Distinct β Band Oscillatory Networks Subserving Motor and Cognitive Control during Gait Adaptation

Dynamic modulations of effective brain connectivity associated with postural instability during multi-joint compound movement on compliant surface

Random fluctuations in somatosensory signals affect the ability of effectively coordinating multimodal information pertaining to the postural state during movement. Therefore, this study aimed to investigate the impact of a compliant surface on cortico-cortical causal information flow during multi-joint compound movements. Fifteen healthy adults (7 female / 8 male, 25.9 ± 4.0 years) performed 5 × 20 repetitions of bodyweight squats on firm and compliant surface. Motor behavior was quantified by center of pressure (CoP) displacements, hip movement and the root mean square of the rectus femoris activity. Using source space analysis, renormalized partial directed coherence (rPDC) computed subject-level multivariate effective brain connectivity of sensorimotor nodes. Bootstrap statistics revealed significantly decreased medio-lateral CoP displacement (p < 0.001), significantly increased velocity of medio-lateral hip motion (p < 0.001) as well as significantly lower rectus femoris activity (p < 0.01) in the compliant surface condition. On the cortical level, rPDC showed significantly modulated information flow in theta and beta frequencies for fronto-parietal edges (p < 0.01) only during the concentric phase of the movement. The compliant surface led to increased difficulties controlling hip but not center of pressure motion in the medio-lateral plane. Moreover, a decreased activation of the prime movers accompanied by modulations of effective brain connectivity among fronto-central nodes may point to altered demands on sensorimotor information processing in presence of sensory noise when performing bodyweight squats on compliant surface. Further studies are needed to evaluate a potential benefit for athletic and clinical populations.

Clinical and neurophysiological predictors of the functional outcome in right-hemisphere stroke

OBJECTIVE

The aim of the present study is to examine the relationship between EEG measures and functional recovery in right-hemisphere stroke patients.

METHODS

Participants with stroke (PS) and neurologically unimpaired controls (UC) were enrolled. At enrolment, all participants were assessed for motor and cognitive functioning with specific scales (motricity index, trunk control test, Level of Cognitive Functioning, and Functional Independence Measure (FIM). Moreover, EEG data were recorded. At discharge, participants were re-tested with the FIM RESULTS: Powers in the delta, theta, alpha, and beta bands and connectivity within the fronto-parietal network were compared between groups. Then, the between-group discriminative EEG measures and the motor/cognitive scales were used to feed a machine learning algorithm to predict FIM scores at discharge and the length of hospitalization (LoH). Higher delta, theta, and beta and impaired connectivity were found in PS compared to UC. Moreover, motor/cognitive functioning, beta power, and fronto-parietal connectivity predicted the FIM score at discharge and the LoH (accuracy=73.2 % and 85.2 % respectively).

CONCLUSIONS

Results show that the integration of motor/cognitive scales and EEG measures can reveal the rehabilitative potentials of PS predicting their functional outcome and LoH.

SIGNIFICANCE

Synergistic clinical and electrophysiological models can support rehabilitative decision-making.

Assessing walking adaptability in children with cerebral palsy: validity and reliability of the walking adaptability ladder test for kids

INTRODUCTION

Assessing gait adaptation in children with cerebral palsy (CP) requires cost-effective and easily applicable methods.

OBJECTIVE

To evaluate the reliability and validity of the Walking Adaptability Ladder Test for Kids (WAL-K) in assessing gait adaptation in children with CP.

METHODS

Sixty-six participants (40 children with CP and 26 controls), aged 6-18 years, underwent WAL-K testing under single- and double-run conditions with video recording. Test-retest reliability, interrater reliability, concurrent validity, and known-group validity were assessed. Concurrent validity was assessed using the Timed Up and Go Test (TUGT), Four-Square Step Test (FSST), and Five Times Sit-to-Stand Test.

RESULTS

Interrater intraclass correlation coefficients (ICC3,k) values were > 0.999 for the WAL-K single- and double-run tests. The test-retest reliability ICC3,k values were 0.988 for the WAL-K single-run, and 0.963, 0.962, and 0.963 for the WAL-K double-run (p < .05). WAL-K double-run showed a strong correlation with FSST (r = 0.791), while WAL-K single-run correlated weakly with TUGT (r = 0.394) (p < .01). Moderate correlations were observed between other tests (p < .01). Children with CP had higher scores in all WAL-K tests compared to controls (p < .001).

CONCLUSION

The WAL-K test demonstrated validity and reliability, making it suitable for clinical use without requiring specialized laboratory settings. It enables repeated assessments of gait adaptation in children with CP.

Spatiospectral dynamics of electroencephalography patterns during propofol-induced alterations of consciousness states

Altered consciousness induced by anesthetics is characterized by distinct spatial and spectral neural dynamics that are readily apparent in the human electroencephalogram. Despite considerable study, we remain uncertain which brain regions and neural oscillations are involved, as well as how they are impacted when consciousness is disrupted. The experimental data was obtained from the open-access dataset, which contains pre-processed EEG data recorded from 20 healthy participants during propofol sedation. Using unsupervised machine learning methods (i.e., non-negative matrix factorization, NMF), we investigated the spatiospectral dynamic evolution of brain activity from awake to sedation and back induced by propofol in healthy research volunteers. Our methods yielded six dynamical patterns that continuously reflect the neural activity changes in specific brain regions and frequency bands under propofol sedation. Temporal dynamic analyses showed that differences in alpha oscillation patterns were less pronounced in response group than drowsy group, with hemispheric asymmetry in posterior occipital lobe over the course of the sedation procedure. We designed an index 'hemispheric lateralization modulation of alpha [HLM(α)]' to measure asymmetry during awake state and predicting individual variability in propofol-induced alterations of consciousness states, obtaining prediction AUC of 0.8462. We present an alpha modulation index which characterizes how these patterns track the transition from awake to sedation as a function of increasing dosage. Our study reveals dynamics indices that track the evolution of neurophysiological of propofol on brain circuits. Analyzing the spatiospectral dynamics influenced by propofol provides valuable understanding of the mechanisms of these agents and strategies for monitoring and precisely controlling the level of consciousness in patients under sedation and general anesthesia.

Using passive BCI for personalization of assistive wearable devices: a proof-of-concept study

Assistive wearable devices can significantly enhance the quality of life for individuals with movement impairments, aid the rehabilitation process, and augment movement abilities of healthy users. However, personalizing the assistance to individual preferences and needs remains a challenge. Brain-Computer Interface (BCI) offers a promising solution for this personalization problem. The overarching goal of this study is to investigate the feasibility of utilizing passive BCI technology to personalize the assistance provided by a knee exoskeleton. Participants performed seated knee flexion-extension tasks while wearing a one-degree-of-freedom knee exoskeleton with varying levels of applied force. Their brain activities were recorded throughout the movements using electroencephalography (EEG). EEG spectral bands from several brain regions were compared between the conditions with the lowest and highest exoskeleton forces to identify statistically significant changes. A Naive Bayes classifier was trained on these spectral features to distinguish between the two conditions. Statistical analysis revealed significant increases in δ and θ activity and decreases in α and β activity in the frontal, motor, and occipital cortices. These changes suggest heightened attention, concentration, and motor engagement when the task became more difficult. The trained Naive Bayes classifier achieved an average accuracy of approximately 72% in distinguishing between the two conditions. The outcomes of our study demonstrate the potential of passive BCI in personalizing assistance provided by wearable devices. Future research should further explore integrating passive BCI into assistive wearable devices to enhance user experience.

Perceptual information processing in table tennis players: based on top-down hierarchical predictive coding

Long-term training induces neural plasticity in the visual cognitive processing cortex of table tennis athletes, who perform cognitive processing in a resource-conserving manner. However, further discussion is needed to determine whether the spatial processing advantage of table tennis players manifests in the early stage of sensory input or the late stage of processing. This study aims to explore the processing styles and neural activity characteristics of table tennis players during spatial cognitive processing. Spatial cognitive tasks were completed by 28 college students and 20 s-level table tennis players, and event-related potentials (ERP) data were recorded during the task. The behavioral results showed that the table tennis group performed better on the task than the college students group (control). The ERP results showed that the amplitude of the N1 component of the table tennis group was significantly lower than that of the control group. The amplitude of the P2 and P3 components of the table tennis group was higher than that of the control group. Table tennis players showed significant synergistic activity between electrodes in the β-band. The results of this study suggest that table tennis players significantly deploy attentional resources and cognitive control. Further, they employ stored motor experience to process spatial information in a hierarchical predictive coding manner.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11571-024-10171-4.

