Model-based closed-loop control of thalamic deep brain stimulation.

Introduction: Closed-loop control of deep brain stimulation (DBS) is beneficial for effective and automatic treatment of various neurological disorders like Parkinson's disease (PD) and essential tremor (ET). Manual (open-loop) DBS programming solely based on clinical observations relies on neurologists' expertise and patients' experience. Continuous stimulation in open-loop DBS may decrease battery life and cause side effects. On the contrary, a closed-loop DBS system uses a feedback biomarker/signal to track worsening (or improving) of patients' symptoms and offers several advantages compared to the open-loop DBS system. Existing closed-loop DBS control systems do not incorporate physiological mechanisms underlying DBS or symptoms, e.g., how DBS modulates dynamics of synaptic plasticity. Methods: In this work, we propose a computational framework for development of a model-based DBS controller where a neural model can describe the relationship between DBS and neural activity and a polynomial-based approximation can estimate the relationship between neural and behavioral activities. A controller is used in our model in a quasi-real-time manner to find DBS patterns that significantly reduce the worsening of symptoms. By using the proposed computational framework, these DBS patterns can be tested clinically by predicting the effect of DBS before delivering it to the patient. We applied this framework to the problem of finding optimal DBS frequencies for essential tremor given electromyography (EMG) recordings solely. Building on our recent network model of ventral intermediate nuclei (Vim), the main surgical target of the tremor, in response to DBS, we developed neural model simulation in which physiological mechanisms underlying Vim-DBS are linked to symptomatic changes in EMG signals. By using a proportional-integral-derivative (PID) controller, we showed that a closed-loop system can track EMG signals and adjust the stimulation frequency of Vim-DBS so that the power of EMG reaches a desired control target. Results and discussion: We demonstrated that the model-based DBS frequency aligns well with that used in clinical studies. Our model-based closed-loop system is adaptable to different control targets and can potentially be used for different diseases and personalized systems.

Neural signatures of indirect pathway activity during subthalamic stimulation in Parkinson's disease.

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) produces an electrophysiological signature called evoked resonant neural activity (ERNA); a high-frequency oscillation that has been linked to treatment efficacy. However, the single-neuron and synaptic bases of ERNA are unsubstantiated. This study proposes that ERNA is a subcortical neuronal circuit signature of DBS-mediated engagement of the basal ganglia indirect pathway network. In people with Parkinson's disease, we: (i) showed that each peak of the ERNA waveform is associated with temporally-locked neuronal inhibition in the STN; (ii) characterized the temporal dynamics of ERNA; (iii) identified a putative mesocircuit architecture, embedded with empirically-derived synaptic dynamics, that is necessary for the emergence of ERNA in silico; (iv) localized ERNA to the dorsal STN in electrophysiological and normative anatomical space; (v) used patient-wise hotspot locations to assess spatial relevance of ERNA with respect to DBS outcome; and (vi) characterized the local fiber activation profile associated with the derived group-level ERNA hotspot.

Supervised and Unsupervised Deep Learning Approaches for EEG Seizure Prediction.

Epilepsy affects more than 50 million people worldwide, making it one of the world's most prevalent neurological diseases. The main symptom of epilepsy is seizures, which occur abruptly and can cause serious injury or death. The ability to predict the occurrence of an epileptic seizure could alleviate many risks and stresses people with epilepsy face. We formulate the problem of detecting preictal (or pre-seizure) with reference to normal EEG as a precursor to incoming seizure. To this end, we developed several supervised deep learning approaches model to identify preictal EEG from normal EEG. We further develop novel unsupervised deep learning approaches to train the models on only normal EEG, and detecting pre-seizure EEG as an anomalous event. These deep learning models were trained and evaluated on two large EEG seizure datasets in a person-specific manner. We found that both supervised and unsupervised approaches are feasible; however, their performance varies depending on the patient, approach and architecture. This new line of research has the potential to develop therapeutic interventions and save human lives.

