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Grid cell modules coordination improves accuracy and reliability for spatial navigation
Grid cell modules coordination improves accuracy and reliability for spatial navigation
Most mammals efficiently overcome self-localization deviations by coordinating grid and place cells in their brain’s...
Efficient system for classifying cyclic alternating pattern phases in sleep
Efficient system for classifying cyclic alternating pattern phases in sleep
Electroencephalogram (EEG) signals are a popular tool to analyze sleep patterns. Cyclic alternating patterns (CAP) can be ...
Coherence resonance, parameter estimation and self-regulation in a thermalsensitive neuron
Coherence resonance, parameter estimation and self-regulation in a thermalsensitive neuron
In this work, two capacitors connected by a thermistor are used to explore the electrical property of double-layer membran...
Multilevel Inter-modal and Intra-modal Transformer network with domain adversarial learning for multimodal sleep staging
Multilevel Inter-modal and Intra-modal Transformer network with domain adversarial learning for multimodal sleep staging
Sleep staging identification is a fundamental task for the diagnosis of sleep disorders. With the development of biosensin...
The mechanism of a 16-Week Baduanjin intervention in altering neural inhibition responses to food cues in healthy adults - an ERP study
The mechanism of a 16-Week Baduanjin intervention in altering neural inhibition responses to food cues in healthy adults - an ERP study
The positive impact of exercise on inhibitory control has been validated in numerous studies; however, few studies have ex...
Reducing calibration efforts of SSVEP-BCIs by shallow fine-tuning-based transfer learning
Reducing calibration efforts of SSVEP-BCIs by shallow fine-tuning-based transfer learning
The utilization of transfer learning (TL), particularly through pre-training and fine-tuning, in steady-state visual evoke...
ECn-MultiBSTM: multiclass epileptic seizure classification using electro cetacean optimized bidirectional long short-term memory model
ECn-MultiBSTM: multiclass epileptic seizure classification using electro cetacean optimized bidirectional long short-term memory model
Multiclass epileptic seizureclassification aims to identify and categorize different epileptic seizure types like a non-ep...
Conditional probabilistic-based domain adaptation for cross-subject EEG-based emotion recognition
Conditional probabilistic-based domain adaptation for cross-subject EEG-based emotion recognition
Electroencephalogram (EEG)-based emotion recognition has received increasing attention in affective computing. Due to the ...
Shap-driven explainable AI with simulated annealing for optimized seizure detection using multichannel EEG signal
Shap-driven explainable AI with simulated annealing for optimized seizure detection using multichannel EEG signal
The aim of this research is to combine Explainable AI (XAI) with advanced optimization techniques to provide a unique fram...
DMPat-based SOXFE: investigations of the violence detection using EEG signals
DMPat-based SOXFE: investigations of the violence detection using EEG signals
Automatic violence detection is one of the most important research areas at the intersection of machine learning and infor...
Complexity and non-predictability in neurodynamic: gender-specific EEG dynamics uncovered via hidden markov models
Complexity and non-predictability in neurodynamic: gender-specific EEG dynamics uncovered via hidden markov models
One area of interest in neuroscience is the study of differences between male and female brains, encompassing structural, ...
Sound intensity-dependent cortical activation: implications of the electrical and vascular activity on auditory intensity
Sound intensity-dependent cortical activation: implications of the electrical and vascular activity on auditory intensity
Recent studies combining electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) have shown promisi...
EEG-derived brain connectivity in theta/alpha frequency bands increases during reading of individual words
EEG-derived brain connectivity in theta/alpha frequency bands increases during reading of individual words
Objective: Although extensive insights about the neural mechanisms of reading have been gained via magnetic and e...
Astrocytic signatures in neuronal activity: a machine learning-based identification approach
Astrocytic signatures in neuronal activity: a machine learning-based identification approach
This study investigates the expanding role of astrocytes, the predominant glial cells, in brain function, focusing on whet...
TCANet: a temporal convolutional attention network for motor imagery EEG decoding
TCANet: a temporal convolutional attention network for motor imagery EEG decoding
Decoding motor imagery electroencephalogram (MI-EEG) signals is fundamental to the development of brain–computer int...
Aberrant dynamics of the default mode network activity in patients with obsessive-compulsive disorder
Aberrant dynamics of the default mode network activity in patients with obsessive-compulsive disorder
Obsessive compulsive disorder (OCD) is a serious mental disease highly associated with the dysfunctional dynamics of brain...
EA–EEG: a novel model for efficient motor imagery EEG classification with whitening and multi-scale feature integration
EA–EEG: a novel model for efficient motor imagery EEG classification with whitening and multi-scale feature integration
Electroencephalography (EEG) is a non-invasive technique widely used in neuroscience and brain–computer interfaces (...
Visual statistical learning based on a coupled shape-position recurrent neural network model
Visual statistical learning based on a coupled shape-position recurrent neural network model
The visual system has the ability to learn the statistical regularities (temporal and/or spatial) that characterize the vi...
MBRSTCformer: a knowledge embedded local–global spatiotemporal transformer for emotion recognition
MBRSTCformer: a knowledge embedded local–global spatiotemporal transformer for emotion recognition
Emotion recognition is an essential prerequisite for realizing generalized BCI, which possesses an extensive range of appl...
Non-Gaussianity of neurotransmitters co-released from mammalian adrenal chromaffin cells
Non-Gaussianity of neurotransmitters co-released from mammalian adrenal chromaffin cells
While synaptic currents in computational neuroscience are conventionally modeled as Gaussian processes, there tends to be ...
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...
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 ...
Black-white hole pattern: an investigation on the automated chronic neuropathic pain detection using EEG signals
Black-white hole pattern: an investigation on the automated chronic neuropathic pain detection using EEG signals
Electroencephalography (EEG) signals provide information about the brain activities, this study bridges neuroscience and m...
Effect of adult hippocampal neurogenesis on pattern separation and its applications
Effect of adult hippocampal neurogenesis on pattern separation and its applications
Adult hippocampal neurogenesis (AHN) is considered essential in memory formation. The dentate gyrus neural network contain...
Resting state EEG delta-beta amplitude-amplitude coupling: a neural predictor of cortisol response under stress
Resting state EEG delta-beta amplitude-amplitude coupling: a neural predictor of cortisol response under stress
Stress is ubiquitous in daily life. Subcortical and cortical regions closely interact to respond to stress. Delta-beta cro...
Assessing the influence of latency variability on EEG classifiers - a case study of face repetition priming
Assessing the influence of latency variability on EEG classifiers - a case study of face repetition priming
Data-driven strategies have been widely used to distinguish experimental effects on single-trial EEG signals. However, how...
Cortex level connectivity between ACT-R modules during EEG-based n-back task
Cortex level connectivity between ACT-R modules during EEG-based n-back task
Finding the synchronization between Electroencephalography (EEG) and human cognition is an essential aspect of cognitive n...
Adaptive learning rate in dynamical binary environments: the signature of adaptive information processing
Adaptive learning rate in dynamical binary environments: the signature of adaptive information processing
Adaptive mechanisms of learning models play critical roles in interpreting adaptive behavior of humans and animals. Differ...
Pupil dilation and behavior as complementary measures of fear response in Mice
Pupil dilation and behavior as complementary measures of fear response in Mice
The precise assessment of emotional states in animals under the combined influence of multiple stimuli remains a challenge...
Collective behavior of an adapting synapse-based neuronal network with memristive effect and randomness
Collective behavior of an adapting synapse-based neuronal network with memristive effect and randomness
This study delves into the examination of a network of adaptive synapse neurons characterized by a small-world network top...
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