scholarly journals Stopping vs Resting state during motor imagery paradigm

2021 ◽  
Author(s):  
Bastien Orset ◽  
Kyuhwa Lee ◽  
Ricardo Chavarriaga ◽  
Jose del R Millan
Keyword(s):  
Motor Imagery ◽  
Resting State ◽  
Beta Band ◽  
Movement Onset ◽  
Major Drawback ◽  
Non Invasive ◽  
Control Brain ◽  
Motor Actions ◽  
Imagined Movement ◽  
Termination Process

Current non-invasive Brain Machine interfaces commonly rely on the decoding of sustained motor imagery activity (MI). This approach enables a user to control brain-actuated devices by triggering predetermined motor actions. One major drawback of such strategy is that users are not trained to stop their actions. Indeed, the termination process involved in BMI is poorly understood with most of the studies assuming that the end of an MI action is similar to the resting state. Here we hypothesize that the process of stopping MI (MI termination) and resting state are two different processes that should be decoded independently due to the exhibition of different neural pattens. We compared the detection of both states transitions of an imagined movement, i.e. rest-to-movement (onset) and movement-to-rest (offset). Our results shows that both decoders show significant differences in term of performances and latency (N=17 Subjects) with the offset decoder able to detect faster and better MI termination. While studying this difference, we found that the offset decoder is primarily based on the use of features in Beta band which appears earlier. Based on this finding, we also proposed a Random Forrest based decoder which enable to distinguish three classes (MI, MI termination and REST).

scholarly journals Implicit Motor Imagery and the Lateral Occipitotemporal Cortex: Hints for Tailoring Non-Invasive Brain Stimulation

2020 ◽  
Vol 17 (16) ◽  
pp. 5851 ◽  
Author(s):  
Massimiliano Conson ◽  
Roberta Cecere ◽  
Chiara Baiano ◽  
Francesco De Bellis ◽  
Gabriela Forgione ◽  
...  
Keyword(s):  
Motor Imagery ◽  
Brain Stimulation ◽  
Repetitive Transcranial Magnetic Stimulation ◽  
Dominant Hand ◽  
Non Invasive ◽  
Implicit Motor ◽  
Left And Right ◽  
Occipitotemporal Cortex ◽  
Biomechanical Effect ◽  
Motor Representations

Background: Recent evidence has converged in showing that the lateral occipitotemporal cortex is over-recruited during implicit motor imagery in elderly and in patients with neurodegenerative disorders, such as Parkinson’s disease. These data suggest that when automatically imaging movements, individuals exploit neural resources in the visual areas to compensate for the decline in activating motor representations. Thus, the occipitotemporal cortex could represent a cortical target of non-invasive brain stimulation combined with cognitive training to enhance motor imagery performance. Here, we aimed at shedding light on the role of the left and right lateral occipitotemporal cortex in implicit motor imagery. Methods: We applied online, high-frequency, repetitive transcranial magnetic stimulation (rTMS) over the left and right lateral occipitotemporal cortex while healthy right-handers judged the laterality of hand images. Results: With respect to the sham condition, left hemisphere stimulation specifically reduced accuracy in judging the laterality of right-hand images. Instead, the hallmark of motor simulation, i.e., the biomechanical effect, was never influenced by rTMS. Conclusions: The lateral occipitotemporal cortex seems to be involved in mental representation of the dominant hand, at least in right-handers, but not in reactivating sensorimotor information during simulation. These findings provide useful hints for developing combined brain stimulation and behavioural trainings to improve motor imagery.

scholarly journals 2190 Longitudinal changes in EEG power envelope connectivity are proportional to motor recovery in chronic stroke patients

2018 ◽  
Vol 2 (S1) ◽  
pp. 17-17
Author(s):  
Joseph B. Humphries ◽  
David T. Bundy ◽  
Eric C. Leuthardt ◽  
Thy N. Huskey
Keyword(s):  
Motor Cortex ◽  
Motor Imagery ◽  
Stroke Rehabilitation ◽  
Brain Computer Interface ◽  
Chronic Stroke ◽  
Motor Recovery ◽  
Stroke Recovery ◽  
Computer Interface ◽  
Beta Band ◽  
Stroke Patients

