Differentiation in Theta and Beta Electrocortical Activity between Visual and Physical Perturbations to Walking and Standing Balance

Mobile Electroencephalography for Studying Neural Control of Human Locomotion

Walking or running in real-world environments requires dynamic multisensory processing within the brain. Studying supraspinal neural pathways during human locomotion provides opportunities to better understand complex neural circuity that may become compromised due to aging, neurological disorder, or disease. Knowledge gained from studies examining human electrical brain dynamics during gait can also lay foundations for developing locomotor neurotechnologies for rehabilitation or human performance. Technical barriers have largely prohibited neuroimaging during gait, but the portability and precise temporal resolution of non-invasive electroencephalography (EEG) have expanded human neuromotor research into increasingly dynamic tasks. In this narrative mini-review, we provide a (1) brief introduction and overview of modern neuroimaging technologies and then identify considerations for (2) mobile EEG hardware, (3) and data processing, (4) including technical challenges and possible solutions. Finally, we summarize (5) knowledge gained from human locomotor control studies that have used mobile EEG, and (6) discuss future directions for real-world neuroimaging research.

Brain Activity Response to Visual Cues for Gait Impairment in Parkinson's Disease: An EEG Study

Background. Gait impairments are common in Parkinson's disease (PD) and increase falls risk. Visual cues can improve gait in PD, particularly freezing of gait (FOG), but mechanisms involved in visual cue response are unknown. This study aimed to examine brain activity in response to visual cues in people with PD who do (PD+FOG) and do not report FOG (PD-FOG) and explore relationships between attention, brain activity and gait. Methods. Mobile EEG measured brain activity during gait in 20 healthy older adults and 43 PD participants (n=22 PD+FOG, n=21 PD-FOG). Participants walked for 2-minutes with and without visual cues (transverse lines to step over). We report power spectral density (PSD) in Delta (1-4 Hz), Theta (4-7 Hz), Alpha (8-12 Hz), Beta (14-24 Hz) and Gamma (30-50 Hz) bands within clusters of similarly brain localized independent component sources. Results. PSDs within the parietal and occipital lobes were altered when walking with visual cues in PD, particularly in PD+FOG. Between group, differences suggested that parietal sources in PD, particularly with PD+FOG, had larger activity compared to healthy older adults when walking. Within group, visual cues altered brain activity in PD, particularly in PD+FOG, within visual processing brain regions. In PD participants, brain activity differences with cues correlated with gait improvements, and in PD+FOG those with worse attention required more visual attentional processing (reduced alpha PSD) in the occipital lobe. Conclusions. Visual cues improve gait and influence brain activity during walking in PD, particularly in PD+FOG. Findings may allow development of more effective therapeutics.

Graph-theoretical analysis of EEG functional connectivity during balance perturbation in traumatic brain injury: A pilot study

Traumatic brain injury (TBI) often results in balance impairment, increasing the risk of falls, and the chances of further injuries. However, the underlying neural mechanisms of postural control after TBI are not well understood. To this end, we conducted a pilot study to explore the neural mechanisms of unpredictable balance perturbations in 17 chronic TBI participants and 15 matched healthy controls (HC) using the EEG, MRI, and diffusion tensor imaging (DTI) data. As quantitative measures of the functional integration and segregation of the brain networks during the postural task, we computed the global graph-theoretic network measures (global efficiency and modularity) of brain functional connectivity derived from source-space EEG in different frequency bands. We observed that the TBI group showed a lower balance performance as measured by the center of pressure displacement during the task, and the Berg Balance Scale (BBS). They also showed reduced brain activation and connectivity during the balance task. Furthermore, the decrease in brain network segregation in alpha-band from baseline to task was smaller in TBI than HC. The DTI findings revealed widespread structural damage. In terms of the neural correlates, we observed a distinct role played by different frequency bands: theta-band modularity during the task was negatively correlated with the BBS in the TBI group; lower beta-band network connectivity was associated with the reduction in white matter structural integrity. Our future studies will focus on how postural training will modulate the functional brain networks in TBI.

Visual Effect on Brain Connectome That Scales Feedforward and Feedback Processes of Aged Postural System During Unstable Stance

Older adults with degenerative declines in sensory systems depend strongly on visual input for postural control. By connecting advanced neural imaging and a postural control model, this study investigated the visual effect on the brain functional network that regulates feedback and feedforward processes of the postural system in older adults under somatosensory perturbations. Thirty-six older adults conducted bilateral stance on a foam surface in the eyes-open (EO) and eyes-closed (EC) conditions while their center of pressure (COP) and scalp EEG were recorded. The stochastic COP trajectory was modeled with non-linear stabilogram diffusion analysis (SDA) to characterize shifts in postural control in a continuum of feedback and feedforward processes. The EEG network was analyzed with the phase-lag index (PLI) and minimum spanning tree (MST). The results indicated that visual input rebalanced feedforward and feedback processes for postural sway, resulting in a greater critical point of displacement (CD), short-term effective diffusion coefficients (D_s) and short-term exponent (H_s), but the smaller critical point of time (CT) and long-term exponent (H_l) for the EC state. The EC network demonstrated stronger frontoparietal-occipital connectivity but weaker fronto-tempo-motor connectivity of the theta (4–7 Hz), alpha (8–12 Hz), and beta (13–35 Hz) bands than did the EO network. MST analysis revealed generally greater leaf fraction and maximal betweenness centrality (BC_max) and kappa of the EC network, as compared with those of the EO network. In contrast, the EC network exhibited a smaller diameter and average eccentricity than those of the EO network. The modulation of long-term negative feedback gain of the aged postural system with visual occlusion was positively correlated with leaf fraction, BC_max, and kappa, but negatively correlated with the diameter and average eccentricity for all EEG sub-bands. In conclusion, the aged brain functional network in older adults is tuned to visual information for modulating long-term negative feedback of the postural system under somatosensory perturbations.