Corticocortical and corticomuscular connectivity dynamics in standing posture: electroencephalography study

Cortical mechanism is necessary for human standing control. Previous research has demonstrated that cortical oscillations and corticospinal excitability respond flexibly to postural demands. However, it is unclear how corticocortical and corticomuscular connectivity changes dynamically during standing with spontaneous postural sway and over time. This study investigated the dynamics of sway- and time-varying connectivity using electroencephalography and electromyography. Electroencephalography and electromyography were recorded in sitting position and 3 standing postures with varying base-of-support: normal standing, one-leg standing, and standing on a piece of wood. For sway-varying connectivity, corticomuscular connectivity was calculated based on the timing of peak velocity in anteroposterior sway. For time-varying connectivity, corticocortical connectivity was measured using the sliding-window approach. This study found that corticomuscular connectivity was strengthened at the peak velocity of postural sway in the γ- and β-frequency bands. For time-varying corticocortical connectivity, the θ-connectivity in all time-epoch was classified into 7 clusters including posture-relevant component. In one of the 7 clusters, strong connectivity pairs were concentrated in the mid-central region, and the proportion of epochs under narrow-base standing conditions was significantly higher, indicating a functional role for posture balance. These findings shed light on the connectivity dynamics and cortical oscillation that govern standing balance.

Vision Is Not Required to Elicit Balance Improvements From Beam Walking Practice

BACKGROUND

Beam walking is a highly studied assessment of walking balance. Recent research has demonstrated that brief intermittent visual rotations and occlusions can increase the efficacy of beam walking practice on subsequent beam walking without visual perturbations. We sought to examine the influence of full vision removal during practice walking on a treadmill-mounted balance beam. Although visual disruptions improved performance of this task, we hypothesized that removing visual feedback completely would lead to less balance improvements than with normal vision due to the specificity of practice.

METHODS

Twenty healthy young adults trained to walk at a fixed speed on a treadmill-mounted balance beam for 30 min, either with, or without, normal vision. We compared their balance pre-, during, and posttraining by calculating their step-offs per minute and the percentage change in step-offs per minute.

RESULTS

Balance improved in both groups after training, with no significant difference in percentage change in step-offs between the normal vision and the no vision participants. On average, the no vision participants had twice as many step-offs per minute as the normal vision group during training.

CONCLUSION

Although previous experiments show that intermittent visual perturbations led to large enhancements of the effectiveness of beam walking training, completely removing visual feedback did not alter training effectiveness compared with normal vision training. It is likely a result of sensory reweighting in the absence of vision, where a greater weight was placed on proprioceptive, cutaneous, and vestibular inputs.

Wide-field calcium imaging of cortical activation and functional connectivity in externally- and internally-driven locomotion

The role of the cerebral cortex in self-initiated versus sensory-driven movements is central to understanding volitional action. Whether the differences in these two movement classes are due to specific cortical areas versus more cortex-wide engagement is debated. Using wide-field Ca2+ imaging, we compared neural dynamics during spontaneous and motorized treadmill locomotion, determining the similarities and differences in cortex-wide activation and functional connectivity (FC). During motorized locomotion, the cortex exhibits greater activation globally prior to and during locomotion starting compared to spontaneous and less during steady-state walking, during stopping, and after termination. Both conditions are characterized by FC increases in anterior secondary motor cortex (M2) nodes and decreases in all other regions. There are also cortex-wide differences; most notably, M2 decreases in FC with all other nodes during motorized stopping and after termination. Therefore, both internally- and externally-generated movements widely engage the cortex, with differences represented in cortex-wide activation and FC patterns.

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.

A systematic review of mobile brain/body imaging studies using the P300 event-related potentials to investigate cognition beyond the laboratory

The P300 ERP component, related to the onset of task-relevant or infrequent stimuli, has been widely used in the Mobile Brain/Body Imaging (MoBI) literature. This systematic review evaluates the quality and breadth of P300 MoBI studies, revealing a maturing field with well-designed research yet grappling with standardization and global representation challenges. While affirming the reliability of measuring P300 ERP components in mobile settings, the review identifies significant hurdles in standardizing data cleaning and processing techniques, impacting comparability and reproducibility. Geographical disparities emerge, with studies predominantly in the Global North and a dearth of research from the Global South, emphasizing the need for broader inclusivity to counter the WEIRD bias in psychology. Collaborative projects and mobile EEG systems showcase the feasibility of reaching diverse populations, which is essential to advance precision psychiatry and to integrate varied data streams. Methodologically, a trend toward ecological validity is noted, shifting from lab-based to real-world settings with portable EEG system advancements. Future hardware developments are expected to balance signal quality and sensor intrusiveness, enriching data collection in everyday contexts. Innovative methodologies reflect a move toward more natural experimental settings, prompting critical questions about the applicability of traditional ERP markers, such as the P300 outside structured paradigms. The review concludes by highlighting the crucial role of integrating mobile technologies, physiological sensors, and machine learning to advance cognitive neuroscience. It advocates for an operational definition of ecological validity to bridge the gap between controlled experiments and the complexity of embodied cognitive experiences, enhancing both theoretical understanding and practical application in study design.

Lateralized modulation of cortical beta power during human gait is related to arm swing

Human gait is a complex behavior requiring dynamic control of upper and lower extremities that is accompanied by cortical activity in multiple brain areas. We investigated the contribution of beta (15-30 Hz) and gamma (30-50 Hz) band electroencephalography (EEG) activity during specific phases of the gait cycle, comparing treadmill walking with and without arm swing. Modulations of spectral power in the beta band during early double support and swing phases source-localized to the sensorimotor cortex ipsilateral, but not contralateral, to the leading leg. The lateralization disappeared in the condition with constrained arms, together with an increase of activity in bilateral supplementary motor areas. By contrast, gamma band modulations that localized to the presumed leg area of sensorimotor cortex around the heel-strike events were unaffected by arm movement. Our findings demonstrate that arm swing is accompanied by considerable cortical activation that should not be neglected in gait-related neuroimaging studies.

Novice Users' Brain Activity and Biomechanics Change After Practicing Walking With an Ankle Exoskeleton

Walking with an exoskeleton represents a sophisticated interplay between human physiology and mechanical augmentation, yet understanding of cortical responses in this context remains limited. To address this gap, this study aimed to explore cortical responses during walking with an ankle exoskeleton, examining how these responses evolve with familiarity to the augmentation. Healthy participants without prior exoskeleton experience underwent EEG, EMG, and motion capture analysis while walking with exoskeleton assistance at 1.2m/s. Initially, exoskeleton-assisted walking induced significant biomechanical changes accompanied by corresponding cortical alterations, leading to increased cortical involvement. In addition, after a brief familiarization period, significant increases in alpha band cortical power were observed, indicating decreased cortical engagement. These findings hold significance for elucidating the cortical mechanisms involved in exoskeleton-assisted walking and may contribute to the development of more seamlessly integrated augmentation devices.

HD-tDCS over left supplementary motor area differentially modulated neural correlates of motor planning for speech vs. limb movement

The supplementary motor area (SMA) is implicated in planning, execution, and control of speech production and limb movement. The SMA is among putative generators of pre-movement EEG activity which is thought to be neural markers of motor planning. In neurological conditions such as Parkinson's disease, abnormal pre-movement neural activity within the SMA has been reported during speech production and limb movement. Therefore, this region can be a potential target for non-invasive brain stimulation for both speech and limb movement. The present study took an initial step in examining the application of high-definition transcranial direct current stimulation (HD-tDCS) over the left SMA in 24 neurologically intact adults. Subsequently, event-related potentials (ERPs) were recorded while participants performed speech and limb movement tasks. Participants' data were collected in three counterbalanced sessions: anodal, cathodal and sham HD-tDCS. Relative to sham stimulation, anodal, but not cathodal, HD-tDCS significantly attenuated ERPs prior to the onset of the speech production. In contrast, neither anodal nor cathodal HD-tDCS significantly modulated ERPs prior to the onset of limb movement compared to sham stimulation. These findings showed that neural correlates of motor planning can be modulated using HD-tDCS over the left SMA in neurotypical adults, with translational implications for neurological conditions that impair speech production. The absence of a stimulation effect on ERPs prior to the onset of limb movement was not expected in this study, and future studies are warranted to further explore this effect.

Mobile neuroimaging: What we have learned about the neural control of human walking, with an emphasis on EEG-based research

Our understanding of the neural control of human walking has changed significantly over the last twenty years and mobile brain imaging methods have contributed substantially to current knowledge. High-density electroencephalography (EEG) has the advantages of being lightweight and mobile while providing temporal resolution of brain changes within a gait cycle. Advances in EEG hardware and processing methods have led to a proliferation of research on the neural control of locomotion in neurologically intact adults. We provide a narrative review of the advantages and disadvantages of different mobile brain imaging methods, then summarize findings from mobile EEG studies quantifying electrocortical activity during human walking. Contrary to historical views on the neural control of locomotion, recent studies highlight the widespread involvement of many areas, such as the anterior cingulate, posterior parietal, prefrontal, premotor, sensorimotor, supplementary motor, and occipital cortices, that show active fluctuations in electrical power during walking. The electrocortical activity changes with speed, stability, perturbations, and gait adaptation. We end with a discussion on the next steps in mobile EEG research.

