Muscle synergies after stroke are correlated with perilesional high gamma.

Movements can be factored into modules termed "muscle synergies". After stroke, abnormal synergies are linked to impaired movements; however, their neural basis is not understood. In a single subject, we examined how electrocorticography signals from the perilesional cortex were associated with synergies. The measured synergies contained a mix of both normal and abnormal patterns and were remarkably similar to those described in past work. Interestingly, we found that both normal and abnormal synergies were correlated with perilesional high gamma. Given the link between high gamma and cortical spiking, our results suggest that perilesional spiking may organize synergies after stroke

Utilizing microstimulation and local field potentials in the primary somatosensory and motor cortex

Brain-computer interfaces (BCIs) have advanced considerably from simple target detection by recording from a single neuron, to accomplishments like controlling a computer cursor accurately with neural activity from hundreds of neurons or providing instruction directly to the brain via microstimulation. However as BCIs continue to evolve, so do the challenges they face. Most BCIs rely on visual feedback, requiring sustained visual attention to use the device. As the role of BCIs expands beyond cursors moving on a computer screen to robotic hands picking up objects, there is increased need for an effective way to provide quick feedback independent of vision. Another challenge is utilizing all the signals available to produce the best decoding of movement possible. Local field potentials (LFPs) can be recorded at the same time as multi-unit activity (MUA) from multielectrode arrays but little is known in the area of what kind of information it possess, especially in relation to MUA. To tackle these issues, we preformed the following experiments. First, we examined the effectiveness of alternative forms of feedback applicable to BCIs, tactile stimuli delivered on the skin surface and microstimulation applied directly to the brain via the somatosensory cortex. To gauge effectiveness, we used a paradigm that captured a fundamental element of feedback: the ability to react to a stimulus while already in action. By measuring the response time to that stimulus, we were able to compare how well each modality could perform as a feedback stimulus. Second, we use regression and mutual information analyses to study how MUA, low-frequency LFP (15-40Hz, LFPL ), and high-frequency LFP (100-300Hz, LFPH) encoded reaching movements. The representation of kinematic parameters for direction, speed, velocity, and position were quantified and compared across these signals to be better applied in decoding models. Lastly, the results from these experiments could not have been accurately obtained without keeping careful account of the mechanical lags involved. Each of the stimuli affecting behavior had onset lags, which in some cases, varied greatly from trial to trial and could easily distorted timing effects if not accounted for. Special adaptations were constructed to precisely pinpoint display, system, and device onset lags

Comparison of Therapy Practice at Home and in the Clinic: A Retrospective Analysis of the Constant Therapy Platform Data Set

Background: Computer-based therapies can provide an affordable and practical alternative by providing frequent intervention for stroke survivors with chronic aphasia by allowing the opportunity for home exercise practice, however more evidence is needed. The goal of this retrospective analysis was to compare the time course of therapy engagement when therapy was targeted in the clinic or at home by post-stroke individuals. We examined if home users of the therapy were compliant in therapy and if this documented practice time was associated with improved outcomes similar to clinic patients who practiced under the guidance of a clinician.Methods: A retrospective analysis of anonymously aggregated data collected for 3,686 patients with post-stroke aphasia over the course of four years (2013–2017) was conducted. Participants either received therapy delivered through Constant Therapy only at home (N = 2,100) or only in the clinic (N = 1,577). Constant Therapy includes over 70 evidence-based therapies for language and cognitive skills. This program was individualized for each patient with targeted tasks that dynamically adapted to each individual's progress.Results: Patients with <60% accuracy were analyzed to determine how long it took them to reach >90% accuracy. Results showed that both home-therapy and clinic patients reached 90% accuracy on their tasks similarly (Median = 3 sessions), but the frequency of therapy was significantly different with 50% of home users receiving therapy at least every 2 days while 50% of clinic patients only had therapy once every 5 days (p < 0.001). Thus, home-therapy users were able to master tasks in a shorter time (median of 6 days) than clinic patients (median of 12 days) (p < 0.001).Conclusion: Outcomes of treatment are similar for home users and clinic patients indicating the potential usability of a home-based treatment program for rehabilitation for post-stroke aphasia

Muscle synergies after stroke are correlated with perilesional high gamma.

