AIMC Topic: Motor Cortex

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Investigating the benefits of artificial neural networks over linear approaches to BMI decoding.

Journal of neural engineering
Brain-machine interfaces (BMI) aim to restore function to persons living with spinal cord injuries by 'decoding' neural signals into behavior. Recently, nonlinear BMI decoders have outperformed previous state-of-the-art linear decoders, but few studi...

Neural mechanisms underlying the improvement of gait disturbances in stroke patients through robot-assisted gait training based on QEEG and fNIRS: a randomized controlled study.

Journal of neuroengineering and rehabilitation
BACKGROUND: Robot-assisted gait training is more effective in improving lower limb function and walking ability in stroke patients compared to conventional rehabilitation, but the neural mechanisms remain unclear. This study aims to explore the effec...

Enhanced Brain Functional Interaction Following BCI-Guided Supernumerary Robotic Finger Training Based on Sixth-Finger Motor Imagery.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Supernumerary robotic finger (SRF) has shown unique advantages in the field of motor augmentation and rehabilitation, while the development of brain computer interface (BCI) technology has provided the possibility for direct control of SRF. However, ...

Neurorehabilitation in spinal cord injury: Increased cortical activity through tDCS and robotic gait training.

Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
OBJECTIVE: This study investigates the neurophysiological outcomes of combining robot-assisted gait training (RAGT) with active transcranial direct current stimulation (tDCS) on individuals with spinal cord injury (SCI).

Effect of Parallel Cognitive-Motor Training Tasks on Hemodynamic Responses in Robot-Assisted Rehabilitation.

Brain connectivity
Previous studies suggest that the combination of robot-assisted training with other concurrent tasks may promote the functional recovery and improvement better than the single task. It is well-established that robot-assisted rehabilitation training ...

Spatio-temporal transformers for decoding neural movement control.

Journal of neural engineering
. Deep learning tools applied to high-resolution neurophysiological data have significantly progressed, offering enhanced decoding, real-time processing, and readability for practical applications. However, the design of artificial neural networks to...

Unsupervised, piecewise linear decoding enables an accurate prediction of muscle activity in a multi-task brain computer interface.

Journal of neural engineering
Creating an intracortical brain computer interface (iBCI) capable of seamless transitions between tasks and contexts would greatly enhance user experience. However, the nonlinearity in neural activity presents challenges to computing a global iBCI de...

An ANN models cortical-subcortical interaction during post-stroke recovery of finger dexterity.

Journal of neural engineering
Finger dexterity, and finger individuation in particular, is crucial for human movement, and disruptions due to brain injury can significantly impact quality of life. Understanding the neurological mechanisms responsible for recovery is vital for eff...

Brain Activation Pattern Caused by Soft Rehabilitation Glove and Virtual Reality Scenes: A Pilot fNIRS Study.

IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Clinical studies have proved significant improvements in hand motor function in stroke patients when assisted by robotic devices. However, there were few studies on neural activity changes in the brain during execution. This study aimed to investigat...

Effects of high-definition tDCS targeting individual motor hotspot with EMG-driven robotic hand training on upper extremity motor function: a pilot randomized controlled trial.

Journal of neuroengineering and rehabilitation
BACKGROUND: Delivering HD-tDCS on individual motor hotspot with optimal electric fields could overcome challenges of stroke heterogeneity, potentially facilitating neural activation and improving motor function for stroke survivors. However, the inte...