Exploring Electrocortical Signatures of Gait Adaptation: Differential Neural Dynamics in Slow and Fast Gait Adapters

Individuals exhibit significant variability in their ability to adapt locomotor skills, with some adapting quickly and others more slowly. Differences in brain activity likely contribute to this variability, but direct neural evidence is lacking. We investigated individual differences in electrocortical activity that led to faster locomotor adaptation rates. We recorded high-density electroencephalography while young, neurotypical adults adapted their walking on a split-belt treadmill and grouped them based on how quickly they restored their gait symmetry. Results revealed unique spectral signatures within the posterior parietal, bilateral sensorimotor, and right visual cortices that differ between fast and slow adapters. Specifically, fast adapters exhibited lower alpha power in the posterior parietal and right visual cortices during early adaptation, associated with quicker attainment of steady-state step length symmetry. Decreased posterior parietal alpha may reflect enhanced spatial attention, sensory integration, and movement planning to facilitate faster locomotor adaptation. Conversely, slow adapters displayed greater alpha and beta power in the right visual cortex during late adaptation, suggesting potential differences in visuospatial processing. Additionally, fast adapters demonstrated reduced spectral power in the bilateral sensorimotor cortices compared with slow adapters, particularly in the theta band, which may suggest variations in perception of the split-belt perturbation. These findings suggest that alpha and beta oscillations in the posterior parietal and visual cortices and theta oscillations in the sensorimotor cortex are related to the rate of gait adaptation.

Brain Networks Modulation during Simple and Complex Gait: A "Mobile Brain/Body Imaging" Study

Walking encompasses a complex interplay of neuromuscular coordination and cognitive processes. Disruptions in gait can impact personal independence and quality of life, especially among the elderly and neurodegenerative patients. While traditional biomechanical analyses and neuroimaging techniques have contributed to understanding gait control, they often lack the temporal resolution needed for rapid neural dynamics. This study employs a mobile brain/body imaging (MoBI) platform with high-density electroencephalography (hd-EEG) to explore event-related desynchronization and synchronization (ERD/ERS) during overground walking. Simultaneous to hdEEG, we recorded gait spatiotemporal parameters. Participants were asked to walk under usual walking and dual-task walking conditions. For data analysis, we extracted ERD/ERS in α, β, and γ bands from 17 selected regions of interest encompassing not only the sensorimotor cerebral network but also the cognitive and affective networks. A correlation analysis was performed between gait parameters and ERD/ERS intensities in different networks in the different phases of gait. Results showed that ERD/ERS modulations across gait phases in the α and β bands extended beyond the sensorimotor network, over the cognitive and limbic networks, and were more prominent in all networks during dual tasks with respect to usual walking. Correlation analyses showed that a stronger α ERS in the initial double-support phases correlates with shorter step length, emphasizing the role of attention in motor control. Additionally, β ERD/ERS in affective and cognitive networks during dual-task walking correlated with dual-task gait performance, suggesting compensatory mechanisms in complex tasks. This study advances our understanding of neural dynamics during overground walking, emphasizing the multidimensional nature of gait control involving cognitive and affective networks.

Dynamics of brain-muscle networks reveal effects of age and somatosensory function on gait

Walking is a complex motor activity that requires coordinated interactions between the sensory and motor systems. We used mobile EEG and EMG to investigate the brain-muscle networks involved in gait control during overground walking in young people, older people, and individuals with Parkinson's disease. Dynamic interactions between the sensorimotor cortices and eight leg muscles within a gait cycle were assessed using multivariate analysis. We identified three distinct brain-muscle networks during a gait cycle. These networks include a bilateral network, a left-lateralized network activated during the left swing phase, and a right-lateralized network active during the right swing. The trajectories of these networks are contracted in older adults, indicating a reduction in neuromuscular connectivity with age. Individuals with the impaired tactile sensitivity of the foot showed a selective enhancement of the bilateral network, possibly reflecting a compensation strategy to maintain gait stability. These findings provide a parsimonious description of interindividual differences in neuromuscular connectivity during gait.

The influence of prosthetic suspension on gait and cortical modulations is persons with a transfemoral amputation: socket-suspended versus bone-anchored prosthesis

BACKGROUND

Persons with a transfemoral amputation (TFA) often experience difficulties in daily-life ambulation, including an asymmetrical and less stable gait pattern and a greater cognitive demand of walking. However, it remains unclear whether this is effected by the prosthetic suspension, as eliminating the non-rigid prosthetic connection may influence stability and cortical activity during walking. Spatiotemporal and stability-related gait parameters, as well as cortical activity during walking, were evaluated between highly active individuals (MFC-level K3-4) with a TFA and able-bodied (AB) persons, and between persons with a bone-anchored prosthesis (BAP) and those with a socket-suspended prosthesis (SSP).

METHODS

18 AB persons and 20 persons with a unilateral TFA (10 BAP-users, 10 SSP-users) walked on a treadmill at their preferred speed. Spatiotemporal and margin of stability parameters were extracted from three-dimensional movement recordings. In addition, 126-channel electroencephalogram (EEG) was recorded. Brain-related activity from several cortical areas was isolated using independent component analysis. Source-level data were divided into gait cycles and subjected to time-frequency analysis to determine gait-cycle dependent modulations of cortical activity.

RESULTS

Persons with TFA walked with smaller and wider steps and with greater variability in mediolateral foot placement than AB subjects; no significant differences were found between BAP- and SSP-users. The EEG analysis yielded four cortical clusters in frontal, central (both hemispheres), and parietal areas. No statistically significant between-group differences were found in the mean power over the entire gait cycle. The event-related spectral perturbation maps revealed differences in power modulations (theta, alpha, and beta bands) between TFA and AB groups, and between BAP- and SSP-users, with largest differences observed around heel strike of either leg.

CONCLUSIONS

The anticipated differences in gait parameters in persons with TFA were confirmed, however no significant effect of the fixed suspension of a BAP was found. The preliminary EEG findings may indicate more active monitoring and control of stability in persons with TFA, which appeared to be timed differently in SSP than in BAP-users. Future studies may focus on walking tasks that challenge stability to further investigate differences related to prosthetic suspension.

Motor imagery ability scores are related to cortical activation during gait imagery

Motor imagery (MI) is the mental execution of actions without overt movements that depends on the ability to imagine. We explored whether this ability could be related to the cortical activity of the brain areas involved in the MI network. To this goal, brain activity was recorded using high-density electroencephalography in nineteen healthy adults while visually imagining walking on a straight path. We extracted Event-Related Desynchronizations (ERDs) in the θ, α, and β band, and we measured MI ability via (i) the Kinesthetic and Visual Imagery Questionnaire (KVIQ), (ii) the Vividness of Movement Imagery Questionnaire-2 (VMIQ), and (iii) the Imagery Ability (IA) score. We then used Pearson's and Spearman's coefficients to correlate MI ability scores and average ERD power (avgERD). Positive correlations were identified between VMIQ and avgERD of the middle cingulum in the β band and with avgERD of the left insula, right precentral area, and right middle occipital region in the θ band. Stronger activation of the MI network was related to better scores of MI ability evaluations, supporting the importance of testing MI ability during MI protocols. This result will help to understand MI mechanisms and develop personalized MI treatments for patients with neurological dysfunctions.

Reduced Proactive and Reactive Cognitive Flexibility in Older Adults Underlies Performance Costs During Dual-Task Walking: A Mobile Brain/Body Imaging (MoBI) Study

Age-related reductions in cognitive flexibility may limit modulation of control processes during systematic increases to cognitive-motor demands, exacerbating dual-task costs. In this study, behavioral and neurophysiologic changes to proactive and reactive control during progressive cognitive-motor demands were compared across older and younger adults to explore the basis for age-differences in cognitive-motor interference (CMI). 19 younger (19 - 29 years old, mean age = 22.84 +/- 2.75 years, 6 male, 13 female) and 18 older (60 - 77 years old, mean age = 67.89 +/- 4.60 years, 9 male, 9 female) healthy adults completed cued task-switching while alternating between sitting and walking on a treadmill. Gait kinematics, task performance measures, and brain activity were recorded using electroencephalography (EEG) based Mobile Brain/Body Imaging (MoBI). Response accuracy on easier trial types improved in younger, but not older adults when they walked while performing the cognitive task. As difficulty increased, walking provoked accuracy costs in older, but not younger adults. Both groups registered faster responses and reduced gait variability during dual-task walking. Older adults exhibited lower amplitude modulations of proactive and reactive neural activity as cognitive-motor demands systematically increased, which may reflect reduced flexibility for progressive preparatory and reactive adjustments over behavioral control.

