacqua,Francesca, AU - Sharrack,Basil, AU - Venneri,Annalena, Y1 - 2019/09/16/ PY - 2019/9/4/pubmed PY - 2019/10/24/medline PY - 2019/9/4/entrez KW - MS phenotypes KW - cognition KW - default mode KW - disconnection KW - functional connectivity KW - salience SP - 523 EP - 532 JF - Postgraduate medicine JO - Postgrad Med VL - 131 IS - 7 N2 - 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. SN - 1941-9260 UR - https://www.unboundmedicine.com/medline/citation/31478421/Multiple_brain_networks_support_processing_speed_abilities_of_patients_with_multiple_sclerosis_ L2 - http://www.tandfonline.com/doi/full/10.1080/00325481.2019.1663706 DB - PRIME DP - Unbound Medicine ER -