AIMC Topic: Motor Cortex
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Robot-Guided Neuronavigated Repetitive Transcranial Magnetic Stimulation (rTMS) in Central Neuropathic Pain.
Archives of physical medicine and rehabilitation
May 9, 2018
OBJECTIVES: To confirm and extend previous results involving repetitive transcranial magnetic stimulation (rTMS) aimed at alleviating refractory central neuropathic pain (CNP). To evaluate pain relief in detail and to assess ongoing benefits after on...
Muscleless motor synergies and actions without movements: From motor neuroscience to cognitive robotics.
Physics of life reviews
Apr 27, 2018
Emerging trends in neurosciences are providing converging evidence that cortical networks in predominantly motor areas are activated in several contexts related to 'action' that do not cause any overt movement. Indeed for any complex body, human or e...
Resting-state functional connectivity predicts the ability to adapt arm reaching in a robot-mediated force field.
NeuroImage
Mar 26, 2018
Motor deficits are common outcomes of neurological conditions such as stroke. In order to design personalised motor rehabilitation programmes such as robot-assisted therapy, it would be advantageous to predict how a patient might respond to such trea...
Ongoing brain rhythms shape I-wave properties in a computational model.
Brain stimulation
Mar 20, 2018
BACKGROUND: Responses to transcranial magnetic stimulation (TMS) are notoriously variable. Previous studies have observed a dependence of TMS-induced responses on ongoing brain activity, for instance sensorimotor rhythms. This suggests an opportunity...
Deep learning for hybrid EEG-fNIRS brain-computer interface: application to motor imagery classification.
Journal of neural engineering
Feb 15, 2018
OBJECTIVE: Brain-computer interface (BCI) refers to procedures that link the central nervous system to a device. BCI was historically performed using electroencephalography (EEG). In the last years, encouraging results were obtained by combining EEG ...
Combining robotic training and inactivation of the healthy hemisphere restores pre-stroke motor patterns in mice.
eLife
Dec 27, 2017
Focal cortical stroke often leads to persistent motor deficits, prompting the need for more effective interventions. The efficacy of rehabilitation can be increased by 'plasticity-stimulating' treatments that enhance experience-dependent modification...
Emergent coordination underlying learning to reach to grasp with a brain-machine interface.
Journal of neurophysiology
Dec 13, 2017
The development of coordinated reach-to-grasp movement has been well studied in infants and children. However, the role of motor cortex during this development is unclear because it is difficult to study in humans. We took the approach of using a bra...
A cryptography-based approach for movement decoding.
Nature biomedical engineering
Dec 12, 2017
Brain decoders use neural recordings to infer the activity or intent of a user. To train a decoder, one generally needs to infer the measured variables of interest (covariates) from simultaneously measured neural activity. However, there are cases fo...
A Deep Learning Scheme for Motor Imagery Classification based on Restricted Boltzmann Machines.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Aug 17, 2016
Motor imagery classification is an important topic in brain-computer interface (BCI) research that enables the recognition of a subject's intension to, e.g., implement prosthesis control. The brain dynamics of motor imagery are usually measured by el...
Reproducibility of Results
Movement
Sensitivity and Specificity
Humans
Signal Processing, Computer-Assisted
Evoked Potentials, Motor
Fourier Analysis
Brain Mapping
Neural Networks, Computer
Intention
Electroencephalography
Machine Learning
Motor Cortex
Pattern Recognition, Automated
Algorithms
Imagination
Brain-Computer Interfaces
A cortically-inspired model for inverse kinematics computation of a humanoid finger with mechanically coupled joints.
Bioinspiration & biomimetics
May 19, 2016
The human hand's versatility allows for robust and flexible grasping. To obtain such efficiency, many robotic hands include human biomechanical features such as fingers having their two last joints mechanically coupled. Although such coupling enables...
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