EEG Dynamics of Locomotion and Balancing: Solution to Neuro-Rehabilitation

The past decade has witnessed tremendous growth in analyzing the cortical representation of human locomotion and balance using Electroencephalography (EEG). With the advanced developments in miniaturized electronics, wireless brain recording systems have been developed for mobile recordings, such as in locomotion. In this review, the cortical dynamics during locomotion are presented with extensive focus on motor imagery, and employing the treadmill as a tool for performing different locomotion tasks. Further, the studies that examine the cortical dynamics during balancing, focusing on two types of balancing tasks, ie, static and dynamic, with the challenges in sensory inputs and cognition (dual-task), are presented. Moreover, the current literature demonstrates the advancements in signal processing methods to detect and remove the artifacts from EEG signals. Prior studies show the electrocortical sources in the anterior cingulate, posterior parietal, and sensorimotor cortex was found to be activated during locomotion. The event-related potential has been observed to increase in the fronto-central region for a wide range of balance tasks. The advanced knowledge of cortical dynamics during mobility can benefit various application areas such as neuroprosthetics and gait/balance rehabilitation. This review will be beneficial for the development of neuroprostheses, and rehabilitation devices for patients suffering from movement or neurological disorders.

Decreased beta 1 (12-15 Hertz) power modulates the transfer of suicidal ideation to suicide in major depressive disorder

BACKGROUND

Suicide prevention for major depressive disorder (MDD) is a worldwide challenge, especially for suicide attempt (SA). Viewing suicide as a state rather than a lifetime event provided new perspectives on suicide research.

OBJECTIVE

This study aimed to verify and complement SAs biomarkers of MDD with a recent SA sample.

METHODS

This study included 189 participants (60 healthy controls; 47 MDD patients with non-suicide (MDD-NSs), 40 MDD patients with suicide ideation (MDD-SIs) and 42 MDD patients with SA (MDD-SAs)). MDD patients with an acute SA time was determined to be within 1 week since the last SA. SUICIDALITY Part in MINI was applied to evaluate suicidality. Absolute powers in 14 frequency bands were extracted from subject's resting-state electroencephalography data and compared within four groups. The relationship among suicidality, the number of SA and powers in significant frequency bands were investigated.

RESULTS

MDD-SIs had increased powers in delta, theta, alpha and beta band on the right frontocentral channels compared to MDD-NSs, while MDD-SAs had decreased powers in delta, beta and gamma bands on widely the right frontocentral and parietooccipital channels compared to MDD-SIs. Beta 1 power was the lowest in MDD-SAs and was modulated by the number of SA. The correlation between suicidality and beta 1 power was negative in MDD-SAs and positive in MDD-SIs.

CONCLUSION

Reduced beta 1 (12-15 Hz) power could be essential in promoting suicidal behaviour in MDD. Research on recent SA samples contributes to a better understanding of suicide mechanisms and preventing suicidal behaviour in MDD.

Electrocortical activity correlated with locomotor adaptation during split-belt treadmill walking

Locomotor adaptation is crucial for daily gait adjustments to changing environmental demands and obstacle avoidance. Mobile brain imaging with high-density electroencephalography (EEG) now permits quantification of electrocortical dynamics during human locomotion. To determine the brain areas involved in human locomotor adaptation, we recorded high-density EEG from healthy, young adults during split-belt treadmill walking. We incorporated a dual-electrode EEG system and neck electromyography to decrease motion and muscle artefacts. Voluntary movement preparation and execution have been linked to alpha (8-13 Hz) and beta band (13-30 Hz) desynchronizations in the sensorimotor and posterior parietal cortices, whereas theta band (4-7 Hz) modulations in the anterior cingulate have been correlated with movement error monitoring. We hypothesized that relative to normal walking, split-belt walking would elicit: (1) decreases in alpha and beta band power in sensorimotor and posterior parietal cortices, reflecting enhanced motor flexibility; and (2) increases in theta band power in anterior cingulate cortex, reflecting instability and balance errors that will diminish with practice. We found electrocortical activity in multiple regions that was associated with stages of gait adaptation. Data indicated that sensorimotor and posterior parietal cortices had decreased alpha and beta band spectral power during early adaptation to split-belt treadmill walking that gradually returned to pre-adaptation levels by the end of the adaptation period. Our findings emphasize that multiple brain areas are involved in adjusting gait under changing environmental demands during human walking. Future studies could use these findings on healthy, young participants to identify dysfunctional supraspinal mechanisms that may be impairing gait adaptation. KEY POINTS: Identifying the location and time course of electrical changes in the brain correlating with gait adaptation increases our understanding of brain function and provides targets for brain stimulation interventions. Using high-density EEG in combination with 3D biomechanics, we found changes in neural oscillations localized near the sensorimotor, posterior parietal and cingulate cortices during split-belt treadmill adaptation. These findings suggest that multiple cortical mechanisms may be associated with locomotor adaptation, and their temporal dynamics can be quantified using mobile EEG. Results from this study can serve as a reference model to examine brain dynamics in individuals with movement disorders that cause gait asymmetry and reduced gait adaptation.

Effect of Lower Limb Exoskeleton on the Modulation of Neural Activity and Gait Classification

Neurorehabilitation with robotic devices requires a paradigm shift to enhance human-robot interaction. The coupling of robot assisted gait training (RAGT) with a brain-machine interface (BMI) represents an important step in this direction but requires better elucidation of the effect of RAGT on the user's neural modulation. Here, we investigated how different exoskeleton walking modes modify brain and muscular activity during exoskeleton assisted gait. We recorded electroencephalographic (EEG) and electromyographic (EMG) activity from ten healthy volunteers walking with an exoskeleton with three modes of user assistance (i.e., transparent, adaptive and full assistance) and during free overground gait. Results identified that exoskeleton walking (irrespective of the exoskeleton mode) induces a stronger modulation of central mid-line mu (8-13 Hz) and low-beta (14-20 Hz) rhythms compared to free overground walking. These modifications are accompanied by a significant re-organization of the EMG patterns in exoskeleton walking. On the other hand, we observed no significant differences in neural activity during exoskeleton walking with the different assistance levels. We subsequently implemented four gait classifiers based on deep neural networks trained on the EEG data during the different walking conditions. Our hypothesis was that exoskeleton modes could impact the creation of a BMI-driven RAGT. We demonstrated that all classifiers achieved an average accuracy of 84.13±3.49% in classifying swing and stance phases on their respective datasets. In addition, we demonstrated that the classifier trained on the transparent mode exoskeleton data can classify gait phases during adaptive and full modes with an accuracy of 78.3±4.8% , while the classifier trained on free overground walking data fails to classify the gait during exoskeleton walking (accuracy of 59.4±11.8% ). These findings provide important insights into the effect of robotic training on neural activity and contribute to the advancement of BMI technology for improving robotic gait rehabilitation therapy.

Directed connectivity in Parkinson's disease patients during over-ground and treadmill walking

Treadmill walking is considered a useful therapeutic tool for improving gait in Parkinson's disease (PD) patients. The study investigated the role of top-down, frontal-parietal versus bottom-up parietal-frontal networks, during over-ground and treadmill walking in PD and control subjects, using functional connectivity. To this end, EEG was recorded simultaneously, during a ten-minute period of continuous walking either over-ground or on a treadmill, in thirteen PD patients and thirteen age-matched controls. We evaluated EEG directed connectivity, using phase transfer entropy in three frequency bands: theta, alpha and beta. PD patients showed increased top-down connectivity during over-ground compared with treadmill walking, in the beta frequency range. Control subjects showed no significant differences in connectivity between the two walking conditions. Our results suggest that in PD patients, OG walking was associated with increased allocation of attentional resources, compared with that on the TL. These functional connectivity modulations may shed further light on the mechanisms underlying treadmill versus overground walking in PD.

Mobile cognition: imaging the human brain in the 'real world'

Cognitive neuroscience studies in humans have enabled decades of impactful discoveries but have primarily been limited to recording the brain activity of immobile participants in a laboratory setting. In recent years, advances in neuroimaging technologies have enabled recordings of human brain activity to be obtained during freely moving behaviours in the real world. Here, we propose that these mobile neuroimaging methods can provide unique insights into the neural mechanisms of human cognition and contribute to the development of novel treatments for neurological and psychiatric disorders. We further discuss the challenges associated with studying naturalistic human behaviours in complex real-world settings as well as strategies for overcoming them. We conclude that mobile neuroimaging methods have the potential to bring about a new era of cognitive neuroscience in which neural mechanisms can be studied with increased ecological validity and with the ability to address questions about natural behaviour and cognitive processes in humans engaged in dynamic real-world experiences.

