Non-motor Brain Regions in Non-dominant Hemisphere Are Influential in Decoding Movement Speed

Internal states as a source of subject-dependent movement variability are represented by large-scale brain networks

Humans' ability to adapt and learn relies on reflecting on past performance. These experiences form latent representations called internal states that induce movement variability that improves how we interact with our environment. Our study uncovered temporal dynamics and neural substrates of two states from ten subjects implanted with intracranial depth electrodes while they performed a goal-directed motor task with physical perturbations. We identified two internal states using state-space models: one tracking past errors and the other past perturbations. These states influenced reaction times and speed errors, revealing how subjects strategize from trial history. Using local field potentials from over 100 brain regions, we found large-scale brain networks such as the dorsal attention and default mode network modulate visuospatial attention based on recent performance and environmental feedback. Notably, these networks were more prominent in higher-performing subjects, emphasizing their role in improving motor performance by regulating movement variability through internal states.

Static and dynamic resting-state brain activity patterns of table tennis players in 7-Tesla MRI

Table tennis involves quick and accurate motor responses during training and competition. Multiple studies have reported considerably faster visuomotor responses and expertise-related intrinsic brain activity changes among table tennis players compared with matched controls. However, the underlying neural mechanisms remain unclear. Herein, we performed static and dynamic resting-state functional magnetic resonance imaging (rs-fMRI) analyses of 20 table tennis players and 21 control subjects using 7T ultra-high field imaging. We calculated the static and dynamic amplitude of low-frequency fluctuations (ALFF) of the two groups. The results revealed that table tennis players exhibited decreased static ALFF in the left inferior temporal gyrus (lITG) compared with the control group. Voxel-wised static functional connectivity (sFC) and dynamic functional connectivity (dFC) analyses using lITG as the seed region afforded complementary and overlapping results. The table tennis players exhibited decreased sFC in the right middle temporal gyrus and left inferior parietal gyrus. Conversely, they displayed increased dFC from the lITG to prefrontal cortex, particularly the left middle frontal gyrus, left superior frontal gyrus-medial, and left superior frontal gyrus-dorsolateral. These findings suggest that table tennis players demonstrate altered visuomotor transformation and executive function pathways. Both pathways involve the lITG, which is a vital node in the ventral visual stream. These static and dynamic analyses provide complementary and overlapping results, which may help us better understand the neural mechanisms underlying the changes in intrinsic brain activity and network organization induced by long-term table tennis skill training.

Stereo-EEG recordings extend known distributions of canonical movement-related oscillations

Objective.Previous electrophysiological research has characterized canonical oscillatory patterns associated with movement mostly from recordings of primary sensorimotor cortex. Less work has attempted to decode movement based on electrophysiological recordings from a broader array of brain areas such as those sampled by stereoelectroencephalography (sEEG), especially in humans. We aimed to identify and characterize different movement-related oscillations across a relatively broad sampling of brain areas in humans and if they extended beyond brain areas previously associated with movement.Approach.We used a linear support vector machine to decode time-frequency spectrograms time-locked to movement, and we validated our results with cluster permutation testing and common spatial pattern decoding.Main results.We were able to accurately classify sEEG spectrograms during a keypress movement task versus the inter-trial interval. Specifically, we found these previously-described patterns: beta (13-30 Hz) desynchronization, beta synchronization (rebound), pre-movement alpha (8-15 Hz) modulation, a post-movement broadband gamma (60-90 Hz) increase and an event-related potential. These oscillatory patterns were newly observed in a wide range of brain areas accessible with sEEG that are not accessible with other electrophysiology recording methods. For example, the presence of beta desynchronization in the frontal lobe was more widespread than previously described, extending outside primary and secondary motor cortices.Significance.Our classification revealed prominent time-frequency patterns which were also observed in previous studies that used non-invasive electroencephalography and electrocorticography, but here we identified these patterns in brain regions that had not yet been associated with movement. This provides new evidence for the anatomical extent of the system of putative motor networks that exhibit each of these oscillatory patterns.

Enhanced gait variability index and cognitive performance in Asian adults: Results from the Yishun Study

BACKGROUND

Although gait variability has been linked to cognitive decline among older adults, the lack of a comprehensive composite gait variability score has dampened the application of gait variability.

RESEARCH QUESTION

Does the enhanced gait variability index (EGVI) - a composite score gait variability index - provide differential and useful information on cognitive decline in community-dwelling adults from that using gait speed?

METHODS

Healthy community-dwelling adults (n = 311) aged 21-90 were individually administered the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). Habitual gait speed and spatiotemporal parameters were measured using a 6 m instrumented walkway system. The EGVI for each participant was calculated from five spatiotemporal parameters - step length(cm), step time(s), stance time(s), single support time(s) and stride velocity(cm/s). Linear regression models, controlling for age, gender, and education, were built to examine the independent effects of EGVI or gait speed on global cognition and individual domains.

RESULTS

Multiple regression revealed that gait speed contributed significantly to the performance of the domain "Attention" (p = 0.04) whereas EGVI contributed significantly for the performance of the domain "Visuospatial" (p = 0.04) and "Delayed Memory" (p = 0.02).

SIGNIFICANCE

EGVI provides differential and useful information from using gait speed alone. The EGVI may offer a solution to measure or track GV changes in relation to cognitive changes.

