Cortical reorganization to improve dynamic balance control with error amplification feedback

Background Error amplification (EA), virtually magnify task errors in visual feedback, is a potential neurocognitive approach to facilitate motor performance. With regional activities and inter-regional connectivity of electroencephalography (EEG), this study investigated underlying cortical mechanisms associated with improvement of postural balance using EA. Methods Eighteen healthy young participants maintained postural stability on a stabilometer, guided by two visual feedbacks (error amplification (EA) vs. real error (RE)), while stabilometer plate movement and scalp EEG were recorded. Plate dynamics, including root mean square (RMS), sample entropy (SampEn), and mean frequency (MF) were used to characterize behavioral strategies. Regional cortical activity and inter-regional connectivity of EEG sub-bands were characterized to infer neural control with relative power and phase-lag index (PLI), respectively. Results In contrast to RE, EA magnified the errors in the visual feedback to twice its size during stabilometer stance. The results showed that EA led to smaller RMS of postural fluctuations with greater SampEn and MF than RE did. Compared with RE, EA altered cortical organizations with greater regional powers in the mid-frontal cluster (theta, 4–7 Hz), occipital cluster (alpha, 8–12 Hz), and left temporal cluster (beta, 13–35 Hz). In terms of the phase-lag index of EEG between electrode pairs, EA significantly reduced long-range prefrontal-parietal and prefrontal-occipital connectivity of the alpha/beta bands, and the right tempo-parietal connectivity of the theta/alpha bands. Alternatively, EA augmented the fronto-centro-parietal connectivity of the theta/alpha bands, along with the right temporo-frontal and temporo-parietal connectivity of the beta band. Conclusion EA alters postural strategies to improve stance stability on a stabilometer with visual feedback, attributable to enhanced error processing and attentional release for target localization. This study provides supporting neural correlates for the use of virtual reality with EA during balance training.

Transcranial alternating current stimulation does not modulate corticospinal activity in humans

Transcranial alternating current stimulation (TACS) is commonly used to synchronise the output of a cortical area to other parts of the nervous system, but evidence for this based on brain recordings in humans is challenging. The brain transmits beta oscillations (~21Hz) to tonically contracted limb muscles linearly and through the fastest corticospinal pathways. Therefore, muscle activity may be used as a proxy measure for the level of beta entrainment in the corticospinal tract due to TACS over motor cortex. Here, we assessed if TACS is able to modulate the neural inputs to muscles, which would provide an indirect evidence for TACS-driven neural entrainment. In the first part of this study, we ran a series of simulations of motor neuron (MN) pools receiving inputs from corticospinal neurons with different levels of beta entrainment. Results indicated that MNs should be highly sensitive to changes in corticospinal beta activity. Then, we ran experiments on healthy human subjects (N=10) in which TACS (at 1mA) was delivered over the motor cortex at 21Hz (beta stimulation), or at 7Hz or 40Hz (control conditions) while the abductor digiti minimi (ADM) or the tibialis anterior muscle (TA) were tonically contracted. Muscle activity was measured using high-density electromyography, which allowed us to decompose the spiking activity of pools of motor units innervating the studied muscles. By analysing motor unit pool activity, we observed that none of the tested TACS conditions could consistently alter the spectral characteristics of the common neural inputs received by the muscles. These results suggest that 1mA-TACS over motor cortex given at frequencies in the beta band does not affect corticospinal beta entrainment.

Electrophysiological Biomarkers for the Assessment of Motor Efficiency in Sport

Many disciplines have approached the study of human motor behavior. The motor learning theory based on information processing proposes a learning loop through interaction between the external environment and the central nervous system. Different neuroscience fields and technological advances provide a new perspective for the intensive study of the intrinsic processes of motor behavior, which modify the most visible aspect: motor efficiency. The aim of the present review was to determine which cortical and muscular electrophysiological biomarkers available in the literature could be representative for the study and quantification of motor efficiency. In this review, a survey of the literature related to motor production has been performed. The continuous development of biological signal monitoring techniques has allowed to understand part of the communication methods of the central nervous system, the integration of neural networks, and the interaction between different anatomic structures through rhythmic patterns of discharge known as brain waves. Motor production has been characterized by detecting electrophysiological biomarkers, taking into account the connectivity that can be represented by the corticomuscular and intermuscular coherence indices in different frequency bands. The present work proposes an approach to use these biomarkers on beta-band (for muscle stability synergies) and gamma-band (for mobility synergies). These indices will allow establishing quantitative parameters for motor efficiency, which could improve the precision of sports assessment.