Effects of diabetes mellitus on step length and minimum toe clearance adaptation

BACKGROUND

Adaptive gait involves the ability to adjust the leading foot in response to the requirement of dynamic environments during walking. Accurate adjustments of the minimum toe clearance (MTC) height and step length can prevent older people from falling when walking and responding to hazards. Although older people with diabetes fall more frequently than healthy older adults, no previous studies have quantified their adaptive gait abilities. This study aimed to investigate the effects of diabetes mellitus on step length and MTC height adjustments using a non-immersive virtual-reality system.

METHODS

Sixteen young adults (26 ± 5 years, 7 females), 16 healthy older adults (68 ± 5 years, 6 females), and 16 older adults with diabetes (70 ± 5 years, 6 females) completed adaptability tests while walking on a treadmill. A computer system visualised a continuous real-time signal of absolute step length and MTC on a monitor. Each person responded to four discrete participant-specific step length and MTC visual targets that were presented on the same signal. Tasks were to match the peaks of interest on each signal to presented targets. Targets were 10% longer or shorter than the mean baseline step length, and 2.5 cm, and 3.5 cm higher than the mean baseline MTC. When a target was displayed, it remained unchanged for 10 consecutive foot displacement adaptation attempts. Then, the target was removed and a new target or the same target was present after 10 consecutive steps and remained for 10 steps. Each target was randomly presented three times (3 × 10). Step length and MTC height adjustments in response to targets were measured and compared among groups.

RESULTS

Mean preferred walking speeds were not different among groups significantly when no targets were presented on the monitor in baseline walking. However, when participants walked on a treadmill while attempting to match step lengths or MTC heights to displayed targets on the monitor, the group with diabetes had reduced step length and MTC adjustments compared with other groups significantly. They showed greater errors (differences between their step lengths/MTC heights and presented targets) on the monitor.

CONCLUSIONS

This study quantified reduced abilities for older individuals with diabetes to adjust both step length and MTC in response to stimuli compared to healthy older counterparts. Reduced step length and MTC height adjustments can increase falls in at risk populations. The presented virtual-reality system has merits for assessing and training step and MTC adaptation.

TMS Bursts Can Modulate Local and Networks Oscillations During Lower-Limb Movement

PURPOSE

Lower-limb motor functions involve processing information via both motor and cognitive control networks. Measuring oscillations is a key element in communication within and between cortical networks during high-order motor functions. Increased midfrontal theta oscillations are related to improved lower-limb motor performances in patients with movement disorders. Noninvasive neuromodulation approaches have not been explored extensively to understand the oscillatory mechanism of lower-limb motor functions. This study aims to examine the effects of repetitive transcranial magnetic stimulation on local and network EEG oscillations in healthy elderly subjects.

METHODS

Eleven healthy elderly subjects (67-73 years) were recruited via advertisements, and they underwent both active and sham stimulation procedures in a random, counterbalanced design. Transcranial magnetic stimulation bursts (θ-transcranial magnetic stimulation; 4 pulses/second) were applied over the midfrontal lead (vertex) before a GO-Cue pedaling task, and signals were analyzed using time-frequency methods.

RESULTS

Transcranial magnetic stimulation bursts increase the theta activity in the local ( p = 0.02) and the associated network during the lower-limb pedaling task ( p = 0.02). Furthermore, after task-related transcranial magnetic stimulation burst sessions, increased resting-state alpha activity was observed in the midfrontal region ( p = 0.01).

CONCLUSIONS

This study suggests the ability of midfrontal transcranial magnetic stimulation bursts to directly modulate local and network oscillations in a frequency manner during lower-limb motor task. Transcranial magnetic stimulation burst-induced modulation may provide insights into the functional roles of oscillatory activity during lower-limb movement in normal and disease conditions.

Wide-field calcium imaging of cortical activation and functional connectivity in externally- and internally-driven locomotion

The neural dynamics underlying self-initiated versus sensory driven movements is central to understanding volitional action. Upstream motor cortices are associated with the generation of internally-driven movements over externally-driven. Here we directly compare cortical dynamics during internally- versus externally-driven locomotion using wide-field Ca2+ imaging. We find that secondary motor cortex (M2) plays a larger role in internally-driven spontaneous locomotion transitions, with increased M2 functional connectivity during starting and stopping than in the externally-driven, motorized treadmill locomotion. This is not the case in steady-state walk. In addition, motorized treadmill and spontaneous locomotion are characterized by markedly different patterns of cortical activation and functional connectivity at the different behavior periods. Furthermore, the patterns of fluorescence activation and connectivity are uncorrelated. These experiments reveal widespread and striking differences in the cortical control of internally- and externally-driven locomotion, with M2 playing a major role in the preparation and execution of the self-initiated state.

Neural signature of mobility-related everyday function in older adults at-risk of cognitive impairment

Assessment of everyday activities is central to the diagnosis of dementia. Yet, little is known about brain processes associated with everyday functional limitations, particularly during early stages of cognitive decline. Twenty-six older adults (mean = 74.9 y) were stratified by risk using the Montreal Cognitive Assessment battery (MoCA, range: 0- 30) to classify individuals as higher (22-26) and lower risk (27+) of cognitive impairment. We investigated everyday function using a gait task designed to destabilize posture and applied Mobile Brain/Body Imaging. We predicted that participants would increase step width to gain stability, yet the underlying neural signatures would be different for lower versus higher risk individuals. Step width and fronto-parietal activation increased during visually perturbed input. Frontomedial theta increased in higher risk individuals during perturbed and unperturbed inputs. Left sensorimotor beta decreased in lower risk individuals during visually perturbed input. Modulations in theta and beta power were associated with MoCA scores. Our findings suggest that older adults at-risk of cognitive impairment can be characterized by a unique neural signature of everyday function.

Experiment protocols for brain-body imaging of locomotion: A systematic review

Introduction

Human locomotion is affected by several factors, such as growth and aging, health conditions, and physical activity levels for maintaining overall health and well-being. Notably, impaired locomotion is a prevalent cause of disability, significantly impacting the quality of life of individuals. The uniqueness and high prevalence of human locomotion have led to a surge of research to develop experimental protocols for studying the brain substrates, muscle responses, and motion signatures associated with locomotion. However, from a technical perspective, reproducing locomotion experiments has been challenging due to the lack of standardized protocols and benchmarking tools, which impairs the evaluation of research quality and the validation of previous findings.

Methods

This paper addresses the challenges by conducting a systematic review of existing neuroimaging studies on human locomotion, focusing on the settings of experimental protocols, such as locomotion intensity, duration, distance, adopted brain imaging technologies, and corresponding brain activation patterns. Also, this study provides practical recommendations for future experiment protocols.

Results

The findings indicate that EEG is the preferred neuroimaging sensor for detecting brain activity patterns, compared to fMRI, fNIRS, and PET. Walking is the most studied human locomotion task, likely due to its fundamental nature and status as a reference task. In contrast, running has received little attention in research. Additionally, cycling on an ergometer at a speed of 60 rpm using fNIRS has provided some research basis. Dual-task walking tasks are typically used to observe changes in cognitive function. Moreover, research on locomotion has primarily focused on healthy individuals, as this is the scenario most closely resembling free-living activity in real-world environments.

Discussion

Finally, the paper outlines the standards and recommendations for setting up future experiment protocols based on the review findings. It discusses the impact of neurological and musculoskeletal factors, as well as the cognitive and locomotive demands, on the experiment design. It also considers the limitations imposed by the sensing techniques used, including the acceptable level of motion artifacts in brain-body imaging experiments and the effects of spatial and temporal resolutions on brain sensor performance. Additionally, various experiment protocol constraints that need to be addressed and analyzed are explained.

Mapping Research Trends from 20 Years of Publications in Rhythmic Auditory Stimulation

This study aims to create an all-around insight into the evolutions, status, and global trends of rhythmic auditory stimulation (RAS) research via enhanced bibliometric methods for the 2001-2020 time period. Articles concerning RAS were extracted from the Web of Science database. CiteSpace, Bibliometrix, VOSviewer, and Graphpad Prism were employed to analyze publication patterns and research trends. A total of 586 publications related to RAS between 2001 and 2020 were retrieved from the Web of Science database. The researcher Goswami U. made the greatest contribution to this field. The University of Toronto was the institution that published the most articles. Motor dysfunction, sensory perception, and cognition are the three major domains of RAS research. Neural tracking, working memory, and neural basis may be the latest research frontiers. This study reveals the publication patterns and topic trends of RAS based on the records published between 2001 and 2020. The insights obtained provided useful references for the future research and applications of RAS.

