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Memristive leaky integrate-and-fire neuron and learnable straight-through estimator in spiking neural networks
Memristive leaky integrate-and-fire neuron and learnable straight-through estimator in spiking neural networks
Compared to artificial neural networks (ANNs), spiking neural networks (SNNs) present a more biologically plausible model ...
Time–frequency–space transformer EEG decoding for spinal cord injury
Time–frequency–space transformer EEG decoding for spinal cord injury
Transformer neural networks based on multi-head self-attention are effective in several fields. To capture brain activity ...
A working memory model based on recurrent neural networks using reinforcement learning
A working memory model based on recurrent neural networks using reinforcement learning
Numerous electrophysiological experiments have reported that the prefrontal cortex (PFC) is involved in the process of wor...
Intranasal insulin effect on cognitive and/or memory impairment: a systematic review and meta-analysis
Intranasal insulin effect on cognitive and/or memory impairment: a systematic review and meta-analysis
Background: Cognitive impairment, characterized by deficits in cognitive functions and loss of delayed and immediate recal...
Functional connectivity of EEG motor rhythms after spinal cord injury
Functional connectivity of EEG motor rhythms after spinal cord injury
Spinal cord injury (SCI), which is the injury of the spinal cord site resulting in motor dysfunction, has prompted the use...
Dynamic analysis of FN–HR neural network coupled of bistable memristor and encryption application based on Fibonacci Q-Matrix
Dynamic analysis of FN–HR neural network coupled of bistable memristor and encryption application based on Fibonacci Q-Matrix
In this paper, a cosine hyperbolic memristor model is proposed with bistable asymmetric hysteresis loops. A neural network...
Automatic detection of Alzheimer’s disease from EEG signals using an improved AFS–GA hybrid algorithm
Automatic detection of Alzheimer’s disease from EEG signals using an improved AFS–GA hybrid algorithm
Alzheimer’s Disease (AD) is a neurodegenerative disorder characterized by energy diffusion and partial disconnection...
Fixed-/preassigned-time synchronization for delayed complex-valued neural networks with discontinuous activations
Fixed-/preassigned-time synchronization for delayed complex-valued neural networks with discontinuous activations
Finite-time synchronization is a crucial phenomenon observed in nonlinear complex systems, the settling time in such a dyn...
Quantitative analysis and machine learning-based interpretation of EEG signals in coma and brain-death diagnosis
Quantitative analysis and machine learning-based interpretation of EEG signals in coma and brain-death diagnosis
Electroencephalography (EEG) reflects brain activity and is crucial for diagnosing states such as coma and brain-death. Ho...
Data-driven natural computational psychophysiology in class
Data-driven natural computational psychophysiology in class
Objective. The assessment of mental fatigue (MF) and attention span in educational and healthcare settings frequently reli...
PSPN: Pseudo-Siamese Pyramid Network for multimodal emotion analysis
PSPN: Pseudo-Siamese Pyramid Network for multimodal emotion analysis
Emotion recognition plays an important role in human life and healthcare. The EEG has been extensively researched as an ob...
A new class of chaotic attractors using different activation functions in neuron with multi dendrites
A new class of chaotic attractors using different activation functions in neuron with multi dendrites
This paper introduces a novel class of chaotic attractors by lever- aging different activation functions within neurons po...
A novel dual-step transfer framework based on domain selection and feature alignment for motor imagery decoding
A novel dual-step transfer framework based on domain selection and feature alignment for motor imagery decoding
In brain-computer interfaces (BCIs) based on motor imagery (MI), reducing calibration time is gradually becoming an urgent...
MSHANet: a multi-scale residual network with hybrid attention for motor imagery EEG decoding
MSHANet: a multi-scale residual network with hybrid attention for motor imagery EEG decoding
EEG decoding plays a crucial role in the development of motor imagery brain-computer interface. Deep learning has great po...
