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The Neural Decoding Toolbox [PDF]
Frontiers in Neuroinformatics, 2013 Population decoding is a powerful way to analyze neural data, however currently only a small percentage of systems neuroscience researchers use this method. In order to increase the use of population decoding, we have created the Neural Decoding Toolbox (
Ethan eMeyers
doaj +9 more sources
Machine Learning for Neural Decoding. [PDF]
eNeuro, 2020 Despite rapid advances in machine learning tools, the majority of neural decoding approaches still use traditional methods. Modern machine learning tools, which are versatile and easy to use, have the potential to significantly improve decoding ...
Glaser JI +5 more
europepmc +9 more sources
Neural decoding of music from the EEG. [PDF]
Sci Rep, 2023 Neural decoding models can be used to decode neural representations of visual, acoustic, or semantic information. Recent studies have demonstrated neural decoders that are able to decode accoustic information from a variety of neural signal types ...
Daly I.
europepmc +5 more sources
Towards in vivo neural decoding. [PDF]
Biomed Eng Lett, 2022 Conventional spike sorting and motor intention decoding algorithms are mostly implemented on an external computing device, such as a personal computer. The innovation of high-resolution and high-density electrodes to record the brain's activity at the single neuron level may eliminate the need for spike sorting altogether while potentially enabling in ...
Valencia D, Alimohammad A.
europepmc +4 more sources
A generic neural network model to estimate populational neural activity for robust neural decoding [PDF]
Computers in Biology and Medicine, 2022 BACKGROUND Robust and continuous neural decoding is crucial for reliable and intuitive neural-machine interactions. This study developed a novel generic neural network model that can continuously predict finger forces based on decoded populational ...
Rinku Roy, Derek Kamper, Xiaogang Hu
exaly +3 more sources
Neural Decoding for Intracortical Brain-Computer Interfaces. [PDF]
Cyborg Bionic Syst, 2023 Brain–computer interfaces have revolutionized the field of neuroscience by providing a solution for paralyzed patients to control external devices and improve the quality of daily life.
Dong Y +5 more
europepmc +2 more sources
Minimally invasive implantation of scalable high-density cortical microelectrode arrays for multimodal neural decoding and stimulation. [PDF]
Nat Biomed EngHigh-bandwidth brain–computer interfaces rely on invasive surgical procedures or brain-penetrating electrodes. Here we describe a cortical 1,024-channel thin-film microelectrode array and we demonstrate its minimally invasive surgical delivery that ...
Hettick M +21 more
europepmc +2 more sources
Robust neural decoding with low-density EEG [PDF]
Scientific ReportsHigh-density Electroencephalography (EEG) recording enhances spatial resolution for neural signal decoding, yet the relationship between electrode density and decoding performance remains unclear.
Ling Huang +2 more
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Neural Decoding With Optimization of Node Activations [PDF]
IEEE Communications Letters, 2022 The problem of maximum likelihood decoding with a neural decoder for error-correcting code is considered. It is shown that the neural decoder can be improved with two novel loss terms on the node’s activations.
Eliya Nachmani, Yair Be’ery
semanticscholar +3 more sources
Neural Decoding of EEG Signals with Machine Learning: A Systematic Review. [PDF]
Brain Sci, 2021 Electroencephalography (EEG) is a non-invasive technique used to record the brain’s evoked and induced electrical activity from the scalp. Artificial intelligence, particularly machine learning (ML) and deep learning (DL) algorithms, are increasingly ...
Saeidi M +6 more
europepmc +2 more sources