A secondary motor area contributing to interlimb coordination during visually guided locomotion in the cat

We investigated the contribution of cytoarchitectonic cortical area 4δc, in the caudal bank of the cruciate sulcus of the cat, to the control of visually guided locomotion. To do so, we recorded the activity of 114 neurons in 4δc while cats walked on a treadmill and stepped over an obstacle that advanced toward them. A total of 84/114 (74%) cells were task-related and 68/84 (81%) of these cells showed significant modulation of their discharge frequency when the contralateral limbs were the first to step over the obstacle. These latter cells included a substantial proportion (27/68 40%) that discharged between the passage of the contralateral forelimb and the contralateral hindlimb over the obstacle, suggesting a contribution of this area to interlimb coordination. We further compared the discharge in area 4δc with the activity patterns of cells in the rostral division of the same cytoarchitectonic area (4δr), which has been suggested to be a separate functional region. Despite some differences in the patterns of activity in the 2 subdivisions, we suggest that activity in each is compatible with a contribution to interlimb coordination and that they should be considered as a single functional area that contributes to both forelimb-forelimb and forelimb-hindlimb coordination.

A systematic review of the prediction of consumer preference using EEG measures and machine-learning in neuromarketing research

Introduction

The present paper discusses the findings of a systematic review of EEG measures in neuromarketing, identifying which EEG measures are the most robust predictor of customer preference in neuromarketing. The review investigated which TF effect (e.g., theta-band power), and ERP component (e.g., N400) was most consistently reflective of self-reported preference. Machine-learning prediction also investigated, along with the use of EEG when combined with physiological measures such as eye-tracking.

Methods

Search terms ‘neuromarketing’ and ‘consumer neuroscience’ identified papers that used EEG measures. Publications were excluded if they were primarily written in a language other than English or were not published as journal articles (e.g., book chapters). 174 papers were included in the present review.

Results

Frontal alpha asymmetry (FAA) was the most reliable TF signal of preference and was able to differentiate positive from negative consumer responses. Similarly, the late positive potential (LPP) was the most reliable ERP component, reflecting conscious emotional evaluation of products and advertising. However, there was limited consistency across papers, with each measure showing mixed results when related to preference and purchase behaviour.

Conclusions and implications

FAA and the LPP were the most consistent markers of emotional responses to marketing stimuli, consumer preference and purchase intention. Predictive accuracy of FAA and the LPP was greatly improved through the use of machine-learning prediction, especially when combined with eye-tracking or facial expression analyses.

Dual-task walking improvement with enhanced kinesthetic awareness in Parkinson's disease with mild gait impairment: EEG connectivity and clinical implication

Due to basal ganglia dysfunction, short step length is a common gait impairment in Parkinson's disease (PD), especially in a dual-task walking. Here, we use electroencephalography (EEG) functional connectivity to investigate neural mechanisms of a stride awareness strategy that could improve dual-task walking in PD. Eighteen individuals with PD who had mild gait impairment walked at self-paced speed while keeping two interlocking rings from touching each other. During the dual-task walking trial, the participants received or did not receive awareness instruction to take big steps. Gait parameters, ring-touching time, and EEG connectivity in the alpha and beta bands were analyzed. With stride awareness, individuals with PD exhibited greater gait velocity and step length, along with a significantly lower mean EEG connectivity strength in the beta band. The awareness-related changes in the EEG connectivity strength of the beta band positively correlated with the awareness-related changes in gait velocity, cadence, and step length, but negatively correlated with the awareness-related change in step-length variability. The smaller reduction in beta connectivity strength was associated with greater improvement in locomotion control with stride awareness. This study is the first to reveal that a stride awareness strategy modulates the beta band oscillatory network and is related to walking efficacy in individuals with PD in a dual-task condition.

Mobile electroencephalography captures differences of walking over even and uneven terrain but not of single and dual-task gait

Walking on natural terrain while performing a dual-task, such as typing on a smartphone is a common behavior. Since dual-tasking and terrain change gait characteristics, it is of interest to understand how altered gait is reflected by changes in gait-associated neural signatures. A study was performed with 64-channel electroencephalography (EEG) of healthy volunteers, which was recorded while they walked over uneven and even terrain outdoors with and without performing a concurrent task (self-paced button pressing with both thumbs). Data from n = 19 participants (M = 24 years, 13 females) were analyzed regarding gait-phase related power modulations (GPM) and gait performance (stride time and stride time-variability). GPMs changed significantly with terrain, but not with the task. Descriptively, a greater beta power decrease following right-heel strikes was observed on uneven compared to even terrain. No evidence of an interaction was observed. Beta band power reduction following the initial contact of the right foot was more pronounced on uneven than on even terrain. Stride times were longer on uneven compared to even terrain and during dual- compared to single-task gait, but no significant interaction was observed. Stride time variability increased on uneven terrain compared to even terrain but not during single- compared to dual-tasking. The results reflect that as the terrain difficulty increases, the strides become slower and more irregular, whereas a secondary task slows stride duration only. Mobile EEG captures GPM differences linked to terrain changes, suggesting that the altered gait control demands and associated cortical processes can be identified. This and further studies may help to lay the foundation for protocols assessing the cognitive demand of natural gait on the motor system.

Abnormal neural oscillations during gait and dual-task in Parkinson’s disease

Gait dysfunctions are debilitating motor symptoms of Parkinson’s disease (PD) and may result in frequent falling with health complications. The contribution of the motor-cognitive network to gait disturbance can be studied more thoroughly by challenging motor-cognitive dual-task gait performances. Gait is a complex motor task that requires an appropriate contribution from motor and cognitive networks, reflected in frequency modulations among several cortical and subcortical networks. Electrophysiological recordings by scalp electroencephalography and implanted deep brain stimulation (DBS) electrodes have unveiled modulations of specific oscillatory patterns in the cortical-subcortical circuits in PD. In this review, we summarize oscillatory contributions of the cortical, basal ganglia, mesencephalic locomotor, and cerebellar regions during gait and dual-task activities in PD. We detail the involvement of the cognitive network in dual-task settings and compare how abnormal oscillations in the specific frequency bands in the cortical and subcortical regions correlate with gait deficits in PD, particularly freezing of gait (FOG). We suggest that altered neural oscillations in different frequencies can cause derangements in broader brain networks, so neuromodulation and pharmacological therapies should be considered to normalize those network oscillations to improve challenged gait and dual-task motor functions in PD. Specifically, the theta and beta bands in premotor cortical areas, subthalamic nucleus, as well as alpha band activity in the brainstem prepontine nucleus, modulate under clinically effective levodopa and DBS therapies, improving gait and dual-task performance in PD with FOG, compared to PD without FOG and age-matched healthy control groups.

Corticomuscular Connectivity during Walking in Able Bodied and Individuals with Incomplete Spinal Cord Injury

This exploratory study used EEG as mobile imaging method to study cortico-muscular connectivity (CMC) during walking in able-bodied individuals (AB) and individuals with spinal cord injury (iSCI), while walking with and without exoskeleton walking robot (EWR) assistance. We also explored change in CMC after intensive training using EWR assistance in iSCI. Results showed no different in CMC within the AB group during walking with and without robot assistance. However, before training the iSCI subjects showed lower CMC during walking with robot assistance. The intensive 40 hours of walking training with EWR improved the walking function in iSCI participants allowing them to walk with robot assistance set to lower assistance level. This decrease in assistance level and improvement in walking function correlated with increase in CMC, reducing the difference in CMC during walking with and without EWR assistance. The findings suggest that high level of robot assistance and low walking function in iSCI correlates with weaker connectivity between primary motor cortices and lower extremity muscles. Further research is needed to better understand the importance of intention and cortical involvement in training of walking function using EWRs. Clinical Relevance - This study provides innovative data on CMC during walking and how it changes with EWR assistance and with training. This research is important to the clinical field to provide recommendations of how training of walking function can be delivered to maximize cortical engagement and improve rehabilitation outcomes.

