Previous research has indicated that neural crosstalk is asymmetric, with the dominant effector exerting a stronger influence on the non-dominant effector than vice versa. Recently, it has been hypothesized that this influence is more substantial for proximal than distal effectors. The current investigation was designed to determine the effects of distal ((First Dorsal Interosseous (FDI)) and proximal (triceps brachii (TBI)) muscle activation on neural crosstalk. Twelve right-limb dominant participants (mean age = 21.9) were required to rhythmically coordinate a 1:2 pattern of isometric force guided by Lissajous displays. Participants performed 10, 30 s trials with both distal and proximal effectors. Coherence between the two effector groups were calculated using EMG-EMG wavelet coherence. The results indicated that participants could effectively coordinate the goal coordination pattern regardless of the effectors used. However, spatiotemporal performance was more accurate when performing the task with distal than proximal effectors. Force distortion, quantified by harmonicity, indicated that more perturbations occurred in the non-dominant effector than in the dominant effector. The results also indicated significantly lower harmonicity for the non-dominant proximal effector compared to the distal effectors. The current results support the notion that neural crosstalk is asymmetric in nature and is greater for proximal than distal effectors. Additionally, the EMG-EMG coherence results indicated significant neural crosstalk was occurring in the Alpha bands (5–13 Hz), with higher values observed in the proximal condition. Significant coherence in the Alpha bands suggest that the influence of neural crosstalk is occurring at a subcortical level.

Background/Objectives: Parkinson’s disease (PD) is a neurodegenerative disorder characterized by tremors, balance impairments, and mobility limitations. Innovative approaches like combining transcranial direct current stimulation (tDCS) with exercise show promise in addressing these symptoms. This study investigates the effects of exercise combined with tDCS on mobility and tremor management in PD patients. Methods: Twenty-five individuals aged 60−75 (66.6 ± 7.33), diagnosed with PD (Hoehn and Yahr stage 2−3), were assigned to three groups in a randomized controlled design: exercise with active tDCS (n = 8), exercise with sham tDCS (n = 8), and a control group (n = 9). Dual-task training sessions focusing on walking speed, balance, and force control were conducted over ten sessions. Results: No significant differences were detected across the groups for grip strength or force control measures (p > 0.05). Significant improvements were observed in the intervention group: the Timed Up and Go (TUG) test showed a significant reduction in time (mean difference = 2.498 s, p < 0.001, ηp² = 0.331); anterior–posterior displacement significantly increased (mean difference = 21.375 mm, p = 0.0269, ηp² = 0.303); and force-tremor decoupling improved, with coherence in the 1−4 Hz band significantly decreasing (p = 0.0067). Finally, changes in TUG from post- to pre-treatment values were significantly positively correlated with the changes in coherence (R = 0.468, p = 0.018). Conclusions: Combining tDCS with exercise enhances mobility and tremor management in PD patients. These findings support the potential for such interventions to improve functional outcomes and quality of life for individuals with PD.

Motor learning involves acquiring new movement sequences and adapting motor commands to novel conditions. Labile motor memories, acquired through sequence learning and dynamic adaptation, undergo a consolidation process during wakefulness after initial training. This process stabilizes the new memories, leading to long-term memory formation. However, it remains unclear if the consolidation processes underlying sequence learning and dynamic adaptation are independent and if distinct neural regions underpin memory consolidation associated with sequence learning and dynamic adaptation. Here, we first demonstrated that the initially labile memories formed during sequence learning and dynamic adaptation were stabilized against interference through time-dependent consolidation processes occurring during wakefulness. Furthermore, we found that sequence learning memory was not disrupted when immediately followed by dynamic adaptation and vice versa, indicating distinct mechanisms for sequence learning and dynamic adaptation consolidation. Finally, by applying patterned transcranial magnetic stimulation to selectively disrupt the activity in the primary motor (M1) or sensory (S1) cortices immediately after sequence learning or dynamic adaptation, we found that sequence learning consolidation depended on M1 but not S1, while dynamic adaptation consolidation relied on S1 but not M1. For the first time in a single experimental framework, this study revealed distinct neural underpinnings for sequence learning and dynamic adaptation consolidation during wakefulness, with significant implications for motor skill enhancement and rehabilitation.

Touch sensation from the glabrous skin of the hand is essential for precisely controlling dexterous movements, yet the neural mechanisms by which tactile inputs influence motor circuits remain largely unexplored. By pairing air-puff tactile stimulation on the hand's glabrous skin with transcranial magnetic stimulation (TMS) over the primary motor cortex (M1), we examined the effects of tactile stimuli from single or multiple fingers on corticospinal excitability and M1's intracortical circuits. Our results showed that when we targeted the hand's first dorsal interosseous (FDI) muscle with TMS, homotopic (index finger) tactile stimulation, regardless of its point (fingertip or base), reduced corticospinal excitability. Conversely, heterotopic (ring finger) tactile stimulation had no such effect. Notably, stimulating all five fingers simultaneously led to a more pronounced decrease in corticospinal excitability than stimulating individual fingers. Furthermore, tactile stimulation significantly increased intracortical facilitation (ICF) and decreased long-interval intracortical inhibition (LICI) but did not affect short-interval intracortical inhibition (SICI). Considering the significant role of the primary somatosensory cortex (S1) in tactile processing, we also examined the effects of downregulating S1 excitability via continuous theta burst stimulation (cTBS) on tactile–motor interactions. Following cTBS, the inhibitory influence of tactile inputs on corticospinal excitability was diminished. Our findings highlight the spatial specificity of tactile inputs in influencing corticospinal excitability. Moreover, we suggest that tactile inputs distinctly modulate M1's excitatory and inhibitory pathways, with S1 being crucial in facilitating tactile–motor integration.

Typical symptoms of Parkinson's disease (PD) include freezing of gait, shuffling steps, and stooped posture, which introduce high risks of falling. Existing studies characterize and analyze PD symptoms through walking using wearable sensors. In addition, toe tapping is often used in clinical motor examination representing rotational agility in lower extremities, which is a critical factor in PD motor functionality and relates to falling. In this letter, we investigate the time and acceleration feature differences between PD patients and their age-matched healthy control (HC) subjects through alternating and synchronized toe tapping. Monitoring insoles are used to collect acceleration data with ten PD patients and nine HC subjects. In total, 87 time-axis and 1152 acceleration-axis features are extracted and analyzed between the two groups. The results suggest acceleration-axis features are with more significance in differing PD patients and HC subjects than time-axis features. The results show toe tapping motion can better distinguish PD patients and HC with an accuracy of 87.65% using the acceleration-axis feature set compared to 57.07% with time-axis feature set. To help PD patient understand their falling, falling risks are evaluated in scores using linear regression, with (error ± standard deviation) = (0.97 ± 0.85) to be compatible to fall risk questionnaire developed by the U.S. Centers for Disease Control and Prevention. Our method and the experiment can be easily transformed into a mobile game for daily life use and provides falling risk scores to PD patients without occupying spaces.