Effect of Multisession Progressive Gait-Slip Training on Fall-Resisting Skills of People with Chronic Stroke: Examining Motor Adaptation in Reactive Stability

Background: This study examined whether a multisession gait-slip training could enhance reactive balance control and fall-resisting skills of people with chronic stroke (PwCS). Methods: A total of 11 PwCS underwent a four-week treadmill-based gait-slip training (four sessions). Pre- and post-training assessment was performed on six intensities of gait-slips (levels 1–6). Training consisted of 10 blocks of each progressively increasing intensity (four trials per block) until participants fell at >2 trials per block (fall threshold). In the next session, training began at a sub-fall threshold and progressed further. Fall outcome and threshold, number of compensatory steps, multiple stepping threshold, progression to higher intensities, pre- and post-slip center of mass (CoM), state stability, clinical measures, and treadmill walking speed were analyzed. Results: Post-training, PwCS demonstrated a reduction in falls and compensatory steps on levels 5 and 6 (p < 0.05) compared to pre-training. While an increase in pre-slip stability was limited to level 6 (p < 0.05), improvement in post-slip stability at lift-off was noted on levels 2, 3, and 5 (p < 0.05) along with improved post-slip minimum stability on levels 5 and 6 (p < 0.05). Post-training demonstrated improved fall (p < 0.05) and multiple stepping thresholds (p = 0.05). While most participants could progress to level 4 between the first and last training sessions, more participants progressed to level 6 (p < 0.05). Participants’ treadmill walking speed increased (p < 0.05); however, clinical measures remained unchanged (p > 0.05). Conclusions: Multisession, progressively increasing intensity of treadmill-based gait-slip training appears to induce significant adaptive improvement in falls, compensatory stepping, and postural stability among PwCS.

Internal Consistency of Sway Measures via Embedded Head-Mounted Accelerometers: Implications for Neuromotor Investigations

Accelerometers are being increasingly incorporated into neuroimaging devices to enable real-time filtering of movement artifacts. In this study, we evaluate the reliability of sway metrics derived from these accelerometers in a standard eyes-open balance assessment to determine their utility in multimodal study designs. Ten participants equipped with a head-mounted accelerometer performed an eyes-open standing condition on 7 consecutive days. Sway performance was quantified with 4 standard metrics: root-mean-square (RMS) acceleration, peak-to-peak (P2P) acceleration, jerk, and ellipse area. Intraclass correlation coefficients (ICC) quantified reliability. P2P in both the mediolateral (ICC = 0.65) and anteroposterior (ICC = 0.67) planes yielded the poorest reliability. Both ellipse area and RMS exhibited good reliability, ranging from 0.76 to 0.84 depending on the plane. Finally, jerk displayed the highest reliability with an ICC value of 0.95. Moderate to excellent reliability was observed in all sway metrics. These findings demonstrate that head-mounted accelerometers, commonly found in neuroimaging devices, can be used to reliably assess sway. These data validate the use of head-mounted accelerometers in the assessment of motor control alongside other measures of brain activity such as electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS).

Long-Lasting Event-Related Beta Synchronizations of Electroencephalographic Activity in Response to Support-Surface Perturbations During Upright Stance: A Pilot Study Associating Beta Rebound and Active Monitoring in the Intermittent Postural Control

Movement related beta band cortical oscillations, including beta rebound after execution and/or suppression of movement, have drawn attention in upper extremity motor control literature. However, fewer studies focused on beta band oscillations during postural control in upright stance. In this preliminary study, we examined beta rebound and other components of electroencephalogram (EEG) activity during perturbed upright stance to investigate supraspinal contributions to postural stabilization. Particularly, we aimed to clarify the timing and duration of beta rebound within a non-sustained, but long-lasting postural recovery process that occurs more slowly compared to upper extremities. To this end, EEG signals were acquired from nine healthy young adults in response to a brief support-surface perturbation, together with the center of pressure, the center of mass and electromyogram (EMG) activities of ankle muscles. Event-related potentials (ERPs) and event-related spectral perturbations were computed from EEG data using the perturbation-onset as a triggering event. After short-latency (<0.3 s) ERPs, our results showed a decrease in high-beta band oscillations (event-related desynchronization), which was followed by a significant increase (event-related synchronization) in the same band, as well as a decrease in theta band oscillations. Unlike during upper extremity motor tasks, the beta rebound in this case was initiated before the postural recovery was completed, and sustained for as long as 3 s with small EMG responses for the first half period, followed by no excessive EMG activities for the second half period. We speculate that those novel characteristics of beta rebound might be caused by slow postural dynamics along a stable manifold of the unstable saddle-type upright equilibrium of the postural control system without active feedback control, but with active monitoring of the postural state, in the framework of the intermittent control.

Behavioral and Neural Variability of Naturalistic Arm Movements

Motor behaviors are central to many functions and dysfunctions of the brain, and understanding their neural basis has consequently been a major focus in neuroscience. However, most studies of motor behaviors have been restricted to artificial, repetitive paradigms, far removed from natural movements performed "in the wild." Here, we leveraged recent advances in machine learning and computer vision to analyze intracranial recordings from 12 human subjects during thousands of spontaneous, unstructured arm reach movements, observed over several days for each subject. These naturalistic movements elicited cortical spectral power patterns consistent with findings from controlled paradigms, but with considerable neural variability across subjects and events. We modeled interevent variability using 10 behavioral and environmental features; the most important features explaining this variability were reach angle and day of recording. Our work is among the first studies connecting behavioral and neural variability across cortex in humans during unstructured movements and contributes to our understanding of long-term naturalistic behavior.

A Model-Based Analysis of Supraspinal Mechanisms of Inter-Leg Coordination in Human Gait: Toward Model-Informed Robot-Assisted Rehabilitation

Stroke survivors are often left suffering from gait instability due to hemiparesis. This gait dysfunction can lead to higher fall rates and an overall decrease in quality of life. Though there are many post-stroke gait rehabilitation methods in use currently, none of them allow patients to regain complete functionality. Interlimb coordination is one of the main mechanisms of walking and is usually overlooked in most post-stroke gait rehabilitation protocols. This work attempts to help further understand the mechanism of interlimb coordination and how the brain is involved in it, studying the contralateral response to unilateral stiffness perturbations. A unique robotic device, the Variable Stiffness Treadmill (VST), is used in conjunction with a pre-established neuromuscular gait model to analyze for the first time the supraspinal control mechanisms involved in inter-leg coordination induced after unilateral perturbations. The attempt to explain the observed kinematic and muscular activation data via the gait model results in the identification of two control variables that seem to play an important role in gait stability and recovery after perturbations: the target angle of attack and target hip to ankle span. This is significant because these two parameters are directly related to longer stride length and larger foot clearance during swing phase. Both variables work toward correcting common issues with hemiparetic gait, such as a shorter stride and toe drag during swing phase of the paretic leg. The results of this work could aid in the design of future model-based stroke rehabilitation methods that would perturb the subject in a systematic way and allow targeted interventions with specific functional outcomes on gait. Additionally, this work-along with future studies-could assist in improving controllers for robust bipedal robots as well as our understanding of how the brain controls balance during perturbed walking.