Exploring EEG spectral and temporal dynamics underlying a hand grasp movement

For brain-computer interfaces, resolving the differences between pre-movement and movement requires decoding neural ensemble activity in the motor cortex's functional regions and behavioural patterns. Here, we explored the underlying neural activity and mechanisms concerning a grasped motor task by recording electroencephalography (EEG) signals during the execution of hand movements in healthy subjects. The grasped movement included different tasks; reaching the target, grasping the target, lifting the object upwards, and moving the object in the left or right directions. 163 trials of EEG data were acquired from 30 healthy participants who performed the grasped movement tasks. Rhythmic EEG activity was analysed during the premovement (alert task) condition and compared against grasped movement tasks while the arm was moved towards the left or right directions. The short positive to negative deflection that initiated around -0.5ms as a wave before the onset of movement cue can be used as a potential biomarker to differentiate movement initiation and movement. A rebound increment of 14% of beta oscillations and 26% gamma oscillations in the central regions was observed and could be used to distinguish pre-movement and grasped movement tasks. Comparing movement initiation to grasp showed a decrease of 10% in beta oscillations and 13% in gamma oscillations, and there was a rebound increment 4% beta and 3% gamma from grasp to grasped movement. We also investigated the combination MRCPs and spectral estimates of α, β, and γ oscillations as features for machine learning classifiers that could categorize movement conditions. Support vector machines with 3rd order polynomial kernel yielded 70% accuracy. Pruning the ranked features to 5 leaf nodes reduced the error rate by 16%. For decoding grasped movement and in the context of BCI applications, this study identifies potential biomarkers, including the spatio-temporal characteristics of MRCPs, spectral information, and choice of classifiers for optimally distinguishing initiation and grasped movement.

Assessing Neurokinematic and Neuromuscular Connectivity During Walking Using Mobile Brain-Body Imaging

Gait is a common but rather complex activity that supports mobility in daily life. It requires indeed sophisticated coordination of lower and upper limbs, controlled by the nervous system. The relationship between limb kinematics and muscular activity with neural activity, referred to as neurokinematic and neuromuscular connectivity (NKC/NMC) respectively, still needs to be elucidated. Recently developed analysis techniques for mobile high-density electroencephalography (hdEEG) recordings have enabled investigations of gait-related neural modulations at the brain level. To shed light on gait-related neurokinematic and neuromuscular connectivity patterns in the brain, we performed a mobile brain/body imaging (MoBI) study in young healthy participants. In each participant, we collected hdEEG signals and limb velocity/electromyography signals during treadmill walking. We reconstructed neural signals in the alpha (8–13 Hz), beta (13–30 Hz), and gamma (30–50 Hz) frequency bands, and assessed the co-modulations of their power envelopes with myogenic/velocity envelopes. Our results showed that the myogenic signals have larger discriminative power in evaluating gait-related brain-body connectivity with respect to kinematic signals. A detailed analysis of neuromuscular connectivity patterns in the brain revealed robust responses in the alpha and beta bands over the lower limb representation in the primary sensorimotor cortex. There responses were largely contralateral with respect to the body sensor used for the analysis. By using a voxel-wise analysis of variance on the NMC images, we revealed clear modulations across body sensors; the variability across frequency bands was relatively lower, and below significance. Overall, our study demonstrates that a MoBI platform based on hdEEG can be used for the investigation of gait-related brain-body connectivity. Future studies might involve more complex walking conditions to gain a better understanding of fundamental neural processes associated with gait control, or might be conducted in individuals with neuromotor disorders to identify neural markers of abnormal gait.

Frequency-dependent modulation of neural oscillations across the gait cycle

Balance and walking are fundamental to support common daily activities. Relatively accurate characterizations of normal and impaired gait features were attained at the kinematic and muscular levels. Conversely, the neural processes underlying gait dynamics still need to be elucidated. To shed light on gait‐related modulations of neural activity, we collected high‐density electroencephalography (hdEEG) signals and ankle acceleration data in young healthy participants during treadmill walking. We used the ankle acceleration data to segment each gait cycle in four phases: initial double support, right leg swing, final double support, left leg swing. Then, we processed hdEEG signals to extract neural oscillations in alpha, beta, and gamma bands, and examined event‐related desynchronization/synchronization (ERD/ERS) across gait phases. Our results showed that ERD/ERS modulations for alpha, beta, and gamma bands were strongest in the primary sensorimotor cortex (M1), but were also found in premotor cortex, thalamus and cerebellum. We observed a modulation of neural oscillations across gait phases in M1 and cerebellum, and an interaction between frequency band and gait phase in premotor cortex and thalamus. Furthermore, an ERD/ERS lateralization effect was present in M1 for the alpha and beta bands, and in the cerebellum for the beta and gamma bands. Overall, our findings demonstrate that an electrophysiological source imaging approach based on hdEEG can be used to investigate dynamic neural processes of gait control. Future work on the development of mobile hdEEG‐based brain–body imaging platforms may enable overground walking investigations, with potential applications in the study of gait disorders.

Building FAIR Functionality: Annotating Events in Time Series Data Using Hierarchical Event Descriptors (HED)

Human electrophysiological and related time series data are often acquired in complex, event-rich environments. However, the resulting recorded brain or other dynamics are often interpreted in relation to more sparsely recorded or subsequently-noted events. Currently a substantial gap exists between the level of event description required by current digital data archiving standards and the level of annotation required for successful analysis of event-related data across studies, environments, and laboratories. Manifold challenges must be addressed, most prominently ontological clarity, vocabulary extensibility, annotation tool availability, and overall usability, to allow and promote sharing of data with an effective level of descriptive detail for labeled events. Motivating data authors to perform the work needed to adequately annotate their data is a key challenge. This paper describes new developments in the Hierarchical Event Descriptor (HED) system for addressing these issues. We recap the evolution of HED and its acceptance by the Brain Imaging Data Structure (BIDS) movement, describe the recent release of HED-3G, a third generation HED tools and design framework, and discuss directions for future development. Given consistent, sufficiently detailed, tool-enabled, field-relevant annotation of the nature of recorded events, prospects are bright for large-scale analysis and modeling of aggregated time series data, both in behavioral and brain imaging sciences and beyond.

Stepping in time: Alpha-mu and beta oscillations during a walking synchronization task

Interpersonal behavioral synchrony is referred to as temporal coordination of action between two or more individuals. Humans tend to synchronize their movements during repetitive movement tasks such as walking. Mobile EEG technology now allows us to examine how this happens during gait. 18 participants equipped with foot accelerometers and mobile EEG walked with an experimenter in three conditions: With their view of the experimenter blocked, walking naturally, and trying to synchronize their steps with the experimenter. The experimenter walked following a headphone metronome to keep their steps consistent for all conditions. Step behavior and synchronization between the experimenter and participant were compared between conditions. Additionally, event-related spectral perturbations (ERSPs) were time-warped to the gait cycle in order to analyze alpha-mu (7.5-12.5 Hz) and beta (16-32 Hz) rhythms over the whole gait cycle. Step synchronization was significantly higher in the synchrony condition than in the natural condition. Likewise regarding ERSPs, right parietal channel (C4, C6, CP4, CP6) alpha-mu and central channel (C1, Cz, C2) beta power were suppressed from baseline in the walking synchrony condition compared to the natural walking condition. The natural and blocked conditions were not found to be significantly different in behavioral or spectral comparisons. Our results are compatible with the view that intentional synchronization employs systems associated with social interaction as well as the central motor system.

Combined Subthalamic and Nigral Stimulation Modulates Temporal Gait Coordination and Cortical Gait-Network Activity in Parkinson's Disease

Background

Freezing of gait (FoG) is a disabling burden for Parkinson's disease (PD) patients with poor response to conventional therapies. Combined deep brain stimulation of the subthalamic nucleus and substantia nigra (STN+SN DBS) moved into focus as a potential therapeutic option to treat the parkinsonian gait disorder and refractory FoG. The mechanisms of action of DBS within the cortical-subcortical-basal ganglia network on gait, particularly at the cortical level, remain unclear.

Methods

Twelve patients with idiopathic PD and chronically-implanted DBS electrodes were assessed on their regular dopaminergic medication in a standardized stepping in place paradigm. Patients executed the task with DBS switched off (STIM OFF), conventional STN DBS and combined STN+SN DBS and were compared to healthy matched controls. Simultaneous high-density EEG and kinematic measurements were recorded during resting-state, effective stepping, and freezing episodes.

Results

Clinically, STN+SN DBS was superior to conventional STN DBS in improving temporal stepping variability of the more affected leg. During resting-state and effective stepping, the cortical activity of PD patients in STIM OFF was characterized by excessive over-synchronization in the theta (4-8 Hz), alpha (9-13 Hz), and high-beta (21-30 Hz) band compared to healthy controls. Both active DBS settings similarly decreased resting-state alpha power and reduced pathologically enhanced high-beta activity during resting-state and effective stepping compared to STIM OFF. Freezing episodes during STN DBS and STN+SN DBS showed spectrally and spatially distinct cortical activity patterns when compared to effective stepping. During STN DBS, FoG was associated with an increase in cortical alpha and low-beta activity over central cortical areas, while with STN+SN DBS, an increase in high-beta was prominent over more frontal areas.

Conclusions

STN+SN DBS improved temporal aspects of parkinsonian gait impairment compared to conventional STN DBS and differentially affected cortical oscillatory patterns during regular locomotion and freezing suggesting a potential modulatory effect on dysfunctional cortical-subcortical communication in PD.

