Corticomuscular coherence revealed during treadmill walking: further evidence of supraspinal control in human locomotion

Corticomuscular and intermuscular coherence as a function of age and walking balance difficulty

We determined beta-band intermuscular (IMC) and corticomuscular coherence (CMC) as a function of age and walking balance difficulty. Younger (n=14, 23y) and older individuals (n=19, 71y) walked 13 m overground, on a 6-cm-wide ribbon overground, and on a 6-cm-wide (5-cm-high) beam. Walking distance as a proxy for walking balance and speed were computed. CMC was estimated between electroencephalographic signal at Cz electrode and surface electromyographic signals of seven leg muscles, while IMC was calculated in four pairs of leg muscles, during stance and swing gait phases. With increasing difficulty, walking balance decreased in old individuals and speed decreased gradually independent of age. Beam walking increased IMC, while age increased IMC in proximal muscle pairs, and decreased IMC in distal muscle pairs. Age and difficulty increased CMC independent of gait phases. Concluding, CMC and IMC increased with walking balance difficulty and age, except for distal muscle pairs, which had lower IMC with age. These findings suggest an age-related increase in corticospinal involvement in the neural control of walking balance. DATA AVAILABILITY: The datasets used in this study are available from the corresponding author upon reasonable request.

Exploring EEG-based motor imagery decoding: a dual approach using spatial features and spectro-spatial Deep Learning model IFNet

Introduction

In recent years, the decoding of motor imagery (MI) from electroencephalography (EEG) signals has become a focus of research for brain-machine interfaces (BMIs) and neurorehabilitation. However, EEG signals present challenges due to their non-stationarity and the substantial presence of noise commonly found in recordings, making it difficult to design highly effective decoding algorithms. These algorithms are vital for controlling devices in neurorehabilitation tasks, as they activate the patient's motor cortex and contribute to their recovery.

Methods

This study proposes a novel approach for decoding MI during pedalling tasks using EEG signals. A widespread approach is based on feature extraction using Common Spatial Patterns (CSP) followed by a linear discriminant analysis (LDA) as a classifier. The first approach covered in this work aims to investigate the efficacy of a task-discriminative feature extraction method based on CSP filter and LDA classifier. Additionally, the second alternative hypothesis explores the potential of a spectro-spatial Convolutional Neural Network (CNN) to further enhance the performance of the first approach. The proposed CNN architecture combines a preprocessing pipeline based on filter banks in the frequency domain with a convolutional neural network for spectro-temporal and spectro-spatial feature extraction.

Results and discussion

To evaluate the approaches and their advantages and disadvantages, EEG data has been recorded from several able-bodied users while pedalling in a cycle ergometer in order to train motor imagery decoding models. The results show levels of accuracy up to 80% in some cases. The CNN approach shows greater accuracy despite higher instability.

A pilot study assessing reliability and age-related differences in corticomuscular and intramuscular coherence in ankle dorsiflexors during walking

Corticomuscular (CMC) and intramuscular (intraMC) coherence represent measures of corticospinal interaction. Both CMC and intraMC can be assessed during human locomotion tasks, for example, while walking. Corticospinal control of gait can deteriorate during the aging process and CMC and intraMC may represent an important monitoring means. However, it is unclear whether such assessments represent a reliable tool when performed during walking in an ecologically valid scenario and whether age‐related differences may occur. Wireless surface electroencephalography and electromyography were employed in a pilot study with young and old adults during overground walking in two separate sessions. CMC and intraMC analyses were performed in the gathered beta and lower gamma frequencies (i.e., 13–40 Hz). Significant log‐transformed coherence area was tested for intersessions test–retest reliability by determining intraclass correlation coefficient (ICC), yielding to low reliability in CMC in both younger and older adults. intraMC exclusively showed low reliability in the older adults, whereas intraMC in the younger adults revealed similar values as previously reported: test–retest reliability [ICC (95% CI): 0.44 (−0.23, 0.87); SEM: 0.46; MDC: 1.28; MDC%: 103; Hedge's g (95% CI): 0.54 (−0.13, 1.57)]. Significant differences between the age groups were observed in intraMC by either comparing the two groups with the first test [Hedge's g (95% CI): 1.55 (0.85, 2.15); p‐value: .006] or with the retest data [Hedge's g (95% CI): 2.24 (0.73, 3.70); p‐value: .005]. Notwithstanding the small sample size investigated, intraMC seems a moderately reliable assessment in younger adults. The further development and use of this measure in practical settings to infer corticospinal interaction in human locomotion in clinical practice is warranted and should help to refine the analysis. This necessitates involving larger sample sizes as well as including a wider number of lower limb muscles. Moreover, further research seems warranted by the observed differences in modulation mechanisms of corticospinal control of gait as ascertained by intraMC between the age groups.