OBJECTIVES/SPECIFIC AIMS: The objective of this study is to determine the degree to which the use of a contralesionally-controlled brain-computer interface for stroke rehabilitation drives change in interhemispheric motor cortical activity. METHODS/STUDY POPULATION: Ten chronic stroke patients were trained in the use of a brain-computer interface device for stroke recovery. Patients perform motor imagery to control the opening and closing of a motorized hand orthosis. This device was sent home with patients for 12 weeks, and patients were asked to use the device 1 hour per day, 5 days per week. The Action Research Arm Test (ARAT) was performed at 2-week intervals to assess motor function improvement. Before the active motor imagery task, patients were asked to quietly rest for 90 seconds before the task to calibrate recording equipment. EEG signals were acquired from 2 electrodes—one each centered over left and right primary motor cortex. Signals were preprocessed with a 60 Hz notch filter for environmental noise and referenced to the common average. Power envelopes for 1 Hz frequency bands (1–30 Hz) were calculated through Gabor wavelet convolution. Correlations between electrodes were then calculated for each frequency envelope on the first and last 5 runs, thus generating one correlation value per subject, per run. The chosen runs approximately correspond to the first and last week of device usage. These correlations were Fisher Z-transformed for comparison. The first and last 5 run correlations were averaged separately to estimate baseline and final correlation values. A difference was then calculated between these averages to determine correlation change for each frequency. The relationship between beta-band correlation changes (13–30 Hz) and the change in ARAT score was determined by calculating a Pearson correlation. RESULTS/ANTICIPATED RESULTS: Beta-band inter-electrode correlations tended to decrease more in patients achieving greater motor recovery (Pearson’s r=−0.68, p=0.031). A similar but less dramatic effect was observed with alpha-band (8–12 Hz) correlation changes (Pearson’s r=−0.42, p=0.22). DISCUSSION/SIGNIFICANCE OF IMPACT: The negative correlation between inter-electrode power envelope correlations in the beta frequency band and motor recovery indicates that activity in the motor cortex on each hemisphere may become more independent during recovery. The role of the unaffected hemisphere in stroke recovery is currently under debate; there is conflicting evidence regarding whether it supports or inhibits the lesioned hemisphere. These findings may support the notion of interhemispheric inhibition, as we observe less in common between activity in the 2 hemispheres in patients successfully achieving recovery. Future neuroimaging studies with greater spatial resolution than available with EEG will shed further light on changes in interhemispheric communication that occur during stroke rehabilitation.

scholarly journals A Pilot Study Investigating a Novel Non-Linear Measure of Eyes Open versus Eyes Closed EEG Synchronization in People with Alzheimer’s Disease and Healthy Controls

2018 ◽  
Vol 8 (7) ◽  
pp. 134 ◽  
Author(s):  
Daniel Blackburn ◽  
Yifan Zhao ◽  
Matteo De Marco ◽  
Simon Bell ◽  
Fei He ◽  
...  
Keyword(s):  
Pilot Study ◽  
Resting State ◽  
Low Cost ◽  
Linear Measure ◽  
Ageing Population ◽  
Healthy Controls ◽  
Causality Test ◽  
Non Invasive ◽  
Eyes Closed ◽  
Eyes Open

Background: The incidence of Alzheimer disease (AD) is increasing with the ageing population. The development of low cost non-invasive diagnostic aids for AD is a research priority. This pilot study investigated whether an approach based on a novel dynamic quantitative parametric EEG method could detect abnormalities in people with AD. Methods: 20 patients with probable AD, 20 matched healthy controls (HC) and 4 patients with probable fronto temporal dementia (FTD) were included. All had detailed neuropsychology along with structural, resting state fMRI and EEG. EEG data were analyzed using the Error Reduction Ratio-causality (ERR-causality) test that can capture both linear and nonlinear interactions between different EEG recording areas. The 95% confidence intervals of EEG levels of bi-centroparietal synchronization were estimated for eyes open (EO) and eyes closed (EC) states. Results: In the EC state, AD patients and HC had very similar levels of bi-centro parietal synchronization; but in the EO resting state, patients with AD had significantly higher levels of synchronization (AD = 0.44; interquartile range (IQR) 0.41 vs. HC = 0.15; IQR 0.17, p < 0.0001). The EO/EC synchronization ratio, a measure of the dynamic changes between the two states, also showed significant differences between these two groups (AD ratio 0.78 versus HC ratio 0.37 p < 0.0001). EO synchronization was also significantly different between AD and FTD (FTD = 0.075; IQR 0.03, p < 0.0001). However, the EO/EC ratio was not informative in the FTD group due to very low levels of synchronization in both states (EO and EC). Conclusion: In this pilot work, resting state quantitative EEG shows significant differences between healthy controls and patients with AD. This approach has the potential to develop into a useful non-invasive and economical diagnostic aid in AD.