Mobile brain/body imaging of landmark-based navigation with high-density EEG

Coupling behavioral measures and brain imaging in naturalistic, ecological conditions is key to comprehend the neural bases of spatial navigation. This highly integrative function encompasses sensorimotor, cognitive, and executive processes that jointly mediate active exploration and spatial learning. However, most neuroimaging approaches in humans are based on static, motion‐constrained paradigms and they do not account for all these processes, in particular multisensory integration. Following the Mobile Brain/Body Imaging approach, we aimed to explore the cortical correlates of landmark‐based navigation in actively behaving young adults, solving a Y‐maze task in immersive virtual reality. EEG analysis identified a set of brain areas matching state‐of‐the‐art brain imaging literature of landmark‐based navigation. Spatial behavior in mobile conditions additionally involved sensorimotor areas related to motor execution and proprioception usually overlooked in static fMRI paradigms. Expectedly, we located a cortical source in or near the posterior cingulate, in line with the engagement of the retrosplenial complex in spatial reorientation. Consistent with its role in visuo‐spatial processing and coding, we observed an alpha‐power desynchronization while participants gathered visual information. We also hypothesized behavior‐dependent modulations of the cortical signal during navigation. Despite finding few differences between the encoding and retrieval phases of the task, we identified transient time–frequency patterns attributed, for instance, to attentional demand, as reflected in the alpha/gamma range, or memory workload in the delta/theta range. We confirmed that combining mobile high‐density EEG and biometric measures can help unravel the brain structures and the neural modulations subtending ecological landmark‐based navigation.

Integrated 3D motion analysis with functional magnetic resonance neuroimaging to identify neural correlates of lower extremity movement

BACKGROUND

To better understand the neural drivers of aberrant motor control, methods are needed to identify whole brain neural correlates of isolated joints during multi-joint lower-extremity coordinated movements. This investigation aimed to identify the neural correlates of knee kinematics during a unilateral leg press task.

NEW METHOD

The current study utilized an MRI-compatible motion capture system in conjunction with a lower extremity unilateral leg press task during fMRI. Knee joint kinematics and brain activity were collected concurrently and averaged range of motion were modeled as covariates to determine the neural substrates of knee out-of-plane (frontal) and in-plane (sagittal) range of motion.

RESULTS

Increased out-of-plane (frontal) range of motion was associated with altered brain activity in regions important for attention, sensorimotor control, and sensorimotor integration (z >3.1, p < .05), but no such correlates were found with in-plane (sagittal) range of motion (z >3.1, p > .05). Comparison with Existing Method(s): Previous studies have either presented overall brain activation only, or utilized biomechanical data collected outside MRI in a standard biomechanics lab for identifying single-joint neural correlates.

CONCLUSIONS

The study shows promise for the MRI-compatible system to capture lower-extremity biomechanical data collected concurrently during fMRI, and the present data identified potentially unique neural drivers of aberrant biomechanics. Future research can adopt these methods for patient populations with CNS-related movement disorders to identify single-joint kinematic neural correlates that may adjunctively supplement brain-body therapeutic approaches.

Stance leg and surface stability modulate cortical activity during human single leg stance

Mobile Electroencephalography (EEG) provides insights into cortical contributions to postural control. Although changes in theta (4–8 Hz) and alpha frequency power (8–12 Hz) were shown to reflect attentional and sensorimotor processing during balance tasks, information about the effect of stance leg on cortical processing related to postural control is lacking. Therefore, the aim was to examine patterns of cortical activity during single-leg stance with varying surface stability. EEG and force plate data from 21 healthy males (22.43 ± 2.23 years) was recorded during unipedal stance (left/right) on a stable and unstable surface. Using source-space analysis, power spectral density was analyzed in the theta, alpha-1 (8–10 Hz) and alpha-2 (10–12 Hz) frequency bands. Repeated measures ANOVA with the factors leg and surface stability revealed significant interaction effects in the left (p = 0.045, η_p² = 0.13) and right motor clusters (F = 16.156; p = 0.001, η_p² = 0.41). Furthermore, significant main effects for surface stability were observed for the fronto-central cluster (theta), left and right motor (alpha-1), as well as for the right parieto-occipital cluster (alpha-1/alpha-2). Leg dependent changes in alpha-2 power may indicate lateralized patterns of cortical processing in motor areas during single-leg stance. Future studies may therefore consider lateralized patterns of cortical activity for the interpretation of postural deficiencies in unilateral lower limb injuries.

Differential Theta-Band Signatures of the Anterior Cingulate and Motor Cortices During Seated Locomotor Perturbations

Quantifying motor and cortical responses to perturbations during seated locomotor tasks such as recumbent stepping and cycling will expand and improve the understanding of locomotor adaptation processes beyond just perturbed gait. Using a perturbed recumbent stepping protocol, we hypothesized motor errors and anterior cingulate activity would decrease with time, and perturbation timing would influence electrocortical elicitation. Young adults (n = 17) completed four 10-minute arms and legs stepping tasks, with perturbations applied at every left or right leg extension-onset or mid-extension. A random no-perturbation "catch" stride occurred in every five perturbed strides. We instructed subjects to follow a pacing cue and to step smoothly, and we quantified temporal and spatial motor errors. We used high-density electroencephalography to estimate sources of electrocortical fluctuations shared among >70% of subjects. Temporal and spatial errors did not decrease from early to late for either perturbed or catch strides. Interestingly, spatial errors post-perturbation did not return to pre-perturbation levels, suggesting use-dependent learning occurred. Theta (3-8 Hz) synchronization in the anterior cingulate cortex and left and right supplementary motor areas (SMA) emerged near the perturbation event, and extension-onset perturbations elicited greater theta-band power than mid-extension perturbations. Even though motor errors did not adapt, anterior cingulate theta synchronization decreased from early to late perturbed strides, but only during the right-side tasks. Additionally, SMA mainly demonstrated specialized, not contralateral, lateralization. Overall, seated locomotor perturbations produced differential theta-band responses in the anterior cingulate and SMAs, suggesting that tuning perturbation parameters, e.g., timing, can potentially modify electrocortical responses.