EEG signatures change during unilateral Yogi nasal breathing

Airflow through the left-and-right nostrils is said to be entrained by an endogenous nasal cycle paced by both poles of the hypothalamus. Yogic practices suggest, and scientific evidence demonstrates, that right-nostril breathing is involved with relatively higher sympathetic activity (arousal states), while left-nostril breathing is associated with a relatively more parasympathetic activity (stress alleviating state). The objective of this study was to further explore this laterality by controlling nasal airflow and observing patterns of cortical activity through encephalographic (EEG) recordings. Thirty subjects participated in this crossover study. The experimental session consisted of a resting phase (baseline), then a period of unilateral nostril breathing (UNB) using the dominant nasal airway, followed by UNB using the non-dominant nasal airway. A 64-channel EEG was recorded throughout the whole session. The effects of nostril-dominance, and nostril-lateralization were assessed using the power spectral density of the neural activity. The differences in power-spectra and source localization were calculated between EEG recorded during UNB and baseline for delta, theta, alpha, beta and gamma bands. Cluster-based permutation tests showed that compared to baseline, EEG spectral power was significantly (1) decreased in all frequency bands for non-dominant nostril UNB, (2) decreased in alpha, beta and gamma bands for dominant nostril UNB, (3) decreased in all bands for left nostril UNB, and (4) decreased in all bands except delta for right nostril UNB. The beta band showed the most widely distributed changes across the scalp. our source localisation results show that breathing with the dominant nostril breathing increases EEG power in the left inferior frontal (alpha band) and left parietal lobule (beta band), whereas non-dominant nostril breathing is related to more diffuse and bilateral effects in posterior areas of the brain.These preliminary findings may stimulate further research in the area, with potential applications to tailored treatment of brain disorders associated with disruption of sympathetic and parasympathetic activity.

Grasp-Squeeze Adaptation to Changes in Object Compliance Leads to Dynamic Beta-Band Communication Between Primary Somatosensory and Motor Cortices

In asking the question of how the brain adapts to changes in the softness of manipulated objects, we studied dynamic communication between the primary sensory and motor cortical areas when nonhuman primates grasp and squeeze an elastically deformable manipulandum to attain an instructed force level. We focused on local field potentials recorded from S1 and M1 via intracortical microelectrode arrays. We computed nonparametric spectral Granger Causality to assess directed cortico-cortical interactions between these two areas. We demonstrate that the time-causal relationship between M1 and S1 is bidirectional in the beta-band (15-30Hz) and that this interareal communication develops dynamically as the subjects adjust the force of hand squeeze to reach the target level. In particular, the directed interaction is strongest when subjects are focused on maintaining the instructed force of hand squeeze in a steady state for several seconds. When the manipulandum’s compliance is abruptly changed, beta-band interareal communication is interrupted for a short period (~ 1 second) and then is re-established once the subject has reached a new steady state. These results suggest that transient beta oscillations can provide a communication subspace for dynamic cortico-cortical S1-M1 interactions during maintenance of steady sensorimotor states.

Sleep-Dependent Anomalous Cortical Information Interaction in Patients With Depression

Depression is a prevalent mental illness with high morbidity and is considered the main cause of disability worldwide. Brain activity while sleeping is reported to be affected by such mental illness. To explore the change of cortical information flow during sleep in depressed patients, a delay symbolic phase transfer entropy of scalp electroencephalography signals was used to measure effective connectivity between cortical regions in various frequency bands and sleep stages. The patient group and the control group shared similar patterns of information flow between channels during sleep. Obvious information flows to the left hemisphere and to the anterior cortex were found. Moreover, the occiput tended to be the information driver, whereas the frontal regions played the role of the receiver, and the right hemispheric regions showed a stronger information drive than the left ones. Compared with healthy controls, such directional tendencies in information flow and the definiteness of role division in cortical regions were both weakened in patients in most frequency bands and sleep stages, but the beta band during the N1 stage was an exception. The computable sleep-dependent cortical interaction may provide clues to characterize cortical abnormalities in depressed patients and should be helpful for the diagnosis of depression.

Median Nerve Stimulation Facilitates the Identification of Somatotopy of the Subthalamic Nucleus in Parkinson’s Disease Patients under Inhalational Anesthesia

Deep brain stimulation (DBS) improves Parkinson’s disease (PD) symptoms by suppressing neuropathological oscillations. These oscillations are also modulated by inhalational anesthetics used during DBS surgery in some patients, influencing electrode placement accuracy. We sought to evaluate a method that could avoid these effects. We recorded subthalamic nucleus (STN) neuronal firings in 11 PD patients undergoing DBS under inhalational anesthesia. Microelectrode recording (MER) during DBS was collected under median nerve stimulation (MNS) delivered at 5, 20, and 90 Hz frequencies and without MNS. We analyzed the spike firing rate and neuronal activity with power spectral density (PSD), and assessed correlations between the neuronal oscillation parameters and clinical motor outcomes. No patient experienced adverse effects during or after DBS surgery. PSD analysis revealed that peripheral 20 Hz MNS produced significant differences in the dorsal and ventral subthalamic nucleus (STN) between the beta band oscillation (16.9 ± 7.0% versus 13.5 ± 4.8%, respectively) and gamma band oscillation (56.0 ± 13.7% versus 66.3 ± 9.4%, respectively) (p < 0.05). Moreover, 20-Hz MNS entrained neural oscillation over the dorsal STN, which correlated positively with motor disabilities. MNS allowed localization of the sensorimotor STN and identified neural characteristics under inhalational anesthesia. This paradigm may help identify an alternative method to facilitate STN identification and DBS surgery under inhalational anesthesia.

