Fronto-Parietal Brain Areas Contribute to the Online Control of Posture during a Continuous Balance Task

Context-dependent reduction in corticomuscular coupling for balance control in chronic stroke survivors

Balance control is an important indicator of mobility and independence in activities of daily living. How the functional coupling between the cortex and the muscle for balance control is affected following stroke remains to be known. We investigated the changes in coupling between the cortex and leg muscles during a challenging balance task over multiple frequency bands in chronic stroke survivors. Fourteen participants with stroke and ten healthy controls performed a challenging balance task. They stood on a computerized support surface that was either fixed (low difficulty condition) or sway-referenced with varying gain (medium and high difficulty conditions). We computed corticomuscular coherence between electrodes placed over the sensorimotor area (electroencephalography) and leg muscles (electromyography) and assessed balance performance using clinical and laboratory-based tests. We found significantly lower delta frequency band coherence in stroke participants when compared with healthy controls under medium difficulty condition, but not during low and high difficulty conditions. These differences were found for most of the distal but not for proximal leg muscle groups. No differences were found at other frequency bands. Participants with stroke showed poor balance clinical scores when compared with healthy controls, but no differences were found for laboratory-based tests. The observation of effects at distal but not at proximal muscle groups suggests differences in the (re)organization of the descending connections across two muscle groups for balance control. We argue that the observed group difference in delta band coherence indicates balance context-dependent alteration in mechanisms for the detection of somatosensory modulation resulting from sway-referencing of the support surface for balance maintenance following stroke.

Cortical activity associated with the maintenance of balance during unstable stances

Background

Humans continuously maintain and adjust posture during gait, standing, and sitting. The difficulty of postural control is reportedly increased during unstable stances, such as unipedal standing and with closed eyes. Although balance is slightly impaired in healthy young adults in such unstable stances, they rarely fall. The brain recognizes the change in sensory inputs and outputs motor commands to the musculoskeletal system. However, such changes in cortical activity associated with the maintenance of balance following periods of instability require further clarified.

Methods

In this study, a total of 15 male participants performed two postural control tasks and the center of pressure displacement and electroencephalogram were simultaneously measured. In addition, the correlation between amplitude of center of pressure displacement and power spectral density of electroencephalogram was analyzed.

Results

The movement of the center of pressure was larger in unipedal standing than in bipedal standing under both eye open and eye closed conditions. It was also larger under the eye closed condition compared with when the eyes were open in unipedal standing. The amplitude of high-frequency bandwidth (1-3 Hz) of the center of pressure displacement was larger during more difficult postural tasks than during easier ones, suggesting that the continuous maintenance of posture was required. The power spectral densities of the theta activity in the frontal area and the gamma activity in the parietal area were higher during more difficult postural tasks than during easier ones across two postural control tasks, and these correlate with the increase in amplitude of high-frequency bandwidth of the center of pressure displacement.

Conclusions

Taken together, specific activation patterns of the neocortex are suggested to be important for the postural maintenance during unstable stances.

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.

Task-dependent Alteration in Delta Band Corticomuscular Coherence during Standing in Chronic Stroke Survivors

Balance control is an important indicator of mobility and independence in activities of daily living. How the changes in functional integrity of corticospinal tract due to stroke affects the maintenance of upright stance remains to be known. We investigated the changes in functional coupling between the cortex and lower limb muscles during a challenging balance task over multiple frequency bands in chronic stroke survivors. Eleven stroke patients and nine healthy controls performed a challenging balance task. They stood on a computerized platform with/without somatosensory input distortion created by sway-referencing the support surface, thereby varying the difficulty levels of the task. We computed corticomuscular coherence between Cz (electroencephalography) and leg muscles and assessed balance performance using Berg Balance scale (BBS), Timed-up and go (TUG) and center of pressure (COP) measures. We found lower delta frequency band coherence in stroke patients when compared with healthy controls under medium difficulty condition for distal but not proximal leg muscles. For both groups, we found similar coherence at other frequency bands. On BBS and TUG, stroke patients showed poor balance. However, similar group differences were not consistently observed across COP measures. The presence of distal versus proximal effect suggests differences in the (re)organization of the corticospinal connections across the two muscles groups for balance control. We argue that the observed group difference in the delta coherence might be due to altered mechanisms for the detection of somatosensory modulation resulting from sway-referencing of the support platform for balance control.

