Multiscale Information Transfer in Functional Corticomuscular Coupling Estimation Following Stroke: A Pilot Study

Abstract

Recently, functional corticomuscular coupling (FCMC) between the cortex and the contralateral muscle has been used to evaluate motor function after stroke. As we know, the motor-control system is a closed-loop system that is regulated by complex self-regulating and interactive mechanisms which operate in multiple spatial and temporal scales. Multiscale analysis can represent the inherent complexity. However, previous studies in FCMC for stroke patients mainly focused on the coupling strength in single-time scale, without considering the changes of the inherently directional and multiscale properties in sensorimotor systems. In this paper, a multiscale-causal model, named multiscale transfer entropy, was used to quantify the functional connection between electroencephalogram over the scalp and electromyogram from the flexor digitorum superficialis (FDS) recorded simultaneously during steady-state grip task in eight stroke patients and eight healthy controls. Our results showed that healthy controls exhibited higher coupling when the scale reached up to about 12, and the FCMC in descending direction was stronger at certain scales (1, 7, 12, and 14) than that in ascending direction. Further analysis showed these multi-time scale characteristics mainly focused on the beta1 band at scale 11 and beta2 band at scale 9, 11, 13, and 15. Compared to controls, the multiscale properties of the FCMC for stroke were changed, the strengths in both directions were reduced, and the gaps between the descending and ascending directions were disappeared over all scales. Further analysis in specific bands showed that the reduced FCMC mainly focused on the alpha2 at higher scale, beta1 and beta2 across almost the entire scales. This study about multi-scale confirms that the FCMC between the brain and muscles is capable of complex and directional characteristics, and these characteristics in functional connection for stroke are destroyed by the structural lesion in the brain that might disrupt coordination, feedback, and information transmission in efferent control and afferent feedback. The study demonstrates for the first time the multiscale and directional characteristics of the FCMC for stroke patients, and provides a preliminary observation for application in clinical assessment following stroke.

Identifying bidirectional total and non-linear information flow in functional corticomuscular coupling during a dorsiflexion task: a pilot study

“…Compared to the healthy controls, we did not observe significant directional differences in the strength of information flow both in the beta and gamma bands. This may be due to structural damage to the patient's brain, which affects normal information interaction [ 50 ]. Another possible explanation is that the individual differences among patients caused by factors such as different disease levels, different brain damage locations, and different stroke onset times.…”

Multiscale Wavelet Transfer Entropy with Application to Corticomuscular Coupling Analysis

“…The term multiscale TE analysis has been used before, but with a different meaning. In [22], [23], the authors employ a graining pre-processing operator that performs local averaging of considered signals. They propose averaging over windows of different lengths prior to the computation of TE and refer to the methodology as multiscale TE.…”

“…Information theory provides principled tools to quantify the transmission of information, such as mutual information (MI), directed information (DI), and transfer entropy (TE). Their model-free nature and ability to capture both linear and non-linear relationships has spurred considerable interest in their potential for detecting and quantifying functional neurophysiological coupling [11], [12], [13], [14], [15], [16], [17], [18], [19], [20], [21], [22], [23]. Neurophysiological information transfer takes place within and across distinct functional bands of neural oscillations.…”

Sparse representation of brain signals offers effective computation of cortico-muscular coupling value to predict the task-related and non-task sEMG channels: A joint hdEEG-sEMG study

“…Extensive studies have reported the coupling/synchronization of alpha-band (8-14Hz) during static/isometric contractions, finger movements and the transition between force targets [6][7][8]. On the other hand, beta rhythm (15)(16)(17)(18)(19)(20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30) coupling has been indicated as the main contributor to movement control [9,10]. Maximum beta rhythm coupling is observed during maintaining steady-state force and also controlling the fine motor control tasks [5,11].…”