Development of a humanoid robot control system based on AR-BCI and SLAM navigation
Development of a humanoid robot control system based on AR-BCI and SLAM navigation
Brain-computer interface (BCI)-based robot combines BCI and robotics technology to realize the brain’s intention to ...
Chaos analysis of nonlinear variable order fractional hyperchaotic Chen system utilizing radial basis function neural network
Chaos analysis of nonlinear variable order fractional hyperchaotic Chen system utilizing radial basis function neural network
This research explores the various chaotic features of the hyperchaotic Chen dynamical system within a variable order frac...
Quantifying harmony between direct and indirect pathways in the basal ganglia: healthy and Parkinsonian states
Quantifying harmony between direct and indirect pathways in the basal ganglia: healthy and Parkinsonian states
The basal ganglia (BG) show a variety of functions for motor and cognition. There are two competitive pathways in the BG; ...
Multiresolution feature fusion for smart diagnosis of schizophrenia in adolescents using EEG signals
Multiresolution feature fusion for smart diagnosis of schizophrenia in adolescents using EEG signals
Numerous studies on early detection of schizophrenia (SZ) have utilized all available channels or employed set of a few ti...
EEG-based schizophrenia detection using fusion of effective connectivity maps and convolutional neural networks with transfer learning
EEG-based schizophrenia detection using fusion of effective connectivity maps and convolutional neural networks with transfer learning
Schizophrenia (SZ) is a serious mental disorder that can mainly be distinguished by symptoms including delusions and hallu...
Sonification of electronic dynamical systems: Spectral characteristics and sound evaluation using EEG features
Sonification of electronic dynamical systems: Spectral characteristics and sound evaluation using EEG features
Chaos is often described as the limited development of nonlinear dynamic systems that create intricate and non-repetitive ...
Decoded EEG neurofeedback-guided cognitive reappraisal training for emotion regulation
Decoded EEG neurofeedback-guided cognitive reappraisal training for emotion regulation
Neurofeedback, when combined with cognitive reappraisal, offers promising potential for emotion regulation training. Howev...
An effective classification approach for EEG-based motor imagery tasks combined with attention mechanisms
An effective classification approach for EEG-based motor imagery tasks combined with attention mechanisms
Currently, electroencephalogram (EEG)-based motor imagery (MI) signals have been received extensive attention, which can a...
Sustained attention detection in humans using a prefrontal theta-EEG rhythm
Sustained attention detection in humans using a prefrontal theta-EEG rhythm
This research highlights the importance of the prefrontal theta-EEG rhythm in sustained attention monitoring over the Fp1 ...
Involvement of prelimbic cortex neurons and related circuits in the acquisition of a cooperative learning by pairs of rats
Involvement of prelimbic cortex neurons and related circuits in the acquisition of a cooperative learning by pairs of rats
Social behaviors such as cooperation are crucial for mammals. A deeper knowledge of the neuronal mechanisms underlying coo...
Computational model of the spatiotemporal synergetic system dynamics of calcium, IP3 and dopamine in neuron cells
Computational model of the spatiotemporal synergetic system dynamics of calcium, IP3 and dopamine in neuron cells
The functioning of several cellular processes in neuron cells relies on the interplay between multiple systems, such as ca...
Research progress of epileptic seizure prediction methods based on EEG
Research progress of epileptic seizure prediction methods based on EEG
At present, at least 30% of refractory epilepsy patients in the world cannot be effectively controlled and treated. The su...
A novel paradigm for observational learning in rats
A novel paradigm for observational learning in rats
The ability to learn by observing the behavior of others is energy efficient and brings high survival value, making it an ...
Synchronization of delayed coupled neurons with multiple synaptic connections
Synchronization of delayed coupled neurons with multiple synaptic connections
Synchronization is a key feature of the brain dynamics and is necessary for information transmission across brain regions ...
A distributed theta network of error generation and processing in aging
A distributed theta network of error generation and processing in aging
Based on previous concepts that a distributed theta network with a central “hub” in the medial frontal cortex ...