Neuronal activity reorganization in motor cortex for successful locomotion after a lesion in the ventrolateral thalamus

Thalamic stroke leads to ataxia if the cerebellum-receiving ventrolateral thalamus (VL) is affected. The compensation mechanisms for this deficit are not well understood, particularly the roles that single neurons and specific neuronal subpopulations outside the thalamus play in recovery. The goal of this study was to clarify neuronal mechanisms of the motor cortex involved in mitigation of ataxia during locomotion when part of the VL is inactivated or lesioned. In freely ambulating cats, we recorded the activity of neurons in layer V of the motor cortex as the cats walked on a flat surface and horizontally placed ladder. We first reversibly inactivated ∼10% of the VL unilaterally using glutamatergic transmission antagonist CNQX and analyzed how the activity of motor cortex reorganized to support successful locomotion. We next lesioned 50%-75% of the VL bilaterally using kainic acid and analyzed how the activity of motor cortex reorganized when locomotion recovered. When a small part of the VL was inactivated, the discharge rates of motor cortex neurons decreased, but otherwise the activity was near normal, and the cats walked fairly well. Individual neurons retained their ability to respond to the demand for accuracy during ladder locomotion; however, most changed their response. When the VL was lesioned, the cat walked normally on the flat surface but was ataxic on the ladder for several days after lesion. When ladder locomotion normalized, neuronal discharge rates on the ladder were normal, and the shoulder-related group was preferentially active during the stride's swing phase.NEW & NOTEWORTHY This is the first analysis of reorganization of the activity of single neurons and subpopulations of neurons related to the shoulder, elbow, or wrist, as well as fast- and slow-conducting pyramidal tract neurons in the motor cortex of animals walking before and after inactivation or lesion in the thalamus. The results offer unique insights into the mechanisms of spontaneous recovery after thalamic stroke, potentially providing guidance for new strategies to alleviate locomotor deficits after stroke.

Small directional treadmill perturbations induce differential gait stability adaptation

Introducing unexpected perturbations to challenge gait stability is an effective approach to investigate balance control strategies. Little is known about the extent to which people can respond to small perturbations during walking. This study aimed to determine how subjects adapted gait stability to multidirectional perturbations with small magnitudes applied on a stride-by-stride basis. Ten healthy young subjects walked on a treadmill that either briefly decelerated belt speed (“stick”), accelerated belt speed (“slip”), or shifted the platform medial-laterally at right leg mid-stance. We quantified gait stability adaptation in both anterior-posterior and medial-lateral directions using margin of stability and its components, base of support, and extrapolated center of mass. Gait stability was disrupted upon initially experiencing the small perturbations as margin of stability decreased in the stick, slip, and medial shift perturbations and increased in the lateral shift perturbation. Gait stability metrics were generally disrupted more for perturbations in the coincident direction. Subjects employed both feedback and feedforward strategies in response to the small perturbations, but mostly used feedback strategies during adaptation. Subjects primarily used base of support (foot placement) control in the lateral shift perturbation and extrapolated center of mass control in the slip and medial shift perturbations. These findings provide new knowledge about the extent of gait stability adaptation to small magnitude perturbations applied on a stride-by-stride basis and reveal potential new approaches for balance training interventions to target foot placement and center of mass control.

NEW & NOTEWORTHY Little is known about if and how humans can adapt to small magnitude perturbations experienced on a stride-by-stride basis during walking. Here, we show that even small perturbations disrupted gait stability and that subjects could still adapt their reactive balance control. Depending on the perturbation direction, subjects might prefer adjusting their foot placement over their center of mass and vice versa. These findings could help potentially tune balance training to target specific aspects of balance.

A multi-step blind source separation approach for the attenuation of artifacts in mobile high-density electroencephalography data

Objective.Electroencephalography (EEG) is a widely used technique to address research questions about brain functioning, from controlled laboratorial conditions to naturalistic environments. However, EEG data are affected by biological (e.g. ocular, myogenic) and non-biological (e.g. movement-related) artifacts, which-depending on their extent-may limit the interpretability of the study results. Blind source separation (BSS) approaches have demonstrated to be particularly promising for the attenuation of artifacts in high-density EEG (hdEEG) data. Previous EEG artifact removal studies suggested that it may not be optimal to use the same BSS method for different kinds of artifacts.Approach.In this study, we developed a novel multi-step BSS approach to optimize the attenuation of ocular, movement-related and myogenic artifacts from hdEEG data. For validation purposes, we used hdEEG data collected in a group of healthy participants in standing, slow-walking and fast-walking conditions. During part of the experiment, a series of tone bursts were used to evoke auditory responses. We quantified event-related potentials (ERPs) using hdEEG signals collected during an auditory stimulation, as well as the event-related desynchronization (ERD) by contrasting hdEEG signals collected in walking and standing conditions, without auditory stimulation. We compared the results obtained in terms of auditory ERP and motor-related ERD using the proposed multi-step BSS approach, with respect to two classically used single-step BSS approaches.Main results. The use of our approach yielded the lowest residual noise in the hdEEG data, and permitted to retrieve stronger and more reliable modulations of neural activity than alternative solutions. Overall, our study confirmed that the performance of BSS-based artifact removal can be improved by using specific BSS methods and parameters for different kinds of artifacts.Significance.Our technological solution supports a wider use of hdEEG-based source imaging in movement and rehabilitation studies, and contributes to the further development of mobile brain/body imaging applications.

Unexpected Terrain Induced Changes in Cortical Activity in Bipedal-Walking Rats

Simple Summary

Most studies on cortical dynamics during walking require subjects to walk stably on specific terrain. In fact, humans or other animals are often disturbed by an abrupt change in terrains during walking. To study the impact of unexpected terrain on cortical activity, we analyzed the kinematics and electroencephalography (EEG) dynamics of bipedal-walking rats after encountering unexpected terrain. We found that the gait of rats after encountering the unexpected terrain were significantly different from normal walking. Furthermore, the activities of the left and right primary motor areas (M1), the left and right primary somatosensory areas (S1), and the retrosplenial area (RSP) are coupled to gait cycle phase and varied with the terrain conditions. These findings suggest that unexpected terrains induced changes in gait and cortical activity, and provide novel insights into cortical dynamics during walking.

Abstract

Humans and other animals can quickly respond to unexpected terrains during walking, but little is known about the cortical dynamics in this process. To study the impact of unexpected terrains on brain activity, we allowed rats with blocked vision to walk on a treadmill in a bipedal posture and then walk on an uneven area at a random position on the treadmill belt. Whole brain EEG signals and hind limb kinematics of bipedal-walking rats were recorded. After encountering unexpected terrain, the θ band power of the bilateral M1, the γ band power of the left S1, and the θ to γ band power of the RSP significantly decreased compared with normal walking. Furthermore, when the rats left uneven terrain, the β band power of the bilateral M1 and the α band power of the right M1 decreased, while the γ band power of the left M1 significantly increased compared with normal walking. Compared with the flat terrain, the θ to low β (3–20 Hz) band power of the bilateral S1 increased after the rats contacted the uneven terrain and then decreased in the single- or double- support phase. These results support the hypothesis that unexpected terrains induced changes in cortical activity.

Neural markers of proactive and reactive cognitive control are altered during walking: A Mobile Brain-Body Imaging (MoBI) study

The processing of sensory information and the generation of motor commands needed to produce coordinated actions can interfere with ongoing cognitive tasks. Even simple motor behaviors like walking can alter cognitive task performance. This cognitive-motor interference (CMI) could arise from disruption of planning in anticipation of carrying out the task (proactive control) and/or from disruption of the execution of the task (reactive control). In young healthy adults, walking-induced interference with behavioral performance may not be readily observable because flexibility in neural circuits can compensate for the added demands of simultaneous loads. In this study, cognitive-motor loads were systematically increased during cued task-switching while underlying neurophysiologic changes in proactive and reactive mechanisms were measured. Brain activity was recorded from 22 healthy young adults using 64-channel electroencephalography (EEG) based Mobile Brain/Body Imaging (MoBI) as they alternately sat or walked during performance of cued task-switching. Walking altered neurophysiological indices of both proactive and reactive control. Walking amplified cue-evoked late fontal slow waves, and reduced the amplitude of target-evoked fronto-central N2 and parietal P3. The effects of walking on evoked neural responses systematically increased as the task became increasingly difficult. This may provide an objective brain marker of increasing cognitive load, and may prove to be useful in identifying seemingly healthy individuals who are currently able to disguise ongoing degenerative processes through active compensation. If, however, degeneration continues unabated these people may reach a compensatory limit at which point both cognitive performance and control of coordinated actions may decline rapidly.