Lateralized Neural Entropy modulates with Grip Force during Precision Grasping

When holding a coffee mug filled to the brim, we strive to avoid spilling the coffee. This ability relies on the neural processes underlying the control of finger forces on a moment-to-moment basis. The brain activity lateralized to the contralateral hemisphere averaged over a trial and across the trials is known to be associated with the magnitude of grip force applied on an object. However, the mechanistic involvement of the variability in neural signals during grip force control remains unclear. In this study, we examined the dependence of neural variability over the frontal, central, and parietal regions assessed using noninvasive electroencephalography (EEG) on grip force magnitude during an isometric force control task. We hypothesized laterally specific modulation in EEG variability with higher magnitude of the grip force exerted during grip force control. We utilized an existing EEG dataset (64 channel) comprised of healthy young adults, who performed an isometric force control task while receiving visual feedback of the force applied. The force magnitude to be exerted on the instrumented object was cued to participants during the task, and varied pseudorandomly among 5, 10, and 15% of their maximum voluntary contraction (MVC) across the trials. We quantified neural variability via sample entropy (sequence-dependent measure) and standard deviation (sequence-independent measure) of the temporal EEG signal over the frontal, central, and parietal electrodes. The EEG sample entropy over the central electrodes showed lateralized, nonlinear, localized, modulation with force magnitude. Similar modulation was not observed over frontal or parietal EEG activity, nor for standard deviation in the EEG activity. Our findings highlight specificity in neural control of grip forces by demonstrating the modulation in sequence-dependent but not sequence-independent component of EEG variability. This modulation appeared to be lateralized, spatially constrained, and functionally dependent on the grip force magnitude. We discuss the relevance of these findings in scenarios where a finer precision is essential to enable grasp application, such as prosthesis and associated neural signal integration, and propose directions for future studies investigating the mechanistic role of neural entropy in grip force control.

Identifying the changes in the cortical activity of various brain regions for different balance tasks: A review

BACKGROUND

Balance support is critical to a person's overall function and health. Previous neuroimaging studies have shown that cortical structures play an essential role in postural control.

OBJECTIVE

This review aims to identify differences in the pattern of neural activity induced by balance tasks with different balance control requirements.

METHODS

Seventy-four articles were selected from the field of balance training and were examined based on four brain function detection technologies.

RESULTS

In general, most studies focused on the activity changes of various cortical areas during training at different difficulty levels, but more and more attention has also begun to focus on the functional changes of other cortical and deep subcortical structures. Our analysis also revealed the neglect of certain task types.

CONCLUSION

Based on these results, we identify and discuss future research directions that may contribute to a clear understanding of neural functional plasticity under different tasks.

Cerebellum-Cerebrum paired target magnetic stimulation on balance function and brain network of patients with stroke: A functional near-infrared spectroscopy pilot study

Transcranial magnetic stimulation (TMS) modulation over the cerebellum, primary motor cortex, and supplementary motor cortex individually can improve the balance function of patients with stroke. However, whether their combination could have a better balance modulation effect is uncertain. Therefore, we hypothesized that performing TMS over a combination of these targets can regulate the balance function of patients with stroke. We compared the effects of one-session TMS on eye-open and eye-closed balance conditions in patients with stroke, using different target pairs of unilateral cerebellar (CB-single), cerebellar-primary motor cortex (CB-M1), and cerebellar-supplementary motor area (CB-SMA) targets. A total of 31 patients with stroke were enrolled and randomly divided into three groups to receive single sessions of intermittent theta burst stimulation each. Functional near-infrared spectrum data on resting and standing task states (eye-open and eye-closed) and center of pressure parameters (eye-open and eye-closed) were collected before and after the intervention. Compared with the results in the CB-single group, five intergroup differences in the changes in the center of pressure parameters in the CB-M1 group and two significant differences in the CB-SMA group were observed after one session of intermittent theta burst stimulation. In the CB-SMA group, 12 out of the 14 parameters improved significantly in the EC condition after the intervention. Meanwhile, the functional near-infrared spectrum results showed that the CB-SMA group exhibited a significant inhibitory pattern in the resting-state functional connectivity, which was not observed in the other two groups. In conclusion, we believe that paired targeting of the CB-SMA can reshape the brain network and improve the balance function of patients with stroke.