Reliance on Visual Input for Balance Skill Transfer in Older Adults: EEG Connectome Analysis Using Minimal Spanning Tree

Skill transfer from trained balance exercises is critical to reduce the rate of falls in older adults, who rely more on vision to control postural responses due to age-dependent sensory reweighting. With an electroencephalography (EEG) minimum spanning tree (MST) structure, the purpose of this study was to compare the organization of supraspinal neural networks of transfer effect after postural training using full and intermittent visual feedbacks for older adults. Thirty-two older adults were randomly assigned to the stroboscopic vision (SV) (n = 16; age = 64.7 ± 3.0 years) and control (16; 66.3 ± 2.7 years) groups for balance training on a stabilometer (target task) with on-line visual feedback. Center-of-pressure characteristics and an MST-based connectome of the weighted phase-lag index during the bilateral stance on a foam surface (transfer task) were compared before and after stabilometer training. The results showed that both the SV and control groups showed improvements in postural stability in the trained task (p < 0.001). However, unlike the control group (p = 0.030), the SV group who received intermittent visual feedback during the stabilometer training failed to reduce the size of postural sway in the anteroposterior direction of the postural transfer task (unstable stance on the foam surface) in the post-test (p = 0.694). In addition, network integration for the transfer task in the post-test was absent in the SV group (p > 0.05). For the control group in the post-test, it manifested with training-related increases in leaf fraction in beta band (p = 0.015) and maximum betweenness in alpha band (p = 0.018), but a smaller diameter in alpha (p = 0.006)/beta (p = 0.021) bands and average eccentricity in alpha band (p = 0.028). In conclusion, stabilometer training with stroboscopic vision impairs generalization of postural skill to unstable stance for older adults. Adequate visual information is a key mediating factor of supraspinal neural networks to carry over balance skill in older adults.

Generalized neural decoders for transfer learning across participants and recording modalities

OBJECTIVE

Advances in neural decoding have enabled brain-computer interfaces to perform increasingly complex and clinically-relevant tasks. However, such decoders are often tailored to specific participants, days, and recording sites, limiting their practical long-term usage. Therefore, a fundamental challenge is to develop neural decoders that can robustly train on pooled, multi-participant data and generalize to new participants.

APPROACH

We introduce a new decoder, HTNet, which uses a convolutional neural network with two innovations: (1) a Hilbert transform that computes spectral power at data-driven frequencies and (2) a layer that projects electrode-level data onto predefined brain regions. The projection layer critically enables applications with intracranial electrocorticography (ECoG), where electrode locations are not standardized and vary widely across participants. We trained HTNet to decode arm movements using pooled ECoG data from 11 of 12 participants and tested performance on unseen ECoG or electroencephalography (EEG) participants; these pretrained models were also subsequently fine-tuned to each test participant.

MAIN RESULTS

HTNet outperformed state-of-the-art decoders when tested on unseen participants, even when a different recording modality was used. By fine-tuning these generalized HTNet decoders, we achieved performance approaching the best tailored decoders with as few as 50 ECoG or 20 EEG events. We were also able to interpret HTNet's trained weights and demonstrate its ability to extract physiologically-relevant features.

SIGNIFICANCE

By generalizing to new participants and recording modalities, robustly handling variations in electrode placement, and allowing participant-specific fine-tuning with minimal data, HTNet is applicable across a broader range of neural decoding applications compared to current state-of-the-art decoders.

Chronic jaw pain attenuates neural oscillations during motor-evoked pain

Motor- and pain-related processes separately induce a reduction in alpha and beta power. When movement and pain occur simultaneously but are independent of each other, the effects on alpha and beta power are additive. It is not clear whether this additive effect is evident during motor-evoked pain in individuals with chronic pain. We combined highdensity electroencephalography (EEG) with a paradigm in which motor-evoked pain was induced during a jaw force task. Participants with chronic jaw pain and pain-free controls produced jaw force at 2% and 15% of their maximum voluntary contraction. The chronic jaw pain group showed exacerbated motor-evoked pain as force amplitude increased and showed increased motor variability and motor error irrespective of force amplitude. The chronic jaw pain group had an attenuated decrease in power in alpha and lower-beta frequencies in the occipital cortex during the anticipation and experience of motor-evoked pain. Rather than being additive, motor-evoked pain attenuated the modulation of alpha and beta power, and this was most evident in occipital cortex. Our findings provide the first evidence of changes in neural oscillations in the cortex during motor-evoked jaw pain.

A Novel Method to Understand Neural Oscillations During Full-Body Reaching: A Combined EEG and 3D Virtual Reality Study

Virtual reality (VR) can be used to create environments that are not possible in the real-world. Producing movements in VR holds enormous promise for rehabilitation and offers a platform from which to understand the neural control of movement. However, no study has examined the impact of a 3D fully immersive head-mounted display (HMD) VR system on the integrity of neural data. We assessed the quality of 64-channel EEG data with and without HMD VR during rest and during a full-body reaching task. We compared resting EEG while subjects completed three conditions: No HMD (EEG-only), HMD powered off (VR-off), and HMD powered on (VR-on). Within the same session, EEG were collected while subjects completed full-body reaching movements in two conditions (EEG-only, VR-on). During rest, no significant differences in data quality and power spectrum were observed between EEG-only, VR-off, and VR-on conditions. During reaching movements, the proportion of components attributed to the brain was greater in the EEG-only condition compared to the VR-on condition. Despite this difference, neural oscillations in source space were not significantly different between conditions, with both conditions associated with decreases in alpha and beta power in sensorimotor cortex during movements. Our findings demonstrate that the integrity of EEG data can be maintained while individuals execute full-body reaching movements within an immersive 3D VR environment. Clinical impact: Integrating VR and EEG is a viable approach to understanding the cortical processes of movement. Simultaneously recording movement and brain activity in combination with VR provides the foundation for neurobiologically informed rehabilitation therapies.

Cortical Beta Oscillatory Activity Evoked during Reactive Balance Recovery Scales with Perturbation Difficulty and Individual Balance Ability

Cortical beta oscillations (13-30 Hz) reflect sensorimotor processing, but are not well understood in balance recovery. We hypothesized that sensorimotor cortical activity would increase under challenging balance conditions. We predicted greater beta power when balance was challenged, either by more difficult perturbations or by lower balance ability. In 19 young adults, we measured beta power over motor cortical areas (electroencephalography, Cz electrode) during three magnitudes of backward support -surface translations. Peak beta power was measured during early (50-150 ms), late (150-250 ms), and overall (0-400 ms) time bins, and wavelet-based analyses quantified the time course of evoked beta power. An ANOVA was used to compare peak beta power across perturbation magnitudes in each time bin. We further tested the association between perturbation-evoked beta power and individual balance ability measured in a challenging beam walking task. Beta power increased ~50 ms after perturbation, and to a greater extent in larger perturbations. Lower individual balance ability was associated with greater beta power in only the late (150-250 ms) time bin. These findings demonstrate greater sensorimotor cortical engagement under more challenging balance conditions, which may provide a biomarker for reduced automaticity in balance control that could be used in populations with neurological impairments.