Baseline hippocampal beta band power Is lower in the presence of movement uncertainty

Objective This study aimed to characterize hippocampal neural signatures of uncertainty by measuring beta band power in the period prior to movement cue. Approach Participants with epilepsy were implanted with hippocampal depth electrodes for stereo electroencephalographic (SEEG) monitoring. Hippocampal beta (13-30 Hz) power changes have been observed during motor tasks such as the direct reach (DR) and Go/No-Go (GNG) tasks. The primary difference between the tasks is the presence of uncertainty about whether movement should be executed. Previous research on cortical responses to uncertainty has found that baseline beta power changes with uncertainty. SEEG data were sampled throughout phases of the DR and GNG tasks. Beta-band power during the fixation phase was compared between the DR and GNG task using a Wilcoxon rank sum test. This unpaired test was also used to analyze response times from cue to task completion between tasks. Main Results Eight patients who performed both reaching tasks were analyzed in this study. Movement response times in the GNG task were on average 210 milliseconds slower than in the DR task. All patients exhibited a significantly increased response latency in the GNG task compared to the DR task (Wilcoxon rank-sum p-value < 0.001). Six out of eight patients demonstrated statistically significant differences in beta power in single hippocampal contacts between the fixation phases of the GNG and DR tasks. At the group level, baseline beta power was significantly lower in the GNG task than in the DR task (Wilcoxon rank-sum p-value < 0.001). Significance This novel study found that, in the presence of task uncertainty, baseline beta power in the hippocampus is lower than in its absence. This finding implicates movement uncertainty as an important factor in baseline hippocampal beta power during movement preparation.

Shared and distinct voxel-based lesion-symptom mappings for spasticity and impaired movement in the hemiparetic upper limb

Hemiparesis and spasticity are common co-occurring manifestations of hemispheric stroke. The relationship between impaired precision and force in voluntary movement (hemiparesis) and the increment in muscle tone that stems from dysregulated activity of the stretch reflex (spasticity) is far from clear. Here we aimed to elucidate whether variation in lesion topography affects hemiparesis and spasticity in a similar or dis-similar manner. Voxel-based lesion-symptom mapping (VLSM) was used to assess the impact of lesion topography on (a) upper limb paresis, as reflected by the Fugl-Meyer Assessment scale for the upper limb and (b) elbow flexor spasticity, as reflected by the Tonic Stretch Reflex Threshold, in 41 patients with first-ever stroke. Hemiparesis and spasticity were affected by damage to peri-Sylvian cortical and subcortical regions and the putamen. Hemiparesis (but not spasticity) was affected by damage to the corticospinal tract at corona-radiata and capsular levels, and by damage to white-matter association tracts and additional regions in the temporal cortex and pallidum. VLSM conjunction analysis showed only a minor overlap of brain voxels where the existence of damage affected both hemiparesis and spasticity, suggesting that control of voluntary movement and regulation of muscle tone at rest involve largely separate parts of the motor network.

Neuromodulation in Beta-Band Power Between Movement Execution and Inhibition in the Human Hippocampus

INTRODUCTION

The hippocampus is thought to be involved in movement, but its precise role in movement execution and inhibition has not been well studied. Previous work with direct neural recordings has found beta-band (13-30 Hz) modulation in both movement execution and inhibition throughout the motor system, but the role of beta-band modulation in the hippocampus during movement inhibition is not well understood. Here, we perform a Go/No-Go reaching task in ten patients with medically refractory epilepsy to study human hippocampal beta-power changes during movement.

MATERIALS AND METHODS

Ten epilepsy patients (5 female; ages 21-46) were implanted with intracranial depth electrodes for seizure monitoring and localization. Local field potentials were sampled at 2000 Hz during a Go/No-Go movement task. Comparison of beta-band power between Go and No-Go conditions was conducted using Wilcoxon signed-rank hypothesis testing for each patient. Sub-analyses were conducted to assess differences in the anterior vs posterior contacts, ipsilateral vs contralateral contacts, and male vs female beta-power values.

RESULTS

Eight out of ten patients showed significant beta-power decreases during the Go movement response (p < 0.05) compared to baseline. Eight out of ten patients also showed significant beta-power increases in the No-Go condition, occurring in the absence of movement. No significant differences were noted between ipsilateral vs contralateral contacts nor in anterior vs posterior hippocampal contacts. Female participants had a higher task success rate than males and had significantly greater beta-power increases in the No-Go condition (p < 0.001).

CONCLUSION

These findings indicate that increases in hippocampal beta power are associated with movement inhibition. To the best of our knowledge, this study is the first to report this phenomenon in the human hippocampus. The beta band may represent a state-change signal involved in motor processing. Future focus on the beta band in understanding human motor and impulse control will be vital.

Continuously Decoding Grasping Movements using Stereotactic Depth Electrodes

Brain-Computer Interfaces (BCIs) that decode a patient's movement intention to control a prosthetic device could restore some independence to paralyzed patients. An important step on the road towards naturalistic prosthetic control is to decode movement continuously with low-latency. BCIs based on intracortical micro-arrays provide continuous control of robotic arms, but require a minor craniotomy. Surface recordings of neural activity using EEG have made great advances over the last years, but suffer from high noise levels and large intra-session variance. Here, we investigate the use of minimally invasive recordings using stereotactically implanted EEG (sEEG). These electrodes provide a sparse sampling across many brain regions. So far, promising decoding results have been presented using data measured from the subthalamic nucleus or trial-to-trial based methods using depth electrodes. In this work, we demonstrate that grasping movements can continuously be decoded using sEEG electrodes, as well. Beta and high-gamma activity was extracted from eight participants performing a grasping task. We demonstrate above chance level decoding of movement vs rest and left vs right, from both frequency bands with accuracies up to 0.94 AUC. The vastly different electrode locations between participants lead to large variability. In the future, we hope that sEEG recordings will provide additional information for the decoding process in neuroprostheses.