Protocol for metadata and image collection at diabetic foot ulcer clinics: enabling research in wound analytics and deep learning.

BACKGROUND: The escalating impact of diabetes and its complications, including diabetic foot ulcers (DFUs), presents global challenges in quality of life, economics, and resources, affecting around half a billion people. DFU healing is hindered by hyperglycemia-related issues and diverse diabetes-related physiological changes, necessitating ongoing personalized care. Artificial intelligence and clinical research strive to address these challenges by facilitating early detection and efficient treatments despite resource constraints. This study establishes a standardized framework for DFU data collection, introducing a dedicated case report form, a comprehensive dataset named Zivot with patient population clinical feature breakdowns and a baseline for DFU detection using this dataset and a UNet architecture. RESULTS: Following this protocol, we created the Zivot dataset consisting of 269 patients with active DFUs, and about 3700 RGB images and corresponding thermal and depth maps for the DFUs. The effectiveness of collecting a consistent and clean dataset was demonstrated using a bounding box prediction deep learning network that was constructed with EfficientNet as the feature extractor and UNet architecture. The network was trained on the Zivot dataset, and the evaluation metrics showed promising values of 0.79 and 0.86 for F1-score and mAP segmentation metrics. CONCLUSIONS: This work and the Zivot database offer a foundation for further exploration of holistic and multimodal approaches to DFU research.

A dry polymer nanocomposite transcutaneous electrode for functional electrical stimulation.

BACKGROUND: Functional electrical stimulation (FES) can be used in rehabilitation to aid or improve function in people with paralysis. In clinical settings, it is common practice to use transcutaneous electrodes to apply the electrical stimulation, since they are non-invasive, and can be easily applied and repositioned as necessary. However, the current electrode options available for transcutaneous FES are limited and can have practical disadvantages, such as the need for a wet interface with the skin for better comfort and performance. Hence, we were motivated to develop a dry stimulation electrode which could perform equivalently or better than existing commercially available options. METHODS: We manufactured a thin-film dry polymer nanocomposite electrode, characterized it, and tested its performance for stimulation purposes with thirteen healthy individuals. We compared its functionality in terms of stimulation-induced muscle torque and comfort level against two other types of transcutaneous electrodes: self-adhesive hydrogel and carbon rubber. Each electrode type was also tested using three different stimulators and different intensity levels of stimulation. RESULTS: We found the proposed dry polymer nanocomposite electrode to be functional for stimulation, as there was no statistically significant difference between its performance to the other standard electrodes. Namely, the proposed dry electrode had comparable muscle torque generated and comfort level as the self-adhesive hydrogel and carbon rubber electrodes. From all combinations of electrode type and stimulators tested, the dry polymer nanocomposite electrode with the MyndSearch stimulator had the most comfortable average rating. CONCLUSIONS: The dry polymer nanocomposite electrode is a durable and flexible alternative to existing self-adhesive hydrogel and carbon rubber electrodes, which can be used without the addition of a wet interfacing agent (i.e., water or gel) to perform as well as the current electrodes used for stimulation purposes.

Modeling Instantaneous Firing Rate of Deep Brain Stimulation Target Neuronal Ensembles in the Basal Ganglia and Thalamus.

