AIMC Topic: Motor Cortex
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Clustering Neural Patterns in Kernel Reinforcement Learning Assists Fast Brain Control in Brain-Machine Interfaces.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Aug 9, 2019
Neuroprosthesis enables the brain control on the external devices purely using neural activity for paralyzed people. Supervised learning decoders recalibrate or re-fit the discrepancy between the desired target and decoder's output, where the correct...
Non-Invasive Modulation and Robotic Mapping of Motor Cortex in the Developing Brain.
Journal of visualized experiments : JoVE
Jul 1, 2019
Mapping the motor cortex with transcranial magnetic stimulation (TMS) has potential to interrogate motor cortex physiology and plasticity but carries unique challenges in children. Similarly, transcranial direct current stimulation (tDCS) can improve...
Effects of Transcranial Direct Current Stimulation (tDCS) Combined With Wrist Robot-Assisted Rehabilitation on Motor Recovery in Subacute Stroke Patients: A Randomized Controlled Trial.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Jun 3, 2019
Both transcranial direct current stimulation (tDCS) and wrist robot-assisted training have demonstrated to be promising approaches for stroke rehabilitation. However, the effects of the combination of the two treatments in subacute stroke patients ar...
Algorithms
Female
Aged
Aged, 80 and over
Humans
Middle Aged
Adolescent
Treatment Outcome
Recovery of Function
Robotics
Young Adult
Adult
Biomechanical Phenomena
Male
Motor Cortex
Electrodes
Upper Extremity
Stroke Rehabilitation
Transcranial Direct Current Stimulation
Single-Blind Method
Electroencephalography
Wrist
Combined Modality Therapy
Decoding Movements from Cortical Ensemble Activity Using a Long Short-Term Memory Recurrent Network.
Neural computation
Apr 12, 2019
Although many real-time neural decoding algorithms have been proposed for brain-machine interface (BMI) applications over the years, an optimal, consensual approach remains elusive. Recent advances in deep learning algorithms provide new opportunitie...
Human electrocortical dynamics while stepping over obstacles.
Scientific reports
Mar 18, 2019
To better understand human brain dynamics during visually guided locomotion, we developed a method of removing motion artifacts from mobile electroencephalography (EEG) and studied human subjects walking and running over obstacles on a treadmill. We ...
Sensorimotor Robotic Measures of tDCS- and HD-tDCS-Enhanced Motor Learning in Children.
Neural plasticity
Dec 18, 2018
Transcranial direct-current stimulation (tDCS) enhances motor learning in adults. We have demonstrated that anodal tDCS and high-definition (HD) tDCS of the motor cortex can enhance motor skill acquisition in children, but behavioral mechanisms remai...
Machine learning provides novel neurophysiological features that predict performance to inhibit automated responses.
Scientific reports
Nov 2, 2018
Neurophysiological features like event-related potentials (ERPs) have long been used to identify different cognitive sub-processes that may contribute to task performance. It has however remained unclear whether "classical" ERPs are truly the best re...
Robotic TMS mapping of motor cortex in the developing brain.
Journal of neuroscience methods
Aug 16, 2018
BACKGROUND: The human motor cortex can be mapped safely and painlessly with transcranial magnetic stimulation (TMS) to explore neurophysiology in health and disease. Human error likely contributes to heterogeneity of such TMS measures. Here, we aimed...
Interhemispheric dominance switching in a neural network model for birdsong.
Journal of neurophysiology
Jun 20, 2018
Male zebra finches produce a sequence-invariant set of syllables, separated by short inspiratory gaps. These songs are learned from an adult tutor and maintained throughout life, making them a tractable model system for learned, sequentially ordered ...
Unsupervised Discovery of Demixed, Low-Dimensional Neural Dynamics across Multiple Timescales through Tensor Component Analysis.
Neuron
Jun 7, 2018
Perceptions, thoughts, and actions unfold over millisecond timescales, while learned behaviors can require many days to mature. While recent experimental advances enable large-scale and long-term neural recordings with high temporal fidelity, it rema...
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