Embodiment for Robotic Lower-Limb Exoskeletons: A Narrative Review

Research on embodiment of objects external to the human body has revealed important information about how the human nervous system interacts with robotic lower limb exoskeletons. Typical robotic exoskeleton control approaches view the controllers as an external agent intending to move in coordination with the human. However, principles of embodiment suggest that the exoskeleton controller should ideally coordinate with the human such that the nervous system can adequately model the input-output dynamics of the exoskeleton controller. Measuring embodiment of exoskeletons should be a necessary step in the exoskeleton development and prototyping process. Researchers need to establish high fidelity quantitative measures of embodiment, rather than relying on current qualitative survey measures. Mobile brain imaging techniques, such as high-density electroencephalography, is likely to provide a deeper understanding of embodiment during human-machine interactions and advance exoskeleton research and development. In this review we show why future exoskeleton research should include quantitative measures of embodiment as a metric of success.

Postural control paradigm (BioVRSea): towards a neurophysiological signature

Objective.To define a new neurophysiological signature from electroencephalography (EEG) during a complex postural control task using the BioVRSea paradigm, consisting of virtual reality (VR) and a moving platform, mimicking the behavior of a boat on the sea.Approach.EEG (64 electrodes) data from 190 healthy subjects were acquired. The experiment is composed of 6 segments (Baseline, PRE, 25%, 50%, 75%, POST). The baseline lasts 60 s while standing on the motionless platform with a mountain view in the VR goggles. PRE and POST last 40 s while standing on the motionless platform with a sea simulation. The 3 other tasks last 40 s each, with the platform moving to adapt to the waves, and the subject holding a bar to maintain its balance. The power spectral density (PSD) difference for each task minus baseline has been computed for every electrode, for five frequency bands (delta, theta, alpha, beta, and low-gamma). Statistical significance has been computed.Main results.All the bands were significant for the whole cohort, for each task regarding baseline. Delta band shows a prefrontal PSD increase, theta a fronto-parietal decrease, alpha a global scalp power decrease, beta an increase in the occipital and temporal scalps and a decrease in other areas, and low-gamma a significant but slight increase in the parietal, occipital and temporal scalp areas.Significance.This study develops a neurophysiological reference during a complex postural control task. In particular, we found a strong localized activity associated with certain frequency bands during certain phases of the experiment. This is the first step towards a neurophysiological signature that can be used to identify pathological conditions lacking quantitative diagnostics assessment.

Motor imagery in amyotrophic lateral Sclerosis: An fMRI study of postural control

•

ALS is associated with postural control impairment.

•

DCM and PEB frameworks help to characterize connectivity patterns during gait.

•

Clinical manifestations of ALS are underpinned by selective network dysfunction.

•

Altered BG-SMA and SMA-PPC connectivity are observed during imagined gait in ALS.

•

Enhanced BG-cerebellar connectivity may represent functional adaptation.

Background

The functional reorganization of brain networks sustaining gait is poorly characterized in amyotrophic lateral sclerosis (ALS) despite ample evidence of progressive disconnection between brain regions. The main objective of this fMRI study is to assess gait imagery-specific networks in ALS patients using dynamic causal modeling (DCM) complemented by parametric empirical Bayes (PEB) framework.

Method

Seventeen lower motor neuron predominant (LMNp) ALS patients, fourteen upper motor neuron predominant (UMNp) ALS patients and fourteen healthy controls participated in this study. Each subject performed a dual motor imagery task: normal and precision gait. The Movement Imagery Questionnaire (MIQ-rs) and imagery time (IT) were used to evaluate gait imagery in each participant. In a neurobiological computational model, the circuits involved in imagined gait and postural control were investigated by modelling the relationship between normal/precision gait and connection strengths.

Results

Behavioral results showed significant increase in IT in UMNp patients compared to healthy controls (P_corrected < 0.05) and LMNp (P_corrected < 0.05). During precision gait, healthy controls activate the model's circuits involved in the imagined gait and postural control. In UMNp, decreased connectivity (inhibition) from basal ganglia (BG) to supplementary motor area (SMA) and from SMA to posterior parietal cortex (PPC) is observed. Contrary to healthy controls, DCM detects no cerebellar-PPC connectivity in neither UMNp nor LMNp ALS. During precision gait, bilateral connectivity (excitability) between SMA and BG is observed in the LMNp group contrary to UMNp and healthy controls.