OBJECTIVE: Deep brain stimulation (DBS) is an effective treatment for movement disorders, including Parkinson disease and essential tremor. However, the underlying mechanisms of DBS remain elusive. Despite the capability of existing models in interpreting experimental data qualitatively, there are very few unified computational models that quantitatively capture the dynamics of the neuronal activity of varying stimulated nuclei-including subthalamic nucleus (STN), substantia nigra pars reticulata (SNr), and ventral intermediate nucleus (Vim)-across different DBS frequencies. MATERIALS AND METHODS: Both synthetic and experimental data were used in the model fitting; the synthetic data were generated by an established spiking neuron model that was reported in our previous work, and the experimental data were provided using single-unit microelectrode recordings (MERs) during DBS (microelectrode stimulation). Based on these data, we developed a novel mathematical model to represent the firing rate of neurons receiving DBS, including neurons in STN, SNr, and Vim-across different DBS frequencies. In our model, the DBS pulses were filtered through a synapse model and a nonlinear transfer function to formulate the firing rate variability. For each DBS-targeted nucleus, we fitted a single set of optimal model parameters consistent across varying DBS frequencies. RESULTS: Our model accurately reproduced the firing rates observed and calculated from both synthetic and experimental data. The optimal model parameters were consistent across different DBS frequencies. CONCLUSIONS: The result of our model fitting was in agreement with experimental single-unit MER data during DBS. Reproducing neuronal firing rates of different nuclei of the basal ganglia and thalamus during DBS can be helpful to further understand the mechanisms of DBS and to potentially optimize stimulation parameters based on their actual effects on neuronal activity.

Effectiveness of Non-Pharmacological Therapy on Physical Symptoms in Patients With Persistent Concussion Symptoms: A Systematic Review.

This systematic review provides a comprehensive overview on the effectiveness of rehabilitation on physical symptoms in patients of all ages with persistent concussion symptoms. PubMed, MEDLINE®, Cochrane library, Cumulative Index to Nursing and Allied Health Literature (CINAHL), and Embase were searched from January 1, 2012 to September 1, 2023 using terms related to physical post-concussion symptoms. Eligible articles were critically appraised using the Scottish Intercollegiate Guidelines Network (SIGN) and the Quality Assessment Tool. The Grading of Recommendations Assessment, Development, and Evaluation system was applied to rate the quality of evidence. Thirty-two articles were included. Preliminary evidence suggests that transcranial magnetic stimulation improves symptoms in adults, specifically headaches. Young adults reported a significant decrease in physical symptoms following sub-symptom aerobic training as well as cervical spine manual therapy. Tentatively, adults demonstrated improvements in headache symptoms following neurofeedback sessions, and progressive muscle relaxation resulted in a decrease in monthly headaches. Multimodal therapy in adults produced significant change in physical symptoms when compared with usual care. However, no further reduction in physical symptoms was observed when adult patients received a program of care that afforded cervicovestibular rehabilitation with symptom-limited exercise compared with a symptom-limited exercise program alone. Cognitive behavioral therapy demonstrated inconsistent findings for its effects on physical symptoms, specifically headaches. Veterans had a significant change in post-concussive symptoms, specifically headaches, following 3-month use of an interactive smartphone application as compared with standard care. Finally, in a pediatric population, the use of melatonin did not produce any changes in physical persistent concussion symptoms as compared with placebo. Preliminary evidence suggests that various forms of rehabilitative therapies can improve persistent physical concussive symptoms. However, given the methodological limitations in the majority of trials, the results need to be interpreted with caution.

Development of an Aerogel-Based Wet Electrode for Functional Electrical Stimulation.

Functional electrical stimulation (FES) has been a useful therapeutic tool in rehabilitation, particularly for people with paralysis. To deliver stimulation in its most basic setup, a stimulator and at least a pair of electrodes are needed. The electrodes are an essential part of the system since they allow the transduction of the stimulator signals into the body. Their performance can influence the experience of both patient and therapist in terms of movement generation, comfort, and ease of use. For non-invasive surface stimulation, current electrode options have several limitations involving their interfacing with the skin, practical inconveniences, and short-term functionality. Standard hydrogel electrodes tend to lose their adhesion with the skin quickly, while dry or textile electrodes require constant wetting to be comfortable. In this paper, we present the fabrication, characterization, and FES testing of a new aerogel-based wet electrode for surface stimulation applications for long-term and reusable FES applications. We investigated its functionality by stimulating the biceps brachii of twelve healthy individuals and collected elbow joint torque and comfort ratings for three different intensity levels (low, moderate, and high) of FES. Comparing to standard hydrogel electrodes, no statistically significant difference was found for any intensity of stimulation in either torque or comfort. Overall, the new aerogel-based electrode has an appropriate impedance, is flexible and soft, is conformable to the skin, has a high water absorption and retention, and can be used for FES purposes.