scholarly journals Nanomaterial Lipid-Based Carrier for Non-Invasive Capsaicin Delivery; Manufacturing Scale-Up and Human Irritation Assessment

Molecules ◽  
2020 ◽  
Vol 25 (23) ◽  
pp. 5575
Author(s):  
Phunsuk Anantaworasakul ◽  
Songyot Anuchapreeda ◽  
Songwut Yotsawimonwat ◽  
Ornchuma Naksuriya ◽  
Suree Lekawanvijit ◽  
...  
Keyword(s):  
Pain Treatment ◽  
Skin Irritation ◽  
Scale Up ◽  
High Strength ◽  
Skin Layer ◽  
Sustained Drug Release ◽  
Major Drawback ◽  
Non Invasive ◽  
Chili Peppers ◽  
Physical And Chemical

Capsaicin is an active compound in chili peppers (Capsicum chinense) that has been approved for chronic pain treatment. The topical application of high-strength capsaicin has been proven to reduce pain; however, skin irritation is a major drawback. The aim of this study was to investigate an appropriate and scalable technique for preparing nanostructured lipid carriers (NLCs) containing 0.25% capsaicin from capsicum oleoresin (NLC_C) and to evaluate the irritation of human skin by chili-extract-loaded NLCs incorporated in a gel formulation (Gel NLC_C). High-shear homogenization with high intensity (10,000 rpm) was selected to create uniform nanoparticles with a size range from 106 to 156 nm. Both the NLC_C and Gel NLC_C formulations expressed greater physical and chemical stabilities than the free chili formulation. Release and porcine biopsy studies revealed the sustained drug release and significant permeation of the NLCs through the outer skin layer, distributing in the dermis better than the free compounds. Finally, the alleviation of irritation and the decrease in uncomfortable feelings following the application of the Gel NLC_C formulation were compared to the effects from a chili gel and a commercial product in thirty healthy volunteers. The chili-extract-loaded NLCs were shown to be applicable for the transdermal delivery of capsaicin whilst minimizing skin irritation, the major noncompliance cause of patients.

Channel Selection for Optimal EEG Measurement in Motor Imagery-Based Brain-Computer Interfaces

2020 ◽  
pp. 2150003
Author(s):  
Pasquale Arpaia ◽  
Francesco Donnarumma ◽  
Antonio Esposito ◽  
Marco Parvis
Keyword(s):  
Motor Imagery ◽  
Classification Accuracy ◽  
State Of The Art ◽  
Binary Classification ◽  
Brain Computer Interfaces ◽  
Eeg Signals ◽  
Non Invasive ◽  
Computer Interfaces ◽  
Selection For ◽  
A Performance

A method for selecting electroencephalographic (EEG) signals in motor imagery-based brain-computer interfaces (MI-BCI) is proposed for enhancing the online interoperability and portability of BCI systems, as well as user comfort. The attempt is also to reduce variability and noise of MI-BCI, which could be affected by a large number of EEG channels. The relation between selected channels and MI-BCI performance is therefore analyzed. The proposed method is able to select acquisition channels common to all subjects, while achieving a performance compatible with the use of all the channels. Results are reported with reference to a standard benchmark dataset, the BCI competition IV dataset 2a. They prove that a performance compatible with the best state-of-the-art approaches can be achieved, while adopting a significantly smaller number of channels, both in two and in four tasks classification. In particular, classification accuracy is about 77–83% in binary classification with down to 6 EEG channels, and above 60% for the four-classes case when 10 channels are employed. This gives a contribution in optimizing the EEG measurement while developing non-invasive and wearable MI-based brain-computer interfaces.

Motor Imagery Training During Arm Immobilization Prevents Corticomotor Idling: An EEG Resting-State Analysis

2020 ◽  
Vol 33 (3) ◽  
pp. 327-335
Author(s):  
Ursula Debarnot ◽  
Franck Di Rienzo ◽  
Sebastien Daligault ◽  
Sophie Schwartz
Keyword(s):  
Motor Imagery ◽  
Resting State ◽  
Imagery Training ◽  
State Analysis
Sign in / Sign up

Export Citation Format

Share Document