Cortical dynamics of movement-evoked pain in chronic low back pain

KEY POINTS

Cortical activity underlying movement-evoked pain is not well understood, despite being a key symptom of chronic musculoskeletal pain. We combined high-density electroencephalography with a full-body reaching protocol in a virtual reality environment to assess cortical activity during movement-evoked pain in chronic low back pain. Movement-evoked pain in individuals with chronic low back pain was associated with longer reaction times, delayed peak velocity and greater movement variability. Movement-evoked pain was associated with attenuated disinhibition in prefrontal motor areas, as evidenced by an attenuated reduction in beta power in the premotor cortex and supplementary motor area.

ABSTRACT

Although experimental pain alters neural activity in the cortex, evidence of changes in neural activity in individuals with chronic low back pain (cLBP) remains scarce and results are inconsistent. One of the challenges in studying cLBP is that the clinical pain fluctuates over time and often changes during movement. The goal of the present study was to address this challenge by recording high-density electroencephalography (HD-EEG) data during a full-body reaching task to understand neural activity during movement-evoked pain. HD-EEG data were analysed using independent component analyses, source localization and measure projection analyses to compare neural oscillations between individuals with cLBP who experienced movement-evoked pain and pain-free controls. We report two novel findings. First, movement-evoked pain in individuals with cLBP was associated with longer reaction times, delayed peak velocity and greater movement variability. Second, movement-evoked pain was associated with an attenuated reduction in beta power in the premotor cortex and supplementary motor area. Our observations move the field forward by revealing attenuated disinhibition in prefrontal motor areas during movement-evoked pain in cLBP.

Aging-related changes in cortical mechanisms supporting postural control during base of support and optic flow manipulations

Behavioral findings suggest that aging alters the involvement of cortical sensorimotor mechanisms in postural control. However, corresponding accounts of the underlying neural mechanisms remain sparse, especially the extent to which these mechanisms are affected during more demanding tasks. Here, we set out to elucidate cortical correlates of altered postural stability in younger and older adults. 3D body motion tracking and high-density electroencephalography (EEG) were measured while 14 young adults (mean age = 24 years, 43% women) and 14 older adults (mean age = 77 years, 50% women) performed a continuous balance task under four different conditions. Manipulations were applied to the base of support (either regular or tandem (heel-to-toe) stance) and visual input (either static visual field or dynamic optic flow). Standing in tandem, the more challenging position, resulted in increased sway for both age groups, but for the older adults, only this effect was exacerbated when combined with optic flow compared to the static visual display. These changes in stability were accompanied by neuro-oscillatory modulations localized to midfrontal and parietal regions. A cluster of electro-cortical sources localized to the supplementary motor area showed a large increase in theta spectral power (4-7 Hz) during tandem stance, and this modulation was much more pronounced for the younger group. Additionally, the older group displayed widespread mu (8-12 Hz) and beta (13-30 Hz) suppression as balance tasks placed more demands on postural control, especially during tandem stance. These findings may have substantial utility in identifying early cortical correlates of balance impairments in otherwise healthy older adults.

Classification of Rhythmic Cortical Activity Elicited by Whole-Body Balance Perturbations Suggests the Cortical Representation of Direction-Specific Changes in Postural Stability

Postural responses that effectively recover balance following unexpected postural changes need to be tailored to the characteristics of the postural change. We hypothesized that cortical dynamics involved in top-down regulation of postural responses carry information about directional postural changes (i.e., sway) imposed by sudden perturbations to standing balance (i.e., support surface translations). To test our hypothesis, we evaluated the single-trial classification of perturbation-induced directional changes in postural stability from high-density EEG. We analyzed EEG recordings from six young able-bodied individuals and three older individuals with chronic hemiparetic stroke, which were acquired while individuals reacted to low-intensity balance perturbations. Using common spatial patterns for feature extraction and linear discriminant analysis or support vector machines for classification, we achieved classification accuracies above random level (p < 0.05; cross-validated) for the classification of four different sway directions (one vs. the rest scheme). Screening of spectral features (3-50 Hz) revealed that the highest classification performance occurred when low-frequency (3-10 Hz) spectral features were used. Strikingly, the participant-specific classification results were qualitatively similar between young able-bodied individuals and older individuals with chronic hemiparetic stroke. Our findings demonstrate that low-frequency spectral components, corresponding to the cortical theta rhythm, carry direction-specific information about changes in postural stability. Our work presents a new perspective on the cortical representation of postural stability and the possible role of the theta rhythm in the modulation of (directional) reactive balance responses. Importantly, our work provides preliminary evidence that the cortical encoding of direction-specific changes in postural stability is present in chronic hemiparetic stroke.

Cortical responses to whole-body balance perturbations index perturbation magnitude and predict reactive stepping behavior

The goal of this study was to determine whether the cortical responses elicited by whole‐body balance perturbations were similar to established cortical markers of action monitoring. Postural changes imposed by balance perturbations elicit a robust negative potential (N1) and a brisk increase of theta activity in the electroencephalogram recorded over midfrontal scalp areas. Because action monitoring is a cognitive function proposed to detect errors and initiate corrective adjustments, we hypothesized that the possible cortical markers of action monitoring during balance control (N1 potential and theta rhythm) scale with perturbation intensity and the eventual execution of reactive stepping responses (as opposed to feet‐in‐place responses). We recorded high‐density electroencephalogram from eleven young individuals, who participated in an experimental balance assessment. The participants were asked to recover balance following anteroposterior translations of the support surface at various intensities, while attempting to maintain both feet in place. We estimated source‐resolved cortical activity using independent component analysis. Combining time‐frequency decomposition and group‐level general linear modeling of single‐trial responses, we found a significant relation of the interaction between perturbation intensity and stepping responses with multiple cortical features from the midfrontal cortex, including the N1 potential, and theta, alpha, and beta rhythms. Our findings suggest that the cortical responses to balance perturbations index the magnitude of a deviation from a stable postural state to predict the need for reactive stepping responses. We propose that the cortical control of balance may involve cognitive control mechanisms (i.e., action monitoring) that facilitate postural adjustments to maintain postural stability.