Scoping Review on Brain-Computer Interface-Controlled Electrical Stimulation Interventions for Upper Limb Rehabilitation in Adults: A Look at Participants, Interventions, and Technology.

Purpose: While current rehabilitation practice for improving arm and hand function relies on physical/occupational therapy, a growing body of research evaluates the effects of technology-enhanced rehabilitation. We review interventions that combine a brain-computer interface (BCI) with electrical stimulation (ES) for upper limb movement rehabilitation to summarize the evidence on (1) populations of study participants, (2) BCI-ES interventions, and (3) the BCI-ES systems. Method: After searching seven databases, two reviewers identified 23 eligible studies. We consolidated information on the study participants, interventions, and approaches used to develop integrated BCI-ES systems. The included studies investigated the use of BCI-ES interventions with stroke and spinal cord injury (SCI) populations. All studies used electroencephalography to collect brain signals for the BCI, and functional electrical stimulation was the most common type of ES. The BCI-ES interventions were typically conducted without a therapist, with sessions varying in both frequency and duration. Results: Of the 23 eligible studies, only 3 studies involved the SCI population, compared to 20 involving individuals with stroke. Conclusions: Future BCI-ES interventional studies could address this gap. Additionally, standardization of device and rehabilitation modalities, and study-appropriate involvement with therapists, can be considered to advance this intervention towards clinical implementation.

Objectif: les pratiques de réadaptation actuelles pour améliorer le fonctionnement de la main et du bras reposent sur la physiothérapie et l'ergothérapie, mais de plus en plus de recherches évaluent les effets de la réadaptation améliorée par la technologie. Les chercheurs analysent les interventions qui combinent une interface cerveau-ordinateur (ICO) à la stimulation électrique (SÉ) en réadaptation des mouvements des membres supérieurs pour résumer les données probantes sur 1) les populations de participants aux études, 2) les interventions d'ICO-SÉ et 3) les systèmes d'ICO-SÉ. Méthodologie: après avoir fouillé sept bases de données, deux analystes ont extrait 23 études admissibles. Les chercheurs ont regroupé l'information sur les participants aux études, de même que sur les interventions et les approches utilisées pour mettre au point des systèmes d'ICO-SÉ intégrés. Les études portaient sur l'utilisation des interventions d'ICO-SÉ auprès des populations victimes d'un accident vasculaire cérébral ou d'une lésion médullaire. Toutes faisaient appel à l'électroencéphalographie pour obtenir les signaux cérébraux de l'ICO, et la SÉ fonctionnelle était la SÉ la plus courante. Les interventions d'ICO-SÉ se déroulaient généralement sans thérapeute, et la fréquence et la durée des séances étaient variables. Résultats: sur les 23 études admissibles, seulement trois traitaient de la population victime d'une lésion médullaire, par rapport à 20 de personnes victimes d'un accident vasculaire cérébral. Conclusions: les futures études d'interventions d'ICO-SÉ pourraient corriger cette lacune. De plus, on peut envisager de standardiser les modalités des appareils et de la réadaptation et de prévoir une participation avec les thérapeutes adaptée à l'étude pour faire progresser cette intervention vers la mise en œuvre clinique.

Effectiveness of motor and prefrontal cortical areas for brain-controlled functional electrical stimulation neuromodulation.