Corticospinal Control of Human Locomotion as a New Determinant of Age-Related Sarcopenia: An Exploratory Study

Sarcopenia is a muscle disease listed within the ICD-10 classification. Several operational definitions have been created for sarcopenia screening; however, an international consensus is lacking. The Centers for Disease Control and Prevention have recently recognized that sarcopenia detection requires improved diagnosis and screening measures. Mounting evidence hints towards changes in the corticospinal communication system where corticomuscular coherence (CMC) reflects an effective mechanism of corticospinal interaction. CMC can be assessed during locomotion by means of simultaneously measuring Electroencephalography (EEG) and Electromyography (EMG). The aim of this study was to perform sarcopenia screening in community-dwelling older adults and explore the possibility of using CMC assessed during gait to discriminate between sarcopenic and non-sarcopenic older adults. Receiver Operating Characteristic (ROC) curves showed high sensitivity, precision and accuracy of CMC assessed from EEG Cz sensor and EMG sensors located over Musculus Vastus Medialis [Cz-VM; AUC (95.0%CI): 0.98 (0.92-1.04), sensitivity: 1.00, 1-specificity: 0.89, p < 0.001] and with Musculus Biceps Femoris [Cz-BF; AUC (95.0%CI): 0.86 (0.68-1.03), sensitivity: 1.00, 1-specificity: 0.70, p < 0.001]. These muscles showed significant differences with large magnitude of effect between sarcopenic and non-sarcopenic older adults [Hedge's g (95.0%CI): 2.2 (1.3-3.1), p = 0.005 and Hedge's g (95.0%CI): 1.5 (0.7-2.2), p = 0.010; respectively]. The novelty of this exploratory investigation is the hint toward a novel possible determinant of age-related sarcopenia, derived from corticospinal control of locomotion and shown by the observed large differences in CMC when sarcopenic and non-sarcopenic older adults are compared. This, in turn, might represent in future a potential treatment target to counteract sarcopenia as well as a parameter to monitor the progression of the disease and/or the potential recovery following other treatment interventions.

Dynamics of corticospinal motor control during overground and treadmill walking in humans

Increasing evidence suggests cortical involvement in the control of human gait. However, the nature of corticospinal interactions remains poorly understood. We performed time-frequency analysis of electrophysiological activity acquired during treadmill and overground walking in 22 healthy, young adults. Participants walked at their preferred speed (4.2, SD 0.4 km/h), which was matched across both gait conditions. Event-related power, corticomuscular coherence (CMC), and intertrial coherence (ITC) were assessed for EEG from bilateral sensorimotor cortices and EMG from the bilateral tibialis anterior (TA) muscles. Cortical power, CMC, and ITC at theta, alpha, beta, and gamma frequencies (4-45 Hz) increased during the double support phase of the gait cycle for both overground and treadmill walking. High beta (21-30 Hz) CMC and ITC of EMG was significantly increased during overground compared with treadmill walking, as well as EEG power in theta band (4-7 Hz). The phase spectra revealed positive time lags at alpha, beta, and gamma frequencies, indicating that the EEG response preceded the EMG response. The parallel increases in power, CMC, and ITC during double support suggest evoked responses at spinal and cortical populations rather than a modulation of ongoing corticospinal oscillatory interactions. The evoked responses are not consistent with the idea of synchronization of ongoing corticospinal oscillations but instead suggest coordinated cortical and spinal inputs during the double support phase. Frequency-band dependent differences in power, CMC, and ITC between overground and treadmill walking suggest differing neural control for the two gait modalities, emphasizing the task-dependent nature of neural processes during human walking. NEW & NOTEWORTHY We investigated cortical and spinal activity during overground and treadmill walking in healthy adults. Parallel increases in power, corticomuscular coherence, and intertrial coherence during double support suggest evoked responses at spinal and cortical populations rather than a modulation of ongoing corticospinal oscillatory interactions. These findings identify neurophysiological mechanisms that are important for understanding cortical control of human gait in health and disease.

Assessing Brain-Muscle Connectivity in Human Locomotion through Mobile Brain/Body Imaging: Opportunities, Pitfalls, and Future Directions

Assessment of the cortical role during bipedalism has been a methodological challenge. While surface electroencephalography (EEG) is capable of non-invasively measuring cortical activity during human locomotion, it is associated with movement artifacts obscuring cerebral sources of activity. Recently, statistical methods based on blind source separation revealed potential for resolving this issue, by segregating non-cerebral/artifactual from cerebral sources of activity. This step marked a new opportunity for the investigation of the brains' role while moving and was tagged mobile brain/body imaging (MoBI). This methodology involves simultaneous mobile recording of brain activity with several other body behavioral variables (e.g., muscle activity and kinematics), through wireless recording wearable devices/sensors. Notably, several MoBI studies using EEG-EMG approaches recently showed that the brain is functionally connected to the muscles and active throughout the whole gait cycle and, thus, rejecting the long-lasting idea of a solely spinal-driven bipedalism. However, MoBI and brain/muscle connectivity assessments during human locomotion are still in their fledgling state of investigation. Mobile brain/body imaging approaches hint toward promising opportunities; however, there are some remaining pitfalls that need to be resolved before considering their routine clinical use. This article discusses several of these pitfalls and proposes research to address them. Examples relate to the validity, reliability, and reproducibility of this method in ecologically valid scenarios and in different populations. Furthermore, whether brain/muscle connectivity within the MoBI framework represents a potential biomarker in neuromuscular syndromes where gait disturbances are evident (e.g., age-related sarcopenia) remains to be determined.