Alteration of brain dynamics during dual-task overground walking

When walking in our natural environment, we often solve additional cognitive tasks. This increases the demand of resources needed for both the cognitive and motor systems, resulting in Cognitive-Motor Interference (CMI). A large portion of neurophysiological investigations on CMI took place in static settings, emphasizing the experimental rigor but overshadowing the ecological validity. As a more ecologically valid alternative to treadmill and desktop-based setups to investigate CMI, we developed a dual-task walking scenario in virtual reality (VR) combined with Mobile Brain/Body Imaging (MoBI). We aimed at investigating how brain dynamics are modulated by dual-task overground walking with an additional task in the visual domain. Participants performed a visual discrimination task in VR while standing (single-task) and walking overground (dual-task). Even though walking had no impact on the performance in the visual discrimination task, a P3 amplitude reduction along with changes in power spectral densities (PSDs) were observed for discriminating visual stimuli during dual-task walking. These results reflect an impact of walking on the parallel processing of visual stimuli even when the cognitive task is particularly easy. This standardized and easy to modify VR paradigm helps to systematically study CMI, allowing researchers to control for the impact of additional task complexity of tasks in different sensory modalities. Future investigations implementing an improved virtual design with more challenging cognitive and motor tasks will have to investigate the roles of both cognition and motion, allowing for a better understanding of the functional architecture of attention reallocation between cognitive and motor systems during active behavior.

Motion and Muscle Artifact Removal Validation Using an Electrical Head Phantom, Robotic Motion Platform, and Dual Layer Mobile EEG

Motion and muscle artifacts can undermine signal quality in electroencephalography (EEG) recordings during locomotion. We evaluated approaches for recovering ground-truth artificial brain signals from noisy EEG recordings. We built an electrical head phantom that broadcast four brain and four muscle sources. Head movements were generated by a robotic motion platform. We recorded 128-channel dual layer EEG and 8-channel neck electromyography (EMG) from the head phantom during motion. We evaluated ground-truth electrocortical source signal recovery from artifact contaminated data using Independent Component Analysis (ICA) to determine: (1) the number of isolated noise sensor recordings needed to capture and remove motion artifacts, (2) the ability of Artifact Subspace Reconstruction to remove motion and muscle artifacts at contrasting artifact detection thresholds, (3) the number of neck EMG sensor recordings needed to capture and remove muscle artifacts, and (4) the ability of Canonical Correlation Analysis to remove muscle artifacts. We also evaluated source signal recovery by combining the best practices identified in aims 1-4. By including isolated noise and EMG recordings in the ICA decomposition, we more effectively recovered ground-truth artificial brain signals. A reduced subset of 32-noise and 6-EMG channels showed equivalent performance compared to including the complete arrays. Artifact Subspace Reconstruction improved source separation, but this was contingent on muscle activity amplitude. Canonical Correlation Analysis also improved source separation. Merging noise and EMG recordings into the ICA decomposition, with Artifact Subspace Reconstruction and Canonical Correlation Analysis preprocessing, improved source signal recovery. This study expands on previous head phantom experiments by including neck muscle source activity and evaluating artificial electrocortical spectral power fluctuations synchronized with gait events.

Worse balance is associated with larger perturbation-evoked cortical responses in healthy young adults

BACKGROUND

Reactive balance recovery evokes a negative peak of cortical electroencephalography (EEG) activity (N1) that is simultaneous to brainstem-mediated automatic balance-correcting muscle activity. This study follows up on an observation from a previous study, in which N1 responses were larger in individuals who seemed to have greater difficulty responding to support-surface perturbations.

RESEARCH QUESTION

We hypothesized that people engage more cortical activity when balance recovery is more challenging. We predicted that people with lower balance ability would exhibit larger cortical N1 responses during balance perturbations.

METHODS

In 20 healthy young adults (11 female, ages 19-38) we measured the amplitude of the cortical N1 response evoked by 48 backward translational support-surface perturbations of unpredictable timing and amplitude. Perturbations included a Small (8 cm) perturbation that was identical across participants, as well as Medium (13-15 cm) and Large (18-22 cm) perturbations scaled to participant height to control for height-related differences in perturbation difficulty. To assess individual differences in balance ability, we measured the distance traversed on a narrow (0.5-inch wide) 12-foot beam across 6 trials. We tested whether the cortical N1 response amplitude was correlated to balance ability across participants.

RESULTS

Cortical N1 amplitudes in response to standing balance perturbations (54 ± 18 μV) were inversely correlated to the distance traveled in the difficult beam-walking task (R² = 0.20, p = 0.029). Further, there was a significant interaction between performance on the beam-walking task and the effect of perturbation magnitude on the cortical N1 response amplitude, whereby individuals who performed worse on the beam-walking task had greater increases in N1 amplitudes with increases in perturbation magnitude.

SIGNIFICANCE

Cortical N1 response amplitudes may reflect greater cortical involvement in balance recovery when challenged. This increased cortical involvement may reflect cognitive processes such as greater perceived threat or attention to balance, which have the potential to influence subsequent motor control.

Gait-phase-dependent and gait-phase-independent cortical activity across multiple regions involved in voluntary gait modifications in humans

Modification of ongoing walking movement to fit changes in external environments requires accurate voluntary control. In cats, the motor and posterior parietal cortices have crucial roles for precisely adjusting limb trajectory during walking. In human walking, however, it remains unclear which cortical information contributes to voluntary gait modification. In this study, we investigated cortical activity changes associated with visually guided precision stepping using electroencephalography source analysis. Our results demonstrated frequency- and gait-event-dependent changes in the cortical power spectrum elicited by voluntary gait modification. The main differences between normal walking and precision stepping were as follows: (a) the alpha, beta or gamma power decrease during the swing phases in the sensorimotor, anterior cingulate and parieto-occipital cortices, and (b) a power decrease in the theta, alpha and beta bands and increase in the gamma band throughout the gait cycle in the parieto-occipital cortex. Based on the previous knowledge of brain functions, the former change was considered to be related to execution and planning of leg movement, while the latter change was considered to be related to multisensory integration and motor awareness. Therefore, our results suggest that the gait modification is achieved by higher cortical involvements associated with different sensorimotor-related functions across multiple cortical regions including the sensorimotor, anterior cingulate and parieto-occipital cortices. The results imply the critical importance of the cortical contribution to voluntary modification in human locomotion. Further, the observed cortical information related to voluntary gait modification would contribute to developing volitional control systems of brain-machine interfaces for walking rehabilitation.

New Directions in Exercise Prescription: Is There a Role for Brain-Derived Parameters Obtained by Functional Near-Infrared Spectroscopy?

In the literature, it is well established that regular physical exercise is a powerful strategy to promote brain health and to improve cognitive performance. However, exact knowledge about which exercise prescription would be optimal in the setting of exercise–cognition science is lacking. While there is a strong theoretical rationale for using indicators of internal load (e.g., heart rate) in exercise prescription, the most suitable parameters have yet to be determined. In this perspective article, we discuss the role of brain-derived parameters (e.g., brain activity) as valuable indicators of internal load which can be beneficial for individualizing the exercise prescription in exercise–cognition research. Therefore, we focus on the application of functional near-infrared spectroscopy (fNIRS), since this neuroimaging modality provides specific advantages, making it well suited for monitoring cortical hemodynamics as a proxy of brain activity during physical exercise.

