Supervised learning in spiking neural networks: A review of algorithms and evaluations
X Wang, X Lin, X Dang - Neural Networks, 2020 - Elsevier
As a new brain-inspired computational model of the artificial neural network, a spiking
neural network encodes and processes neural information through precisely timed spike …
neural network encodes and processes neural information through precisely timed spike …
human intracortical recording and neural decoding for brain–computer interfaces
DM Brandman, SS Cash… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
Brain-computer interfaces (BCIs) use neural information recorded from the brain for the
voluntary control of external devices. The development of BCI systems has largely focused …
voluntary control of external devices. The development of BCI systems has largely focused …
Rapid calibration of an intracortical brain–computer interface for people with tetraplegia
Objective. Brain–computer interfaces (BCIs) can enable individuals with tetraplegia to
communicate and control external devices. Though much progress has been made in …
communicate and control external devices. Though much progress has been made in …
Efficient and robust coding in heterogeneous recurrent networks
Cortical networks show a large heterogeneity of neuronal properties. However, traditional
coding models have focused on homogeneous populations of excitatory and inhibitory …
coding models have focused on homogeneous populations of excitatory and inhibitory …
Single-trial kernel-based functional connectivity for enhanced feature extraction in motor-related tasks
DG García-Murillo, A Alvarez-Meza… - Sensors, 2021 - mdpi.com
Motor learning is associated with functional brain plasticity, involving specific functional
connectivity changes in the neural networks. However, the degree of learning new motor …
connectivity changes in the neural networks. However, the degree of learning new motor …
Robust neural decoding by kernel regression with siamese representation learning
Objective. Brain–machine interfaces (BMIs) provide a direct pathway between the brain and
external devices such as computer cursors and prosthetics, which have great potential in …
external devices such as computer cursors and prosthetics, which have great potential in …
Eliciting naturalistic cortical responses with a sensory prosthesis via optimized microstimulation
Objective. Lost sensations, such as touch, could one day be restored by electrical
stimulation along the sensory neural pathways. Such stimulation, when informed by …
stimulation along the sensory neural pathways. Such stimulation, when informed by …
Robust closed-loop control of a cursor in a person with tetraplegia using Gaussian process regression
DM Brandman, MC Burkhart, J Kelemen… - Neural …, 2018 - direct.mit.edu
Intracortical brain computer interfaces can enable individuals with paralysis to control
external devices through voluntarily modulated brain activity. Decoding quality has been …
external devices through voluntarily modulated brain activity. Decoding quality has been …
Centered Kernel Alignment Enhancing Neural Network Pretraining for MRI‐Based Dementia Diagnosis
D Cárdenas-Peña, D Collazos-Huertas… - … methods in medicine, 2016 - Wiley Online Library
Dementia is a growing problem that affects elderly people worldwide. More accurate
evaluation of dementia diagnosis can help during the medical examination. Several …
evaluation of dementia diagnosis can help during the medical examination. Several …
Reinforcement learning in video games using nearest neighbor interpolation and metric learning
MS Emigh, EG Kriminger, AJ Brockmeier… - … Intelligence and AI …, 2014 - ieeexplore.ieee.org
Reinforcement learning (RL) has had mixed success when applied to games. Large state
spaces and the curse of dimensionality have limited the ability for RL techniques to learn to …
spaces and the curse of dimensionality have limited the ability for RL techniques to learn to …