Objective. Brain-computer interface (BCI)-controlled functional electrical stimulation (FES) could excite the central nervous system to enhance upper limb motor recovery. Our current study assessed the effectiveness of motor and prefrontal cortical activity-based BCI-FES to help elucidate the underlying neuromodulation mechanisms of this neurorehabilitation approach.Approach. The primary motor cortex (M1) and prefrontal cortex (PFC) BCI-FES interventions were performed for 25 min on separate days with twelve non-disabled participants. During the interventions, a single electrode from the contralateral M1 or PFC was used to detect event-related desynchronization (ERD) in the calibrated frequency range. If the BCI system detected ERD within 15 s of motor imagery, FES activated wrist extensor muscles. Otherwise, if the BCI system did not detect ERD within 15 s, a subsequent trial was initiated without FES. To evaluate neuromodulation effects, corticospinal excitability was assessed using single-pulse transcranial magnetic stimulation, and cortical excitability was assessed by motor imagery ERD and resting-state functional connectivity before, immediately, 30 min, and 60 min after each intervention.Main results. M1 and PFC BCI-FES interventions had similar success rates of approximately 80%, while the M1 intervention was faster in detecting ERD activity. Consequently, only the M1 intervention effectively elicited corticospinal excitability changes for at least 60 min around the targeted cortical area in the M1, suggesting a degree of spatial localization. However, cortical excitability measures did not indicate changes after either M1 or PFC BCI-FES.Significance. Neural mechanisms underlying the effectiveness of BCI-FES neuromodulation may be attributed to the M1 direct corticospinal projections and/or the closer timing between ERD detection and FES, which likely enhanced Hebbian-like plasticity by synchronizing cortical activation detected by the BCI system with the sensory nerve activation and movement related reafference elicited by FES.

Cryogel-based neurostimulation electrodes to activate endogenous neural precursor cells.

The delivery of electrical pulses to the brain via penetrating electrodes, known as brain stimulation, has been recognized as an effective clinical approach for treating neurological disorders. Resident brain neural precursor cells (NPCs) are electrosensitive cells that respond to electrical stimulation by expanding in number, migrating and differentiating which are important characteristics that support neural repair. Here, we report the design of a conductive cryogel brain stimulation electrode specifically developed for NPC activation. The cryogel electrode has a modulus switching mechanism permitting facile penetration and reducing the mechanical mismatch between brain tissue and the penetrating electrode. The cryogel demonstrated good in vivo biocompatibility and reduced the interfacial impedance to deliver the stimulating electric field with lower voltage under charge-balanced current controlled stimulation. An ex vivo assay reveals that electrical stimulation using the cryogel electrodes results in significant expansion in the size of NPC pool. Hence, the cryogel electrodes have the potential to be used for NPC activation to support endogenous neural repair. STATEMENT OF SIGNIFICANCE: The objective of this study is to develop a cryogel-based stimulation electrode as an alternative to traditional electrode materials to be used in regenerative medicine applications for enhancing neural regeneration in brain. The electrode offers benefits such as adaptive modulus for implantation, high charge storage and injection capacities, and modulus matching with brain tissue, allowing for stable delivery of electric field for long-term neuromodulation. The electrochemical properties of cryogel electrodes were characterized in living tissue with an ex vivo set-up, providing a deeper understanding of stimulation capacity in brain environments. The cryogel electrode is biocompatible and enables low voltage, current-controlled stimulation for effective activation of endogenous neural precursor cells, revealing their potential utility in neural stem cell-mediated brain repair.

Rehabilitation professionals' perspectives and experiences with the use of technologies for violence prevention: a qualitative study.

BACKGROUND: There is growing public policy and research interest in the development and use of various technologies for managing violence in healthcare settings to protect the health and well-being of patients and workers. However, little research exists on the impact of technologies on violence prevention, and in particular in the context of rehabilitation settings. Our study addresses this gap by exploring the perceptions and experiences of rehabilitation professionals regarding how technologies are used (or not) for violence prevention, and their perceptions regarding their efficacy and impact. METHODS: This was a descriptive qualitative study with 10 diverse professionals (e.g., physical therapy, occupational therapy, recreation therapy, nursing) who worked across inpatient and outpatient settings in one rehabilitation hospital. Data collection consisted of semi-structured interviews with all participants. A conventional approach to content analysis was used to identify key themes. RESULTS: We found that participants used three types of technologies for violence prevention: an electronic patient flagging system, fixed and portable emergency alarms, and cameras. All of these were perceived by participants as being largely ineffective for violence prevention due to poor design features, malfunction, limited resources, and incompatibility with the culture of care. Our analysis further suggests that professionals' perception that these technologies would not prevent violence may be linked to their focus on individual patients, with a corresponding lack of attention to structural factors, including the culture of care and the organizational and physical environment. CONCLUSIONS: Our findings suggest an urgent need for greater consideration of structural factors in efforts to develop effective interventions for violence prevention in rehabilitation settings, including the design and implementation of new technologies.