Balance task difficulty affects postural sway and cortical activity in healthy adolescents

Electroencephalographic (EEG) research indicates changes in adults’ low frequency bands of frontoparietal brain areas executing different balance tasks with increasing postural demands. However, this issue is unsolved for adolescents when performing the same balance task with increasing difficulty. Therefore, we examined the effects of a progressively increasing balance task difficulty on balance performance and brain activity in adolescents. Thirteen healthy adolescents aged 16–17 year performed tests in bipedal upright stance on a balance board with six progressively increasing levels of task difficulty. Postural sway and cortical activity were recorded simultaneously using a pressure sensitive measuring system and EEG. The power spectrum was analyzed for theta (4–7 Hz) and alpha-2 (10–12 Hz) frequency bands in pre-defined frontal, central, and parietal clusters of electrocortical sources. Repeated measures analysis of variance (rmANOVA) showed a significant main effect of task difficulty for postural sway (p < 0.001; d = 6.36). Concomitantly, the power spectrum changed in frontal, bilateral central, and bilateral parietal clusters. RmANOVAs revealed significant main effects of task difficulty for theta band power in the frontal (p < 0.001, d = 1.80) and both central clusters (left: p < 0.001, d = 1.49; right: p < 0.001, d = 1.42) as well as for alpha-2 band power in both parietal clusters (left: p < 0.001, d = 1.39; right: p < 0.001, d = 1.05) and in the central right cluster (p = 0.005, d = 0.92). Increases in theta band power (frontal, central) and decreases in alpha-2 power (central, parietal) with increasing balance task difficulty may reflect increased attentional processes and/or error monitoring as well as increased sensory information processing due to increasing postural demands. In general, our findings are mostly in agreement with studies conducted in adults. Similar to adult studies, our data with adolescents indicated the involvement of frontoparietal brain areas in the regulation of postural control. In addition, we detected that activity of selected brain areas (e.g., bilateral central) changed with increasing postural demands.

Corticomuscular control of walking in older people and people with Parkinson's disease

Changes in human gait resulting from ageing or neurodegenerative diseases are multifactorial. Here we assess the effects of age and Parkinson’s disease (PD) on corticospinal activity recorded during treadmill and overground walking. Electroencephalography (EEG) from 10 electrodes and electromyography (EMG) from bilateral tibialis anterior muscles were acquired from 22 healthy young, 24 healthy older and 20 adults with PD. Event-related power, corticomuscular coherence (CMC) and inter-trial coherence were assessed for EEG from bilateral sensorimotor cortices and EMG during the double-support phase of the gait cycle. CMC and EMG power at low beta frequencies (13–21 Hz) was significantly decreased in older and PD participants compared to young people, but there was no difference between older and PD groups. Older and PD participants spent shorter time in the swing phase than young individuals. These findings indicate age-related changes in the temporal coordination of gait. The decrease in low-beta CMC suggests reduced cortical input to spinal motor neurons in older people during the double-support phase. We also observed multiple changes in electrophysiological measures at low-gamma frequencies during treadmill compared to overground walking, indicating task-dependent differences in corticospinal locomotor control. These findings may be affected by artefacts and should be interpreted with caution.

Modulations of Inter-Hemispherical Phase Coupling in Human Single Leg Stance

INTRODUCTION

Recent findings from neuroimaging studies provided initial insights into cortical contributions to postural control. These studies observed enhanced cortical activation and connectivity when task-difficulty and postural instability increased. However, little attention has been paid to the allocation of cortical networks appearing with a decreasing base of support from bipedal to single leg stance. Therefore, the aim of the present study was to investigate modulations of functional connectivity from bipedal to single leg stance.

EXPERIMENTAL PROCEDURES

Cortical activity during bipedal and single leg stance (left) was investigated in 15 male subjects using 128 channel mobile electroencephalography (EEG), while standing on a triaxial force plate. Power spectral density was calculated for theta (4-7 Hz), alpha-1 (8-10 Hz) and alpha-2 (10-12 Hz) frequency bands. Estimations of the phase lag index (PLI) were conducted as a measure of functional connectivity. Moreover, postural control was analyzed by the area of sway and sway velocity.

RESULTS

The results demonstrated a significantly increased area of sway and decreased alpha-2 power in single leg compared to bipedal stance. Furthermore, PLIs within the alpha-2 frequency band showed significantly decreased inter-hemispherical phase coupling in single leg stance, associated with connections involving the left motor region.

DISCUSSION

Altogether, the present findings may indicate modulations of cortical contributions in single leg compared to bipedal stance. The present data suggest that decreased inter-hemispherical functional connectivity, in conjunction with a global increase in cortical excitability, may indicate enhanced alertness and task-specific selective inhibition of motor networks in favor of postural control.

Pathway-specific modulatory effects of neuromuscular electrical stimulation during pedaling in chronic stroke survivors

Background

Neuromuscular electrical stimulation (NMES) is extensively used in stroke motor rehabilitation. How it promotes motor recovery remains only partially understood. NMES could change muscular properties, produce altered sensory inputs, and modulate fluctuations of cortical activities; but the potential contribution from cortico-muscular couplings during NMES synchronized with dynamic movement has rarely been discussed.

Method

We investigated cortico-muscular interactions during passive, active, and NMES rhythmic pedaling in healthy subjects and chronic stroke survivors. EEG (128 channels), EMG (4 unilateral lower limb muscles) and movement parameters were measured during 3 sessions of constant-speed pedaling. Sensory-level NMES (20 mA) was applied to the muscles, and cyclic stimulation patterns were synchronized with the EMG during pedaling cycles. Adaptive mixture independent component analysis was utilized to determine the movement-related electro-cortical sources and the source dipole clusters. A directed cortico-muscular coupling analysis was conducted between representative source clusters and the EMGs using generalized partial directed coherence (GPDC). The bidirectional GPDC was compared across muscles and pedaling sessions for post-stroke and healthy subjects.

Results

Directed cortico-muscular coupling of NMES cycling was more similar to that of active pedaling than to that of passive pedaling for the tested muscles. For healthy subjects, sensory-level NMES could modulate GPDC of both ascending and descending pathways. Whereas for stroke survivors, NMES could modulate GPDC of only the ascending pathways.

Conclusions

By clarifying how NMES influences neuromuscular control during pedaling in healthy and post-stroke subjects, our results indicate the potential limitation of sensory-level NMES in promoting sensorimotor recovery in chronic stroke survivors.

