Motor preparation impairment in multiple sclerosis: Evidence from the Bereitschaftspotential in simple and complex motor tasks

Feasibility of source-level motor imagery classification for people with multiple sclerosis

Objective.There is limited work investigating brain-computer interface (BCI) technology in people with multiple sclerosis (pwMS), a neurodegenerative disorder of the central nervous system. Present work is limited to recordings at the scalp, which may be significantly altered by changes within the cortex due to volume conduction. The recordings obtained from the sensors, therefore, combine disease-related alterations and task-relevant neural signals, as well as signals from other regions of the brain that are not relevant. The current study aims to unmix signals affected by multiple sclerosis (MS) progression and BCI task-relevant signals using estimated source activity to improve classification accuracy.Approach.Data was collected from eight participants with a range of MS severity and ten neurotypical participants. This dataset was used to report the classification accuracy of imagined movements of the hands and feet at the sensor-level and the source-level in the current study.K-means clustering of equivalent current dipoles was conducted to unmix temporally independent signals. The location of these dipoles was compared between MS and control groups and used for classification of imagined movement. Linear discriminant analysis classification was performed at each time-frequency point to highlight differences in frequency band delay.Main Results.Source-level signal acquisition significantly improved decoding accuracy of imagined movement vs rest and movement vs movement classification in pwMS and controls. There was no significant difference found in alpha (7-13 Hz) and beta (13-30 Hz) band classification delay between the neurotypical control and MS group, including imagery of limbs with weakness or paralysis.Significance.This study is the first to demonstrate the advantages of source-level analysis for BCI applications in pwMS. The results highlight the potential for enhanced clinical outcomes and emphasize the need for longitudinal studies to assess the impact of MS progression on BCI performance, which is crucial for effective clinical translation of BCI technology.

Exploring Differences in the Lateralized Readiness Potential in Persons With Multiple Sclerosis Compared to Healthy Controls

Multiple sclerosis (MS) is a neurodegenerative disease often leading to cognitive and motor impairment. Little research has examined motor preparation and initiation outcomes in the brain among persons with MS. The lateralized readiness potential is an ERP component that indexes pre-motor activity evaluating the stimulus (LRP-S) and motor activation for the response (LRP-R). We examined the LRP-S and LRP-R in MS and healthy controls (HC) to understand impairments in neural activity associated with response activation and selection. Persons with MS (n = 53) and HC (n = 53) completed a flanker task with concurrent EEG for LRP extraction. Paired t-tests were conducted to determine differences for accuracy, reaction time (RT), LRP-S, and LRP-R. Within-group Pearson correlations were conducted to investigate the relationship between LRP indices and behavioral performance. Participants with MS had delayed LRP-S latency and reduced LRP-R amplitudes compared to HC for both trial types. In the HC group, LRP-S amplitude and latency were positively related to RT. In the MS group, LRP-S latency was positively related to RT. In both MS and HC, incongruent LRP-R latency was negatively related to RT, suggesting that individuals with a shorter time interval between activation and response had faster reaction times. Persons with MS had delayed response selection, and less neural response activation compared to HC. Impairment in MS is evident for both pre-motor and motor response initiation during a selective attention task. Our study also provided evidence the relationship between action-based components and task performance differ in persons with MS and HC.

The contribution of EEG to assess and treat motor disorders in multiple sclerosis

OBJECTIVE

Electroencephalography (EEG) can highlight significant changes in spontaneous electrical activity of the brain produced by altered brain network connectivity linked to inflammatory demyelinating lesions and neuronal loss occurring in multiple sclerosis (MS). In this review, we describe the main EEG findings reported in the literature to characterize motor network alteration in term of local activity or functional connectivity changes in patients with MS (pwMS).

METHODS

A comprehensive literature search was conducted to include articles with quantitative analyses of resting-state EEG recordings (spectrograms or advanced methods for assessing spatial and temporal dynamics, such as coherence, theory of graphs, recurrent quantification, microstates) or dynamic EEG recordings during a motor task, with or without connectivity analyses.

RESULTS

In this systematic review, we identified 26 original articles using EEG in the evaluation of MS-related motor disorders. Various resting or dynamic EEG parameters could serve as diagnostic biomarkers of motor control impairment to differentiate pwMS from healthy subjects or be related to a specific clinical condition (fatigue) or neuroradiological aspects (lesion load).

CONCLUSIONS

We highlight some key EEG patterns in pwMS at rest and during movement, both suggesting an alteration or disruption of brain connectivity, more specifically involving sensorimotor networks.

SIGNIFICANCE

Some of these EEG biomarkers of motor disturbance could be used to design future therapeutic strategies in MS based on neuromodulation approaches, or to predict the effects of motor training and rehabilitation in pwMS.

Event-related desynchronization and synchronization in multiple sclerosis

BACKGROUND

Motor preparation and execution can be impaired in patients with multiple sclerosis (pwMS). These neural processes can be assessed using electroencephalography (EEG). During a self-paced movement, EEG signal amplitude decreases before movement (event-related desynchronization, ERD) and increases after movement (event-related synchronization, ERS).

OBJECTIVE

To reappraise ERD/ERS changes in pwMS compared to healthy controls (HC).

METHODS

This single-center study included 13 pwMS and 10 sex/age-matched HC. 60-channel EEG was recorded during two self-paced movements of the right hand: a simple index finger extension task and a more complex finger tapping task. Clinical variables included MS type, sex, age, disease duration, disability, grip strength, fatigue and attentional performance. EEG variables included ERD and ERS onset latency, duration, and amplitude determined using two methods of signal analyses (based on visual or automated determination) in the alpha and beta frequency bands in five cortical regions: right and left frontocentral and centroparietal regions and a midline region. Neuroimaging variables included the volumes of four deep brain structures (thalamus, putamen, pallidum and caudate nucleus) and the relative lesion load.

RESULTS

ERD/ERS changes in pwMS compared to HC were observed only in the beta band. In pwMS, beta-ERD had a delayed onset in the midline and right parietocentral regions and a shortened duration or increased amplitude in the parietocentral region; beta-ERS had a shorter duration, delayed onset, or reduced amplitude in the left parieto/frontocentral region. In addition, pwMS with a more delayed beta-ERD in the midline region had less impaired executive functions but increased caudate nuclei volume, while pwMS with a more delayed beta-ERS in the parietocentral region contralateral to the movement had less fatigue but increased thalami volume.

CONCLUSION

This study confirms an alteration of movement preparation and execution in pwMS, mainly characterized by a delayed cortical activation (ERD) and a delayed and reduced post-movement inhibition (ERS) in the beta band. Compensatory mechanisms could be involved in these changes, associating more preserved clinical performance and overactivation of deep brain structures.