Movements can be factored into modules termed "muscle synergies". After stroke, abnormal synergies are linked to impaired movements; however, their neural basis is not understood. In a single subject, we examined how electrocorticography signals from the perilesional cortex were associated with synergies. The measured synergies contained a mix of both normal and abnormal patterns and were remarkably similar to those described in past work. Interestingly, we found that both normal and abnormal synergies were correlated with perilesional high gamma. Given the link between high gamma and cortical spiking, our results suggest that perilesional spiking may organize synergies after stroke

Effects of somatosensory electrical stimulation on motor function and cortical oscillations

Abstract Background Few patients recover full hand dexterity after an acquired brain injury such as stroke. Repetitive somatosensory electrical stimulation (SES) is a promising method to promote recovery of hand function. However, studies using SES have largely focused on gross motor function; it remains unclear if it can modulate distal hand functions such as finger individuation. Objective The specific goal of this study was to monitor the effects of SES on individuation as well as on cortical oscillations measured using EEG, with the additional goal of identifying neurophysiological biomarkers. Methods Eight participants with a history of acquired brain injury and distal upper limb motor impairments received a single two-hour session of SES using transcutaneous electrical nerve stimulation. Pre- and post-intervention assessments consisted of the Action Research Arm Test (ARAT), finger fractionation, pinch force, and the modified Ashworth scale (MAS), along with resting-state EEG monitoring. Results SES was associated with significant improvements in ARAT, MAS and finger fractionation. Moreover, SES was associated with a decrease in low frequency (0.9-4 Hz delta) ipsilesional parietomotor EEG power. Interestingly, changes in ipsilesional motor theta (4.8–7.9 Hz) and alpha (8.8–11.7 Hz) power were significantly correlated with finger fractionation improvements when using a multivariate model. Conclusions We show the positive effects of SES on finger individuation and identify cortical oscillations that may be important electrophysiological biomarkers of individual responsiveness to SES. These biomarkers can be potential targets when customizing SES parameters to individuals with hand dexterity deficits. Trial registration: NCT03176550; retrospectively registered

Effects of somatosensory electrical stimulation on motor function and cortical oscillations.

BackgroundFew patients recover full hand dexterity after an acquired brain injury such as stroke. Repetitive somatosensory electrical stimulation (SES) is a promising method to promote recovery of hand function. However, studies using SES have largely focused on gross motor function; it remains unclear if it can modulate distal hand functions such as finger individuation.ObjectiveThe specific goal of this study was to monitor the effects of SES on individuation as well as on cortical oscillations measured using EEG, with the additional goal of identifying neurophysiological biomarkers.MethodsEight participants with a history of acquired brain injury and distal upper limb motor impairments received a single two-hour session of SES using transcutaneous electrical nerve stimulation. Pre- and post-intervention assessments consisted of the Action Research Arm Test (ARAT), finger fractionation, pinch force, and the modified Ashworth scale (MAS), along with resting-state EEG monitoring.ResultsSES was associated with significant improvements in ARAT, MAS and finger fractionation. Moreover, SES was associated with a decrease in low frequency (0.9-4 Hz delta) ipsilesional parietomotor EEG power. Interestingly, changes in ipsilesional motor theta (4.8-7.9 Hz) and alpha (8.8-11.7 Hz) power were significantly correlated with finger fractionation improvements when using a multivariate model.ConclusionsWe show the positive effects of SES on finger individuation and identify cortical oscillations that may be important electrophysiological biomarkers of individual responsiveness to SES. These biomarkers can be potential targets when customizing SES parameters to individuals with hand dexterity deficits.Trial registrationNCT03176550; retrospectively registered

Additional file 1: Figure S2. of Effects of somatosensory electrical stimulation on motor function and cortical oscillations

(A) Placement of the rectangular electrodes overlapping the stimulation sites of the median and ulnar nerves. (B) Placement of the circular electrodes over the stimulation site of the radial nerve. (TIFF 846 kb

Histone acetylation is associated with differential gene expression in the rapid and robust memory CD8+ T-cell response

To understand the molecular basis for the rapid and robust memory T-cell responses, we examined gene expression and chromatin modification by histone H3 lysine 9 (H3K9) acetylation in resting and activated human naive and memory CD8+ T cells. We found that, although overall gene expression patterns were similar, a number of genes are differentially expressed in either memory or naive cells in their resting and activated states. To further elucidate the basis for differential gene expression, we assessed the role of histone H3K9 acetylation in differential gene expression. Strikingly, higher H3K9 acetylation levels were detected in resting memory cells, prior to their activation, for those genes that were differentially expressed following activation, indicating that hyperacetylation of histone H3K9 may play a role in selective and rapid gene expression of memory CD8+ T cells. Consistent with this model, we showed that inducing high levels of H3K9 acetylation resulted in an increased expression in naive cells of those genes that are normally expressed differentially in memory cells. Together, these findings suggest that differential gene expression mediated at least in part by histone H3K9 hyperacetylation may be responsible for the rapid and robust memory CD8+ T-cell response