Conclusions

Our findings demonstrate the utility of implementing both DCM and PEB to characterize connectivity patterns in specific patient phenotypes. Our approach enables the identification of specific circuits involved in postural deficits, and our findings suggest a putative excitatory–inhibitory imbalance. More broadly, our data demonstrate how clinical manifestations are underpinned by network-specific disconnection phenomena in ALS.

Decoding Neural Activity Preceding Balance Loss During Standing with a Lower-limb Exoskeleton using an Interpretable Deep Learning Model

Falls are a leading cause of death in adults 65 and older. Recent efforts to restore lower-limb function in these populations have seen an increase in the use of wearable robotic systems; however, fall prevention measures in these systems require early detection of balance loss to be effective. Prior studies have investigated whether kinematic variables contain information about an impending fall, but few have examined the potential of using electroencephalography (EEG) as a fall-predicting signal and how the brain responds to avoid a fall. To address this, we decoded neural activity in a balance perturbation task while wearing an exoskeleton. We acquired EEG, electromyography (EMG), and center of pressure (COP) data from 7 healthy participants during mechanical perturbations while standing. The timing of the perturbations was randomized in all trials. We found perturbation evoked potentials (PEP) components as early as 75-134 ms after the onset of the external perturbation, which preceded both the peak in EMG (∼ 180 ms) and the COP (∼ 350 ms). A convolutional neural network trained to predict balance perturbations from single-trial EEG had a mean F-score of 75.0 ± 4.3 %. Clustering GradCAM-based model explanations demonstrated that the model utilized components in the PEP and was not driven by artifacts. Additionally, dynamic functional connectivity results agreed with model explanations; the nodal connectivity measured using phase difference derivative was higher in the occipital-parietal region in the early stage of perturbations, before shifting to the parietal, motor, and back to the frontal-parietal channels. Continuous-time decoding of COP trajectories from EEG, using a gated recurrent unit model, achieved a mean Pearson's correlation coefficient of 0.7 ± 0.06. Overall, our findings suggest that EEG signals contain short-latency neural information related to an impending fall, which may be useful for developing brain-machine interface systems for fall prevention in robotic exoskeletons.

Toward passive BCI: asynchronous decoding of neural responses to direction- and angle-specific perturbations during a simulated cockpit scenario

Neuroimaging studies have provided proof that loss of balance evokes specific neural transient wave complexes in electroencephalography (EEG), called perturbation evoked potentials (PEPs). Online decoding of balance perturbations from ongoing EEG signals can establish the possibility of implementing passive brain-computer interfaces (pBCIs) as a part of aviation/driving assistant systems. In this study, we investigated the feasibility of identifying the existence and expression of perturbations in four different conditions by using EEG signals. Fifteen healthy participants experienced four various postural changes while they sat in a glider cockpit. Sudden perturbations were exposed by a robot connected to a glider and moved to the right and left directions with tilting angles of 5 and 10 degrees. Perturbations occurred in an oddball paradigm in which participants were not aware of the time and expression of the perturbations. We employed a hierarchical approach to separate the perturbation and rest, and then discriminate the expression of perturbations. The performance of the BCI system was evaluated by using classification accuracy and F1 score. Asynchronously, we achieved average accuracies of 89.83 and 73.64% and average F1 scores of 0.93 and 0.60 for binary and multiclass classification, respectively. These results manifest the practicality of pBCI for the detection of balance disturbances in a realistic situation.

Assessment of Biomechanical Predictors of Occurrence of Low-Amplitude N1 Potentials Evoked by Naturally Occurring Postural Instabilities