Motor Imagination of Lower Limb Movements at Different Frequencies

Motor imagination (MI) is the mental process of only imagining an action without an actual movement. Research on MI has made significant progress in feature information detection and machine learning decoding algorithms, but there are still problems, such as a low overall recognition rate and large differences in individual execution effects, which make the development of MI run into a bottleneck. Aiming at solving this bottleneck problem, the current study optimized the quality of the MI original signal by “enhancing the difficulty of imagination tasks,” conducted the qualitative and quantitative analyses of EEG rhythm characteristics, and used quantitative indicators, such as ERD mean value and recognition rate. Research on the comparative analysis of the lower limb MI of different tasks, namely, high-frequency motor imagination (HFMI) and low-frequency motor imagination (LFMI), was conducted. The results validate the following: the average ERD of HFMI (−1.827) is less than that of LFMI (−1.3487) in the alpha band, so did (−3.4756 < −2.2891) in the beta band. In the alpha and beta characteristic frequency bands, the average ERD of HFMI is smaller than that of LFMI, and the ERD values of the two are significantly different ( p = 0.0074 < 0.01 ; r = 0.945). The ERD intensity STD values of HFMI are less than those of LFMI. which suggests that the ERD intensity individual difference among the subjects is smaller in the HFMI mode than in the LFMI mode. The average recognition rate of HFMI is higher than that of LFMI (87.84% > 76.46%), and the recognition rate of the two modes is significantly different ( p = 0.0034 < 0.01 ; r = 0.429). In summary, this research optimizes the quality of MI brain signal sources by enhancing the difficulty of imagination tasks, achieving the purpose of improving the overall recognition rate of the lower limb MI of the participants and reducing the differences of individual execution effects and signal quality among the subjects.

Profiling Parkinson's disease cognitive phenotypes via resting-state magnetoencephalography

Aberrant brain oscillations are a hallmark of Parkinson's disease (PD) pathophysiology and may be related to motor and non-motor symptoms. Mild cognitive impairment (MCI) affects many people with PD even at the time of diagnosis and conversion risks to PD dementia (PDD) are very high. Unfortunately, pharmacotherapies are not addressing cognitive symptoms in PD. Profiling PD cognitive phenotypes (eg. MCI, PDD...) may therefore help inform future treatments. Neurophysiological methods, such as magnetoencephalography (MEG), offer the advantage of observing oscillatory patterns, whose regional and temporal profiles may elucidate how cognitive changes relate to neural mechanisms. We conducted a resting state MEG cross-sectional study of 89 persons with PD stratified into three phenotypic groups: normal cognition, MCI and PDD, in order to identify brain regions and frequencies most associated with each cognitive profile. In addition, a neuropsychological battery was administered to assess each domain of cognition. Our data showed higher power in lower frequency bands (delta and theta) observed along with more severe cognitive impairment, and associated with memory, language, attention and global cognition. Of the total 119 brain parcels assessed during source analysis, widespread group differences were found in the beta band, with significant changes mostly occurring between the normal cognition and MCI groups. Moreover, bilateral frontal and left-hemispheric regions were particularly affected in the other frequencies as cognitive decline becomes more pronounced. Our results suggest MCI and PDD may be qualitatively distinct cognitive phenotypes, and most dramatic changes seem to have happened when the PD brain shows mild cognitive decline.

Top-down contribution to motor network reorganization during action preparation

It is unclear whether the Bereitschaftspotential (BP) recorded in humans during action preparation mirrors motor areas activation escalation, or if its early and late phases reflect the engagement of different functional networks. Here, we aimed at recording the TMS evoked-potentials (TEP) stimulating the supplementary motor area (SMA) to assess whether and how cortical excitability and functional connectivity of this region change as the BP increases. We hypothesize that, at later stages, the SMA functional network should become more connected to regions relevant for the implementation of the final motor plan. We performed TMS-EEG recordings on fourteen healthy subjects during the performance of a visuomotor Go/No-go task, eliciting and recording cortical activity and functional connectivity at -700 ms and -300 ms before the onset of visual stimuli over the SMA. When approaching stimulus onset, and thus BP peak, the SMA increased its functional connectivity with movement-related structures in the gamma and alpha bands, indicating a regional top-down preparation to implement the motor act. Beta-band connectivity, instead, was maintained constant for the whole BP time-course, being potentially related to sustained attention required by the experimental task. These findings reveal that the BP is not a mere result of increased activation of the SMA, but the functional networks in which this region is involved qualitatively changes over time, becoming more related to the execution of the motor act.