Objective
Neurofeedback training may improve cognitive function in patients with neurological disorders. However, the underlying cerebral mechanisms of such improvements are poorly understood. Therefore, we aimed to investigate MRI correlates of cognitive improvement after EEG-based neurofeedback training in patients with MS (pwMS).
Methods
Fourteen pwMS underwent ten neurofeedback training sessions within 3–4 weeks at home using a tele-rehabilitation system. Half of the pwMS (N = 7, responders) learned to self-regulate sensorimotor rhythm (SMR, 12–15 Hz) by visual feedback and improved cognitively after training, whereas the remainder (non-responders, n = 7) did not. Diffusion-tensor imaging and resting-state fMRI of the brain was performed before and after training. We analyzed fractional anisotropy (FA) and functional connectivity (FC) of the default-mode, sensorimotor (SMN) and salience network (SAL).
Results
At baseline, responders and non-responders were comparable regarding sex, age, education, disease duration, physical and cognitive impairment, and MRI parameters. After training, compared to non-responders, responders showed increased FA and FC within the SAL and SMN. Cognitive improvement correlated with increased FC in SAL and a correlation trend with increased FA was observed.
Conclusions
This exploratory study suggests that successful neurofeedback training may not only lead to cognitive improvement, but also to increases in brain microstructure and functional connectivity.
Background: Cognitive impairment frequently occurs in patients with MS (pwMS). Magnetic resonance imaging (MRI) markers could help to identify patients at risk for decline. Objective: To characterize the long-term course and morphological MRI correlates of cognitive function in pwMS. Methods: We invited 116 pwMS who had undergone clinical, cognitive, and MRI evaluations between 2006 and 2012 (baseline, BL) to attend follow-up (FU) testing between 2016 and 2018. Disability (expanded disability status scale (EDSS)), cognition (brief repeatable battery of neuropsychological test (BRB-N)), global and regional T2-lesion load (T2-LL), brain volumes, and cortical thickness were assessed. Results: Sixty-three pwMS were willing to attend the FU (54%; median EDSS = 2, interquartile range (IQR) = 2) and did not differ from non-participating pwMS regarding BL characteristics. At BL, half of the participants showed cognitive deficits in at least one domain. Across the entire group, we observed no relevant changes in physical disability and cognition over 10 years. BL thalamic volume best predicted cognitive function at FU, in addition to age and BL cognition, explaining 67% of variance. Cognitive decliners (23.8%) were older, had longer disease duration, and a tendency for lower thalamic volume at BL. Conclusion: Thalamic volume predicted FU cognitive function and distinguished declining from stable pwMS, underlining the potential of MRI to define risk groups.
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