Inferring cognitive state underlying conflict choices in verbal Stroop task using heterogeneous input discriminative-generative decoder model.

Objective. The subthalamic nucleus (STN) of the basal ganglia interacts with the medial prefrontal cortex (mPFC) and shapes a control loop, specifically when the brain receives contradictory information from either different sensory systems or conflicting information from sensory inputs and prior knowledge that developed in the brain. Experimental studies demonstrated that significant increases in theta activities (2-8 Hz) in both the STN and mPFC as well as increased phase synchronization between mPFC and STN are prominent features of conflict processing. While these neural features reflect the importance of STN-mPFC circuitry in conflict processing, a low-dimensional representation of the mPFC-STN interaction referred to as a cognitive state, that links neural activities generated by these sub-regions to behavioral signals (e.g. the response time), remains to be identified.Approach. Here, we propose a new model, namely, the heterogeneous input discriminative-generative decoder (HI-DGD) model, to infer a cognitive state underlying decision-making based on neural activities (STN and mPFC) and behavioral signals (individuals' response time) recorded in ten Parkinson's disease (PD) patients while they performed a Stroop task. PD patients may have conflict processing which is quantitatively (may be qualitative in some) different from healthy populations.Main results. Using extensive synthetic and experimental data, we showed that the HI-DGD model can diffuse information from neural and behavioral data simultaneously and estimate cognitive states underlying conflict and non-conflict trials significantly better than traditional methods. Additionally, the HI-DGD model identified which neural features made significant contributions to conflict and non-conflict choices. Interestingly, the estimated features match well with those reported in experimental studies.Significance. Finally, we highlight the capability of the HI-DGD model in estimating a cognitive state from a single trial of observation, which makes it appropriate to be utilized in closed-loop neuromodulation systems.

Synchrony-Division Neural Multiplexing: An Encoding Model.

Cortical neurons receive mixed information from the collective spiking activities of primary sensory neurons in response to a sensory stimulus. A recent study demonstrated an abrupt increase or decrease in stimulus intensity and the stimulus intensity itself can be respectively represented by the synchronous and asynchronous spikes of S1 neurons in rats. This evidence capitalized on the ability of an ensemble of homogeneous neurons to multiplex, a coding strategy that was referred to as synchrony-division multiplexing (SDM). Although neural multiplexing can be conceived by distinct functions of individual neurons in a heterogeneous neural ensemble, the extent to which nearly identical neurons in a homogeneous neural ensemble encode multiple features of a mixed stimulus remains unknown. Here, we present a computational framework to provide a system-level understanding on how an ensemble of homogeneous neurons enable SDM. First, we simulate SDM with an ensemble of homogeneous conductance-based model neurons receiving a mixed stimulus comprising slow and fast features. Using feature-estimation techniques, we show that both features of the stimulus can be inferred from the generated spikes. Second, we utilize linear nonlinear (LNL) cascade models and calculate temporal filters and static nonlinearities of differentially synchronized spikes. We demonstrate that these filters and nonlinearities are distinct for synchronous and asynchronous spikes. Finally, we develop an augmented LNL cascade model as an encoding model for the SDM by combining individual LNLs calculated for each type of spike. The augmented LNL model reveals that a homogeneous neural ensemble model can perform two different functions, namely, temporal- and rate-coding, simultaneously.

Manipulating facial musculature with functional electrical stimulation as an intervention for major depressive disorder: a focused search of literature for a proposal.