Cortical dynamics of sensorimotor information processing associated with balance control in adolescents with and without idiopathic scoliosis

OBJECTIVE

This study aims at examining the cortical dynamics of sensorimotor information processing related to balance control in participants with adolescent idiopathic scoliosis (AIS) and in age-matched controls (CTL).

METHODS

Cortical dynamics during standing balance control were assessed in 13 girls with AIS and 13 age-matched controls using electroencephalography. Time-frequency analysis were used to determine frequency power during ankle proprioception alteration (ankle tendons co-vibration interval) or reintegration of ankle proprioception (post-vibration interval) with or without vision.

RESULTS

Balance control did not differ between groups. In the co-vibration interval, a significant suppression in alpha (8-12 Hz) and beta (13-30 Hz) band power and a significant increase in theta (4-7 Hz) band power were found respectively in the vision and non-vision condition in the AIS group compared to the CTL group. In the post-vibration interval, significant suppressions in beta (13-30 Hz) and gamma (30-50 Hz) band power were observed in the AIS group in the non-vision condition.

CONCLUSION

Participants with AIS showed brain oscillations differences compared to CTL in the sensorimotor cortex while controlling their balance in various sensory conditions.

SIGNIFICANCE

Future study using evaluation of cortical dynamics could serve documenting whether rehabilitation programs have an effect on sensorimotor function in AIS.

EECoG-Comp: An Open Source Platform for Concurrent EEG/ECoG Comparisons-Applications to Connectivity Studies

Electrophysiological Source Imaging (ESI) is hampered by lack of "gold standards" for model validation. Concurrent electroencephalography (EEG) and electrocorticography (ECoG) experiments (EECoG) are useful for this purpose, especially primate models due to their flexibility and translational value for human research. Unfortunately, there is only one EECoG experiments in the public domain that we know of: the Multidimensional Recording (MDR) is based on a single monkey ( www.neurotycho.org ). The mining of this type of data is hindered by lack of specialized procedures to deal with: (1) Severe EECoG artifacts due to the experimental produces; (2) Sophisticated forward models that account for surgery induced skull defects and implanted ECoG electrode strips; (3) Reliable statistical procedures to estimate and compare source connectivity (partial correlation). We provide solutions to the processing issues just mentioned with EECoG-Comp: an open source platform ( https://github.com/Vincent-wq/EECoG-Comp ). EECoG lead fields calculated with FEM (Simbio) for MDR data are also provided and were used in other papers of this special issue. As a use case with the MDR, we show: (1) For real MDR data, 4 popular ESI methods (MNE, LCMV, eLORETA and SSBL) showed significant but moderate concordance with a usual standard, the ECoG Laplacian (standard partial [Formula: see text]); (2) In both monkey and human simulations, all ESI methods as well as Laplacian had a significant but poor correspondence with the true source connectivity. These preliminary results may stimulate the development of improved ESI connectivity estimators but require the availability of more EECoG data sets to obtain neurobiologically valid inferences.

Neuroergonomics Applications of Electroencephalography in Physical Activities: A Systematic Review

Recent years have seen increased interest in neuroergonomics, which investigates the brain activities of people engaged in diverse physical and cognitive activities at work and in everyday life. The present work extends upon prior assessments of the state of this art. However, here we narrow our focus specifically to studies that use electroencephalography (EEG) to measure brain activity, correlates, and effects during physical activity. The review uses systematically selected, openly published works derived from a guided search through peer-reviewed journals and conference proceedings. Identified studies were then categorized by the type of physical activity and evaluated considering methodological and chronological aspects via statistical and content-based analyses. From the identified works (n = 110), a specific number (n = 38) focused on less mobile muscular activities, while an additional group (n = 22) featured both physical and cognitive tasks. The remainder (n = 50) investigated various physical exercises and sporting activities and thus were here identified as a miscellaneous grouping. Most of the physical activities were isometric exertions, moving parts of upper and lower limbs, or walking and cycling. These primary categories were sub-categorized based on movement patterns, the use of the event-related potentials (ERP) technique, the use of recording methods along with EEG and considering mental effects. Further information on subjects' gender, EEG recording devices, data processing, and artifact correction methods and citations was extracted. Due to the heterogeneous nature of the findings from various studies, statistical analyses were not performed. These were thus included in a descriptive fashion. Finally, contemporary research gaps were pointed out, and future research prospects to address those gaps were discussed.

Group-level cortical and muscular connectivity during perturbations to walking and standing balance

Maintaining balance is a complex process requiring multisensory processing and coordinated muscle activation. Previous studies have indicated that the cortex is directly involved in balance control, but less information is known about cortical flow of signals for balance. We studied source-localized electrocortical effective connectivity dynamics of healthy young subjects (29 subjects: 14 male and 15 female) walking and standing with both visual and physical perturbations to their balance. The goal of this study was to quantify differences in group-level corticomuscular connectivity responses to sensorimotor perturbations during walking and standing. We hypothesized that perturbed visual input during balance would transiently decrease connectivity between occipital and parietal areas due to disruptive visual input during sensory processing. We also hypothesized that physical pull perturbations would increase cortical connections to central sensorimotor areas because of higher sensorimotor integration demands. Our findings show decreased occipito-parietal connectivity during visual rotations and widespread increases in connectivity during pull perturbations focused on central areas, as expected. We also found evidence for communication from cortex to muscles during perturbed balance. These results show that sensorimotor perturbations to balance alter cortical networks and can be quantified using effective connectivity estimation.

Do sensorimotor perturbations to standing balance elicit an error-related negativity?

Detecting and correcting errors is essential to successful action. Studies on response monitoring have examined scalp ERPs following the commission of motor slips in speeded-response tasks, focusing on a frontocentral negativity (i.e., error-related negativity or ERN). Sensorimotor neurophysiologists investigating cortical monitoring of reactive balance recovery behavior observe a strikingly similar pattern of scalp ERPs following externally imposed postural errors, including a brief frontocentral negativity that has been referred to as the balance N1. We integrate and review relevant literature from these discrepant fields to suggest shared underlying mechanisms and potential benefits of collaboration across fields. Unlike the cognitive tasks leveraged to study the ERN, balance perturbations afford precise experimental control of postural errors to elicit balance N1s that are an order of magnitude larger than the ERN and drive robust and well-characterized adaptation of behavior within an experimental session. Many factors that modulate the ERN, including motivation, perceived consequences, perceptual salience, expectation, development, and aging, are likewise known to modulate the balance N1. We propose that the ERN and balance N1 reflect common neural activity for detecting errors. Collaboration across fields could help clarify the functional significance of the ERN and poorly understood interactions between motor and cognitive impairments.