Naturally occurring postural instabilities that occur while standing and walking elicit specific cortical responses in the fronto-central regions (N1 potentials) followed by corrective balance responses to prevent falling. However, no framework could simultaneously track different biomechanical parameters preceding N1s, predict N1s, and assess their predictive power. Here, we propose a framework and show its utility by examining cortical activity (through electroencephalography [EEG]), ground reaction forces, and head acceleration in the anterior-posterior (AP) direction. Ten healthy young adults carried out a balance task of standing on a support surface with or without sway referencing in the AP direction, amplifying, or dampening natural body sway. Using independent components from the fronto-central cortical region obtained from subject-specific head models, we first robustly validated a prior approach on identifying low-amplitude N1 potentials before early signs of balance corrections. Then, a machine learning algorithm was used to evaluate different biomechanical parameters obtained before N1 potentials, to predict the occurrence of N1s. When different biomechanical parameters were directly compared, the time to boundary (TTB) was found to be the best predictor of the occurrence of upcoming low-amplitude N1 potentials during a balance task. Based on these findings, we confirm that the spatio-temporal characteristics of the center of pressure (COP) might serve as an essential parameter that can facilitate the early detection of postural instability in a balance task. Extending our framework to identify such biomarkers in dynamic situations like walking might improve the implementation of corrective balance responses through brain-machine-interfaces to reduce falls in the elderly.

Perturbation of cortical activity elicits regional and age-dependent effects on unconstrained reaching behavior: a pilot study

Contributions from premotor and supplementary motor areas to reaching behavior in aging humans are not well understood. The objective of these experiments was to examine effects of perturbations to specific cortical areas on the control of unconstrained reaches against gravity by younger and older adults. Double-pulse transcranial magnetic stimulation (TMS) was applied to scalp locations targeting primary motor cortex (M1), dorsal premotor area (PMA), supplementary motor area (SMA), or dorsolateral prefrontal cortex (DLPFC). Stimulation was intended to perturb ongoing activity in the targeted cortical region before or after a visual cue to initiate moderately paced reaches to one of three vertical target locations. Regional effects were observed in movement amplitude both early and late in the reach. Perturbation of PMA increased reach distance before the time of peak velocity to a greater extent than all other regions. Reaches showed greater deviation from a straight-line path around the time of peak velocity and greater overall curvature with perturbation of PMA and M1 relative to SMA and DLPFC. The perturbation increased positional variability of the reach path at the time of peak velocity and the time elapsing after peak velocity. Although perturbations had stronger effects on reaches by younger subjects, this group exhibited less reach path variability at the time of peak velocity and required less time to adjust the movement trajectory thereafter. These findings support the role of PMA in visually guided reaching and suggest an age-related change in sensorimotor processing, possibly due to a loss of cortical inhibitory control.

The Effect of a Single Session of Non-Invasive Brain Stimulation on Balance in Healthy Individuals: A Systematic Review and Best Evidence Synthesis

Aim: To evaluate the effects of a single session of non-invasive brain stimulation (NIBS) on postural balance. Introduction: The NIBS has been used widely in improving balance. However, the effect of a single session of NIBS on balance in healthy individuals has not been systemically reviewed. Methods: A systematic literature review and best evidence synthesis were conducted, according to the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) guidelines, to determine the effects of different NIBS techniques on balance function in healthy individuals. The methodological quality of included articles was assessed by the risk of bias, and the Downs and Black tool. Data were analyzed by using the best evidence synthesis. Thirty-five articles were included that used the following NIBS techniques: anodal transcranial direct current stimulation (a-tDCS), cathodal transcranial direct current stimulation (c-tDCS), continuous theta burst stimulation (cTBS), and repetitive transcranial magnetic stimulation (rTMS) on primary motor cortex (M1), supplementary motor area (SMA), dorsolateral prefrontal cortex (DLPFC), and cerebellum on balance. Results: Strong evidence showed that a-tDCS of M1, SMA improve balance in healthy participants, and the a-tDCS of DLPFC induces improvement only in dual task balance indices. Also, the findings indicate that cerebellar a-tDCS might significantly improve balance, if at least 10 min cerebellar a-tDCS with an intensity of ≥1 mA, over or maximum 1.5 cm below the inion, is used. Strong evidence showed that c-tDCS, cTBS, and rTMS are not effective on the balance. Conclusion: According to the results, the a-tDCS may be a useful technique to improve balance in healthy adults.

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.