The aging brain shows less flexible reallocation of cognitive resources during dual-task walking: A mobile brain/body imaging (MoBI) study

Aging is associated with reduced abilities to selectively allocate attention across multiple domains. This may be particularly problematic during everyday multitasking situations when cognitively demanding tasks are performed while walking. Due to previous limitations in neuroimaging technology, much remains unknown about the cortical mechanisms underlying resource allocation during locomotion. Here, we utilized an EEG-based mobile brain/body imaging (MoBI) technique that integrates high-density event-related potential (ERP) recordings with simultaneously acquired foot-force sensor data to monitor gait patterns and brain activity concurrently. To assess effects of motor load on cognition we evaluated young (N=17; mean age=27.2) and older adults (N=16; mean age=63.9) and compared behavioral and ERP measures associated with performing a Go/No-Go response inhibition task as participants sat stationary or walked on a treadmill. Stride time and variability were also measured during task performance and compared to stride parameters obtained without task performance, thereby assessing effects of cognitive load on gait. Results showed that older, but not young adults' accuracy dropped significantly when performing the inhibitory task while walking. Young adults revealed ERP modulations at relatively early (N2 amplitude reduction) and later (earlier P3 latency) stages within the processing stream as motor load increased while walking. In contrast, older adults' ERP modulations were limited to later processing stages (increased P3 amplitude) of the inhibitory network. The relative delay and attenuation of ERP modulations accompanied by behavioral costs in older participants might indicate an age-associated loss in flexible resource allocation across multiple tasks. Better understanding of the neural underpinnings of these age-related changes may lead to improved strategies to reduce fall risk and enhance mobility in aging.

Age-related changes in inter-joint coordination during walking

Existing methods to assess inter-joint coordination in human walking have several important weaknesses. These methods are unable to define 1) the instantaneous changes in coordination within the stride cycle, 2) coordination between multiple joints, or 3) the coupling strength of joint rotations rather than their phase relationships. The present paper introduces a new method called generalized wavelet coherence analysis (GWCA) that solves these three fundamental limitations of previous methods. GWCA combines wavelet coherence analysis with a matrix correlation method to define instantaneous correlation coefficients as the coupling strength for an arbitrary number of joint rotations. The main purpose of the present study is to develop GWCA to quantify inter-joint coordination and thereby assess age-related differences in the coordination of human gaits. Nine young and 19 healthy older persons walked 5 min on a treadmill at three different gait speeds. Joint rotations of the lower extremities were assessed by a Vicon three-dimensional motion capture system. The main results indicated that the older group had significant weaker correlations (t-tests: P < 0.0001) in the preswing phase compared with the younger group for all gait speeds. The age-related differences in inter-joint coordination were more pronounced than the age-related differences in rotations of the individual joints. The intra-stride changes in inter-joint coordination were in agreement with recent findings of intra-stride modulations in neural activity in the sensorimotor cortex. Thus change in the inter-joint coordination assessed by GWCA might be an early indicator of functional decline.

Towards effective non-invasive brain-computer interfaces dedicated to gait rehabilitation systems

In the last few years, significant progress has been made in the field of walk rehabilitation. Motor cortex signals in bipedal monkeys have been interpreted to predict walk kinematics. Epidural electrical stimulation in rats and in one young paraplegic has been realized to partially restore motor control after spinal cord injury. However, these experimental trials are far from being applicable to all patients suffering from motor impairments. Therefore, it is thought that more simple rehabilitation systems are desirable in the meanwhile. The goal of this review is to describe and summarize the progress made in the development of non-invasive brain-computer interfaces dedicated to motor rehabilitation systems. In the first part, the main principles of human locomotion control are presented. The paper then focuses on the mechanisms of supra-spinal centers active during gait, including results from electroencephalography, functional brain imaging technologies [near-infrared spectroscopy (NIRS), functional magnetic resonance imaging (fMRI), positron-emission tomography (PET), single-photon emission-computed tomography (SPECT)] and invasive studies. The first brain-computer interface (BCI) applications to gait rehabilitation are then presented, with a discussion about the different strategies developed in the field. The challenges to raise for future systems are identified and discussed. Finally, we present some proposals to address these challenges, in order to contribute to the improvement of BCI for gait rehabilitation.