IEEE Transactions on Neural Systems and Rehabilitation Engineering最新文献

Peripherally applied low-intensity focused ultrasound stimulation (LIFUS) has emerged as a new modality of tactile restoration recently. If repetitive LIFUS would cause perceptual adaptation, like transcutaneous electrical nerve stimulation (TENS) does, has been rarely investigated. To address this issue, 14 healthy volunteers received LIFUS-based fine tactile stimulation on their right index fingertip in this work. To evaluate their perceptual stability, both subjective perceptual ratings and peripheral local hemodynamic responses were deployed. The sensory-level TENS was also included for comparison. Our results showed that the LIFUS brought better perceptual acuity and perceptual stability than TENS in terms of subjective perception and judgement. Moreover, the LIFUS induced an increase of local blood perfusion volume (BPV) since stimulation onset, while the TENS caused a decrease of BPV, both followed by a slow rebound to the baseline. Notably, repetitive LIFUS didn't cause obvious progressive decrease of BPV responses with increasing dose, i.e., temporal accumulation, whereas TENS did. These findings would facilitate the development of non-invasive sensory feedback technique in multiple human-machine interaction scenarios, and shed valuable insights on neuromodulation mechanisms of peripherally applied LIFUS.

Deciphering the spatiotemporal patterns of gait behavior and synchronized cortical functional networks is highly significant in neuroscience research. However, current small-animal gait analyzers cannot synchronize gait and cortical functional network connectivity (CFNC), thus limiting our understanding of CFNC dynamics under different gaits. To address this issue, we developed a small-animal gait analyzer that can synchronize gait with whole-brain local field potentials in real time. Using this device, we precisely analyzed the real-time dynamic changes in the CFNC during fine gait movements and mapped the dynamic remodeling of the CFNC during the gait cycle in real time in mouse models of neuropathic pain and ischemic stroke, directly correlating phase-specific network reorganization with motor deficits. Our results demonstrate that the device can monitor the CFNC in real time across different gaits and reveal the specificity of cortical functional networks underlying some motor dysfunctions. This device has the potential to be used to dissect neural representations of motor control and assess treatment efficacy.

Electrical stimulation of somatic nerves has long been used as a treatment method for a wide range of diseases by increasing activity on a target nerve. Electrical nerve block is an emerging therapy that can provide the same targeted treatment by decreasing activity on the nerve. Here, we demonstrate that both of these techniques can be applied synergistically via a single electrode to achieve precise control of an autonomic system. Two electrodes were placed on the right-side rat vagus nerve. The vagus proximal to the electrodes was crushed, and the left side was cut to isolate the system. The proximal electrode was used to give a perturbing stimulus ramp (0 Hz → 30 Hz → 0 Hz) over 10 minutes to roughly mimic the vagal activity seen in an episode of vasovagal syncope. The distal electrode was used to apply either stimulation or kilohertz-frequency electrical nerve block (KHFAC) to the vagus to keep the heart rate at a specified setpoint. The stimulation parameters were decided by a closed-loop fuzzy logic controller. Three different gains for the controller were tried. While each gain showed success in controlling the heart rate, lower gain was sometimes not responsive enough for effective control, and high gain was seen to induce oscillations in the heart rate; a medium gain was seen to be effective without either of these issues. This demonstrates that a single electrode can deliver bimodal neuromodulation of a single nerve, providing a powerful treatment tool against autonomic dysregulation.

Understanding the frequency dependent alterations in brain-muscle communication after stroke is crucial for advancing targeted neurorehabilitation strategies. In this study, we propose a novel multilayer corticomuscular network (MCMN) model based on functional corticomuscular coupling characteristics. Using multi-channel electrophysiological recordings acquired during a multi-joint motor task, we constructed a super-connectivity matrix by combining phase synchronization and phase-amplitude coupling across frequency bands. We then examined both local (single-layer) and global (multilayer) network properties by comparing nodal metrics between stroke patients and healthy controls in terms of functional connectivity and topological organization. The results revealed that stroke patients exhibited enhanced theta band within-frequency subnetwork relative to controls, but significantly reduced beta and gamma band subnetworks. Cross-frequency subnetworks in patients showed diminished integrative capacity compared to controls, with the exception of proximal muscle nodes in the beta-gamma subnetwork, which displayed pronounced hub properties. At the global level, patients demonstrated contralateral compensatory reorganization, whereas the contralateral hemisphere exhibited impaired cross-layer integration. The MCMN of stroke patients showed reduced algebraic connectivity, reflecting lower network robustness and information transfer efficiency. Finally, we found that node degree of gamma band and multiplex clustering coefficient of ipsilateral exhibited a linear correlation with FMA-UE scores in stroke patients. This multilayer network approach reveals frequency-specific and topological reorganization of corticomuscular interactions following stroke, providing a novel systems level framework for exploring motor network plasticity and informing precision neurorehabilitation.