BACKGROUND: Major Depressive Disorder (MDD) is associated with interoceptive deficits expressed throughout the body, particularly the facial musculature. According to the facial feedback hypothesis, afferent feedback from the facial muscles suffices to alter the emotional experience. Thus, manipulating the facial muscles could provide a new "mind-body" intervention for MDD. This article provides a conceptual overview of functional electrical stimulation (FES), a novel neuromodulation-based treatment modality that can be potentially used in the treatment of disorders of disrupted brain connectivity, such as MDD. METHODS: A focused literature search was performed for clinical studies of FES as a modulatory treatment for mood symptoms. The literature is reviewed in a narrative format, integrating theories of emotion, facial expression, and MDD. RESULTS: A rich body of literature on FES supports the notion that peripheral muscle manipulation in patients with stroke or spinal cord injury may enhance central neuroplasticity, restoring lost sensorimotor function. These neuroplastic effects suggest that FES may be a promising innovative intervention for psychiatric disorders of disrupted brain connectivity, such as MDD. Recent pilot data on repetitive FES applied to the facial muscles in healthy participants and patients with MDD show early promise, suggesting that FES may attenuate the negative interoceptive bias associated with MDD by enhancing positive facial feedback. Neurobiologically, the amygdala and nodes of the emotion-to-motor transformation loop may serve as potential neural targets for facial FES in MDD, as they integrate proprioceptive and interoceptive inputs from muscles of facial expression and fine-tune their motor output in line with socio-emotional context. CONCLUSIONS: Manipulating facial muscles may represent a mechanistically novel treatment strategy for MDD and other disorders of disrupted brain connectivity that is worthy of investigation in phase II/III trials.

Low-level voluntary input enhances corticospinal excitability during ankle dorsiflexion neuromuscular electrical stimulation in healthy young adults.

Previous evidence indicated that interventions with combined neuromuscular electrical stimulation (NMES) and voluntary muscle contractions could have superior effects on corticospinal excitability when the produced total force is larger than each single intervention. However, it is unclear whether the superior effects exist when the produced force is matched between the interventions. Ten able-bodied individuals performed three intervention sessions on separate days: (i) NMES-tibialis anterior (TA) stimulation; (ii) NMES+VOL-TA stimulation combined with voluntary ankle dorsiflexion; (iii) VOL-voluntary ankle dorsiflexion. Each intervention was exerted at the same total output of 20% of maximal force and applied intermittently (5 s ON / 19 s OFF) for 16 min. Motor evoked potentials (MEP) of the right TA and soleus muscles and maximum motor response (Mmax) of the common peroneal nerve were assessed: before, during, and for 30 min after each intervention. Additionally, the ankle dorsiflexion force-matching task was evaluated before and after each intervention. Consequently, the TA MEP/Mmax during NMES+VOL and VOL sessions were significantly facilitated immediately after the interventions started until the interventions were over. Compared to NMES, larger facilitation was observed during NMES+VOL and VOL sessions, but no difference was found between them. Motor control was not affected by any interventions. Although superior combined effects were not shown compared to voluntary contractions alone, low-level voluntary contractions combined with NMES resulted in facilitated corticospinal excitability compared to NMES alone. This suggests that the voluntary drive could improve the effects of NMES even during low-level contractions, even if motor control is not affected.

Effects of trunk neuromuscular electrical stimulation on the motor circuits of able-bodied individuals.

