Results 51 to 60 of about 2,367,946 (319)
fMRI Brain Decoding and Its Applications in Brain–Computer Interface: A Survey
Brain Sciences, 2022 Brain neural activity decoding is an important branch of neuroscience research and a key technology for the brain–computer interface (BCI). Researchers initially developed simple linear models and machine learning algorithms to classify and recognize ...
Bing Du +3 more
doaj +1 more source
Neural decoding based on probabilistic neural network [PDF]
Journal of Zhejiang University SCIENCE B, 2010 Brain-machine interface (BMI) has been developed due to its possibility to cure severe body paralysis. This technology has been used to realize the direct control of prosthetic devices, such as robot arms, computer cursors, and paralyzed muscles.
Yi, Yu +6 more
openaire +2 more sources
Real-time decoding of arm kinematics during grasping based on F5 neural spike data [PDF]
, 2017 Due to copyright restrictions, the access to the full text of this article is only available via subscription.Several studies have shown that the information related to grip type, object identity and kinematics of monkey grasping actions is available in ...
Raos, V. +7 more
core +1 more source
Neural Decoding with Hierarchical Generative Models [PDF]
Neural Computation, 2010 Recent research has shown that reconstruction of perceived images based on hemodynamic response as measured with functional magnetic resonance imaging (fMRI) is starting to become feasible. In this letter, we explore reconstruction based on a learned hierarchy of features by employing a hierarchical generative model that consists of conditional ...
Marcel van Gerven +2 more
openaire +4 more sources
Nonlinear Approaches for Neural Encoding and Decoding [PDF]
, 2020 Understanding the mapping between stimulus, behavior, and neural responses is vital for understanding sensory, motor, and general neural processing.
Batty, Eleanor
core +2 more sources
Polar codes decoding algorithm based on convolutional neural network
Dianxin kexue, 2020 In order to solve the problem that the existing Polar code decoding algorithm based on neural network can only decode short codewords (codewords length N≤64),a new decoding algorithm using convolution neural network for long codewords (N≥512) was put ...
Rui GUO, Fanchun RAN
doaj +2 more sources
Deep adversarial neural decoding
CoRR, 2017 Added appendix and updated ...
Yagmur Güçlütürk +5 more
openaire +2 more sources
Adaptive HD-sEMG decomposition: towards robust real-time decoding of neural drive [PDF]
Publisher Copyright: © 2024 The Author(s). Published by IOP Publishing LtdObjective. Neural interfacing via decomposition of high-density surface electromyography (HD-sEMG) should be robust to signal non-stationarities incurred by changes in joint pose ...
Negro, Francesco +2 more
core +4 more sources
Neural offset min-sum decoding [PDF]
2017 IEEE International Symposium on Information Theory (ISIT), 2017 Published as a conference paper at the 2017 International Symposium on Information Theory (ISIT)
Loren Lugosch, Warren J. Gross
openaire +2 more sources
Robust and accurate decoding of hand kinematics from entire spiking activity using deep learning [PDF]
, 2021 Objective. Brain–machine interfaces (BMIs) seek to restore lost motor functions in individuals with neurological disorders by enabling them to control external devices directly with their thoughts.
Ahmadi, Nur +2 more
core +1 more source