Brain connectivity during simulated balance in older adults with and without Parkinson's disease

Individuals with Parkinson's disease often experience postural instability, a debilitating and largely treatment-resistant symptom. A better understanding of the neural substrates contributing to postural instability could lead to more effective treatments. Constraints of current functional neuroimaging techniques, such as the horizontal orientation of most MRI scanners (forcing participants to lie supine), complicates investigating cortical and subcortical activation patterns and connectivity networks involved in healthy and parkinsonian balance control. In this cross-sectional study, we utilized a newly-validated MRI-compatible balance simulator (based on an inverted pendulum) that enabled participants to perform balance-relevant tasks while supine in the scanner. We utilized functional MRI to explore effective connectivity underlying static and dynamic balance control in healthy older adults (n = 17) and individuals with Parkinson's disease while on medication (n = 17). Participants performed four tasks within the scanner with eyes closed: resting, proprioceptive tracking of passive ankle movement, static balancing of the simulator, and dynamic responses to random perturbations of the simulator. All analyses were done in the participant's native space without spatial transformation to a common template. Effective connectivity between 57 regions of interest was computed using a Bayesian Network learning approach with false discovery rate set to 5%. The first 12 principal components of the connection weights, binomial logistic regression, and cross-validation were used to create 4 separate models: contrasting static balancing vs {rest, proprioception} and dynamic balancing vs {rest, proprioception} for both controls and individuals with Parkinson's disease. In order to directly compare relevant connections between controls and individuals with Parkinson's disease, we used connections relevant for predicting a task in either controls or individuals with Parkinson's disease in logistic regression with Least Absolute Shrinkage and Selection Operator regularization. During dynamic balancing, we observed decreased connectivity between different motor areas and increased connectivity from the brainstem to several cortical and subcortical areas in controls, while individuals with Parkinson's disease showed increased connectivity associated with motor and parietal areas, and decreased connectivity from brainstem to other subcortical areas. No significant models were found for static balancing in either group. Our results support the notion that dynamic balance control in individuals with Parkinson's disease relies more on cortical motor areas compared to healthy older adults, who show a preference of subcortical control during dynamic balancing.

Age-related differences in alpha and beta band activity in sensory association brain areas during challenging sensory tasks

Sensory challenges to postural balance are daily threats for elderly individuals. This study examined electroencephalography (EEG) in alpha and beta bands in sensory association areas during the Sensory Organization Test, involving withdrawal of visual or presenting misleading somatosensory inputs, in twelve young and twelve elderly participants. The results showed stepwise deterioration in behavioral performance in four conditions, with group effects that were amplified with combined sensory challenges. With eye closure, alpha and beta activities increased in all sensory association areas. Fast beta activity increased in the bilateral parietal-temporal-occipital areas. Misleading somatosensory information effects on EEG activity were of smaller amplitude than eye closure effects and in a different direction. Decreased alpha activity in left parietal-temporal-occipital areas and decreased beta and fast beta activities in bilateral parietal-temporal-occipital areas were significant. Elderly participants had increased fast beta activity in the left temporal-occipital and bilateral occipital areas, indicative of sustained efforts that they made in all sensory conditions. Similar to the young participants, elderly participants with eyes closed showed increased alpha activity, although to a smaller degree, in bilateral temporal-occipital and left occipital areas. This might indicate a lack of efficacy in redistributing relative sensory weights when elderly participants dealt with eye closure. In summary, EEG power changes did not match the stepwise deterioration in behavioral data, but reflected different sensory strategies adopted by young and elderly participants to cope with eye closure or misleading somatosensory information based on the efficacy of these different strategies.

Electroencephalographic neurofeedback training can decrease conscious motor control and increase single and dual-task psychomotor performance

The control of human movements is thought to automize with repetition, promoting consistent execution and reduced dual-task costs. However, contingencies such as illness or constraints to regular movement patterns can promote conscious motor control, which can reduce movement proficiency and make dual-task situations more difficult. This experiment evaluated whether electroencephalographic neurofeedback training can reduce the adverse effects of conscious motor control. Twenty-five participants completed the timed-up-and-go task while wearing a leg brace to de-automize their regular movement, under both single and dual-task (walking + serial sevens) conditions, both before and after 30-min of neurofeedback training. Three different types of neurofeedback were prescribed across three laboratory visits. We hypothesised that training to decrease central EEG alpha-power at scalp sites above the supplementary motor area would facilitate performance compared to opposite (increase central EEG alpha-power) or sham neurofeedback training. Results revealed a pre-test to post-test improvement in performance on the single-task and on both aspects of the dual-task when participants were trained to decrease central EEG alpha-power. There were no benefits of opposite or sham neurofeedback training. Mediation analyses revealed that the improvement in dual-task motor performance was mediated by the improvement in cognitive performance. This suggests that the neurofeedback protocol was beneficial because it helped to reduce conscious control of the motor task. The findings could have important implications for rehabilitation and high-performance (e.g., elite sport) domains; neurofeedback could be prescribed to help alleviate the problems that can arise when individuals exert conscious motor control.

