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Motor and non-motor basal ganglia (BG) circuits can help healthy subjects cope with task-induced central fatigue and re-establish motor performance after deterioration. This work aimed to assess whether patients with multiple sclerosis (MS) were able to recover motor performance after deterioration due to a demanding task and whether BG activity played a role in performance recovery in this population. Fourteen patients with MS performed a finger-tapping sequence with their right hand during three fMRI sessions: at baseline, after a demanding finger motor task (5-min sequence repetition) and after a short rest period. We observed deterioration of spatial and temporal accuracy with task repetition, as expected; after rest, temporal but not spatial accuracy recovered. Further, higher subjective fatigue was associated with increased motor performance deterioration and reduced temporal accuracy recovery. The amplitude of the BOLD signal change in the left caudate, putamen, globus pallidus, thalamus and amygdala was high at baseline and significantly reduced after the demanding task. Following rest, activity achieved values similar to the baseline in all these regions except for the amygdala. These findings suggest that patients were in a fatigue-like state since task beginning, as they showed enhanced BOLD signal change in the subcortical structures known to be recruited in healthy subjects only when coping with fatigue to recover motor performance. Abnormalities in motor and non-motor BG functions can contribute to fatigue in MS., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Objective: To evaluate the neural basis of subjective fatigue in subjects with multiple sclerosis (MS) using a connectionist framework., Methods: Seventy seven subjects with relapsing-remitting MS were recruited in the study and underwent subjective fatigue evaluations and a diffusion MRI scan. Firstly, local white matter Fractional Anisotropy values were correlated with subjective fatigue scores using a voxel-wise approach. The long-range loss of connectivity due to structural damage in the white matter voxels thus associated with subjective fatigue was then assessed using the Network Modification (NeMo) package., Results: A voxel-wise regression analysis with fatigue scores revealed a significant association between structural damage and fatigue levels in two discrete white matter clusters, both included in the left cingulate bundle. The connectivity analysis revealed that damage in these clusters was associated with loss of structural connectivity in the anterior and medial cingulate cortices, dorsolateral prefrontal areas and in the left caudate., Discussion: Our data point to the cingulum bundle and its projections as the key network involved in subjective fatigue perception in MS. More generally, these results suggest the potential of the connectionist framework to generate coherent models of the neural basis of complex symptomatology in MS., (© The Author(s), 2014.)

Subjective fatigue is a typical symptom in Multiple Sclerosis (MS) even in the earliest stages of the disease. The relationship between persistent fatigue and motor task performance is still unclear. Aim of this study was to better investigate this relationship at both the motor behavioral and neuroanatomical levels. Towards this goal, we combined a quantitative evaluation of an undemanding finger motor task with concurrent brain functional magnetic resonance imaging (fMRI) in a group of MS patients with minimal disability but reporting persistent subjective fatigue. We found an unexpected significant positive correlation between persistent subjective fatigue and task-related temporal accuracy, revealing a "fatigue-motor performance paradox". fMRI analysis indicated that this association is potentially mediated by cerebellar and orbitofrontal cortex activity, suggesting a role of these regions in developing subjective fatigue. Our data point to a possible adaptive role for fatigue as the subjective correlate of increased resource demand for motor activities.

Fatigue, an overwhelming lack of physical or mental energy, is a common complaint in patients affected by multiple sclerosis (MS). Although different mechanisms have been proposed to explain MS-related fatigue, injury of distinct anatomical networks seems to be relevant in fatigue etiology. Particularly, theories point to fronto-striatal network pathological changes as a possible neural basis of fatigue. To investigate the role of fronto-striatal white matter structural alterations in fatigue perception we prospectively recruited 40 relapsing remitting patients with MS and 15 healthy controls. In patients with MS, fatigue was assessed using a validated measure, the Modified Fatigue Impact Scale (MFIS; Kos et al., 2005). Brain MRI scans were acquired for each subject enrolled with diffusion tensor imaging. Diffusion tensor data were correlated with MFIS scores using voxel-wise analysis of fractional anisotropy maps and fiber tractography algorithms. A significant cluster of voxels correlating with fatigue scores located in the deep left frontal white matter was identified. Fiber tractography revealed the cluster to be included in a complex fronto-frontal, fronto-striatal, fronto-occipital, and fronto-limbic network. Structural properties of the traced white matter fiber bundles correlated with fatigue perception and patients with clinically relevant fatigue were found to present reduced white matter integrity in the aforementioned tracts compared to those with lower levels of fatigue. Our observations show a significant involvement of different frontal networks in the pathophysiology of fatigue, thus accounting for the multifaceted nature of this disabling symptom.

The article presents a study which aims to explore the neural basis of subjective fatigue in subjects with multiple sclerosis (MS) using a connectionist framework. It notes the correlation of local white matter Fractional Anisotropy values with subjective fatigue scores using a voxel-wise approach. The findings suggest the potential of the connectionist framework to create coherent models of the neural basis of MS complex symptomatology.