Upper- and lower-limb neuromuscular electrical stimulation (NMES) is known to modulate the excitability of the neural motor circuits. However, it remains unclear whether short-duration trunk muscle NMES could achieve similar neuromodulation effects. We assessed motor evoked potentials (MEPs) elicited through transcranial magnetic stimulation of the primary motor cortex representation of the trunk extensor muscles to evaluate corticospinal excitability. Moreover, cervicomedullary motor evoked potentials (CMEPs) were assessed through cervicomedullary junction magnetic stimulation to evaluate subcortical excitability. Twelve able-bodied individuals participated in the MEP study, and another twelve in the CMEP study. During the interventions, NMES was applied bilaterally to activate the erector spinae muscle and produce intermittent contractions (20 s ON/20 s OFF) for a total of 20 min while participants remained seated. Assessments were performed: (i) before; (ii) during (in brief periods when NMES was OFF); and (iii) immediately after the interventions to compare MEP or CMEP excitability. Our results showed that MEP responses were not affected by trunk NMES, while CMEP responses were facilitated for approximately 8 min during the intervention, and returned to baseline before the end of the 20 min stimulating period. Our findings therefore suggest that short-duration NMES of the trunk extensor muscles likely does not affect the corticospinal excitability, but it has a potential to facilitate subcortical neural circuits immediately after starting the intervention. These findings indicate that short-duration application of NEMS may be helpful in rehabilitation to enhance neuromodulation of the trunk subcortical neural motor circuits.

A novel ex vivo assay to define charge-balanced electrical stimulation parameters for neural precursor cell activation in vivo.

Endogenous neural stem cells and their progeny (together termed neural precursor cells (NPCs)) are promising candidates to facilitate neuroregeneration. Charge-balanced biphasic monopolar stimulation (BPMP) is a clinically relevant approach that can activate NPCs both in vitro and in vivo. Herein, we established a novel ex vivo stimulation system to optimize the efficacy of BPMP electric field (EF) application in activating endogenous NPCs. Using the ex vivo system, we discerned that cathodal amplitude of 200 µA resulted in the greatest NPC pool expansion and enhanced cathodal migration. Application of the same stimulation parameters in vivo resulted in the same NPC activation in the mouse brain. The design and implementation of the novel ex vivo model bridges the gap between in vitro and in vivo systems, enabling a moderate throughput stimulation system to explore and optimize EF parameters that can be applied to clinically relevant brain injury/disease models.

Evidence That Brain-Controlled Functional Electrical Stimulation Could Elicit Targeted Corticospinal Facilitation of Hand Muscles in Healthy Young Adults.

OBJECTIVES: Brain-computer interface (BCI)-controlled functional electrical stimulation (FES) has been used in rehabilitation for improving hand motor function. However, mechanisms of improvements are still not well understood. The objective of this study was to investigate how BCI-controlled FES affects hand muscle corticospinal excitability. MATERIALS AND METHODS: A total of 12 healthy young adults were recruited in the study. During BCI calibration, a single electroencephalography channel from the motor cortex and a frequency band were chosen to detect event-related desynchronization (ERD) of cortical oscillatory activity during kinesthetic wrist motor imagery (MI). The MI-based BCI system was used to detect active states on the basis of ERD activity in real time and produce contralateral wrist extension movements through FES of the extensor carpi radialis (ECR) muscle. As a control condition, FES was used to generate wrist extension at random intervals. The two interventions were performed on separate days and lasted 25 minutes. Motor evoked potentials (MEPs) in ECR (intervention target) and flexor carpi radialis (FCR) muscles were elicited through single-pulse transcranial magnetic stimulation of the motor cortex to compare corticospinal excitability before (pre), immediately after (post0), and 30 minutes after (post30) the interventions. RESULTS: After the BCI-FES intervention, ECR muscle MEPs were significantly facilitated at post0 and post30 time points compared with before the intervention (pre), whereas there were no changes in the FCR muscle corticospinal excitability. Conversely, after the random FES intervention, both ECR and FCR muscle MEPs were unaffected compared with before the intervention (pre). CONCLUSIONS: Our results demonstrated evidence that BCI-FES intervention could elicit muscle-specific short-term corticospinal excitability facilitation of the intervention targeted (ECR) muscle only, whereas randomly applied FES was ineffective in eliciting any changes. Notably, these findings suggest that associative cortical and peripheral activations during BCI-FES can effectively elicit targeted muscle corticospinal excitability facilitation, implying possible rehabilitation mechanisms.