Non-invasive Brain Stimulation of the Posterior Parietal Cortex Alters Postural Adaptation

Effective central sensory integration of visual, vestibular, and proprioceptive information is required to promote adaptability in response to changes in the environment during postural control. Patients with a lesion in the posterior parietal cortex (PPC) have an impaired ability to form an internal representation of body position, an important factor for postural control and adaptation. Suppression of PPC excitability has also been shown to decrease postural stability in some contexts. As of yet, it is unknown whether stimulation of the PPC may influence postural adaptation. This investigation aimed to identify whether transcranial direct current stimulation (tDCS) of the bilateral PPC could modulate postural adaptation in response to a bipedal incline postural adaptation task. Using young, healthy subjects, we delivered tDCS over bilateral PPC followed by bouts of inclined stance (incline-interventions). Analysis of postural after-effects identified differences between stimulation conditions for maximum lean after-effect (LAE; p = 0.005) as well as a significant interaction between condition and measurement period for the average position (p = 0.03). We identified impaired postural adaptability following both active stimulation conditions. Results reinforce the notion that the PPC is involved in motor adaptation and extend this line of research to the realm of standing posture. The results further highlight the role of the bilateral PPC in utilizing sensory feedback to update one's internal representation of verticality and demonstrates the diffuse regions of the brain that are involved in postural control and adaptation. This information improves our understanding of the role of the cortex in postural control, highlighting the potential for the PPC as a target for sensorimotor rehabilitation.

Functional neuroimaging of human postural control: A systematic review with meta-analysis

Postural instability is a strong risk factor for falls that becomes more prominent with aging. To facilitate treatment and prevention of falls in an aging society, a thorough understanding of the neural networks underlying postural control is warranted. Here, we present a systematic review of the functional neuroimaging literature of studies measuring posture-related neural activity in healthy subjects. Study methods were overall heterogeneous. Eleven out of the 14 studies relied on postural simulation in a supine position (e.g. motor imagery). The key nodes of human postural control involved the brainstem, cerebellum, basal ganglia, thalamus and several cortical regions. An activation likelihood estimation meta-analysis revealed that the anterior cerebellum was consistently activated across the wide range of postural tasks. The cerebellum is known to modulate the brainstem nuclei involved in the control of posture. Hence, this systematic review with meta-analysis provides insight into the neural correlates which underpin human postural control and which may serve as a reference for future neural network and region of interest analyses.

Fluctuations in Human Corticospinal Activity Prior to Grasp

Neuronal firing rate variability prior to movement onset contributes to trial-to-trial variability in primate behavior. However, in humans, whether similar mechanisms contribute to trial-to-trial behavioral variability remains unknown. We investigated the time-course of trial-to-trial variability in corticospinal excitability (CSE) using transcranial magnetic stimulation (TMS) during a self-paced reach-to-grasp task. We hypothesized that CSE variability will be modulated prior to the initiation of reach and that such a modulation would explain trial-to-trial behavioral variability. Able-bodied individuals were visually cued to plan their grip force before exertion of either 30% or 5% of their maximum pinch force capacity on an object. TMS was delivered at six time points (0.5, 0.75, 1, 1.1, 1.2, and 1.3 s) following a visual cue that instructed the force level. We first modeled the relation between CSE magnitude and its variability at rest (n = 12) to study the component of CSE variability pertaining to the task but not related to changes in CSE magnitude (n = 12). We found an increase in CSE variability from 1.2 to 1.3 s following the visual cue at 30% but not at 5% of force. This effect was temporally dissociated from the decrease in CSE magnitude that was observed from 0.5 to 0.75 s following the cue. Importantly, the increase in CSE variability explained at least ∼40% of inter-individual differences in trial-to-trial variability in time to peak force rate. These results were found to be repeatable across studies and robust to different analysis methods. Our findings suggest that the neural mechanisms underlying modulation in CSE variability and CSE magnitude are distinct. Notably, the extent of modulation in variability in corticospinal system prior to grasp within individuals may explain their trial-to-trial behavioral variability.