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A dual-state generic memristor–neuron coupled system for pain modulation and chaotic dynamics research
A dual-state generic memristor–neuron coupled system for pain modulation and chaotic dynamics research
The nonlinear dynamics of neuronal firing play a key role in understanding modulation mechanisms in excitable systems. In ...
Glutamate receptors as regulators of synaptic plasticity in neuropsychiatric disorders: pathological insight and translational perspectives
Glutamate receptors as regulators of synaptic plasticity in neuropsychiatric disorders: pathological insight and translational perspectives
Glutamate receptors (GluRs) are central regulators of synaptic plasticity, a fundamental physiological process underlying ...
Thermodynamic neural networks and intersection theory: an ontological hypothesis of emergent intelligence
Thermodynamic neural networks and intersection theory: an ontological hypothesis of emergent intelligence
This article proposes a new ontological framework for describing cognitive processes, grounded in intersection theory and ...
A MBPAF-memristive Hopfield neural network and its application in image encryption
A MBPAF-memristive Hopfield neural network and its application in image encryption
The complexity of neural dynamics heavily depends on the nonlinear activation functions, and a mixed-bipower activation fu...
Dynamical analysis of a mean firing rate model in Parkinson’s disease
Dynamical analysis of a mean firing rate model in Parkinson’s disease
The generation of pathological oscillations in Parkinson’s disease(PD) is closely linked to the synchronous evolutio...
Classification of consciousness disorders based on graph convolution and attention mechanism
Classification of consciousness disorders based on graph convolution and attention mechanism
This study develops an interpretable, task-adaptive EEG diagnostic framework to overcome the subjectivity and time burden ...
Exploring electromagnetic induction and astrocyte influence in excitatory-inhibitory coupling neuron network
Exploring electromagnetic induction and astrocyte influence in excitatory-inhibitory coupling neuron network
This study investigates how electromagnetic induction and astrocytic modulation jointly influence firing dynamics and sync...
Extinction reshapes SWR-coupled reactivation of behavior-defined assembly templates and auditory responses during sleep in the hippocampus and auditory cortex
Extinction reshapes SWR-coupled reactivation of behavior-defined assembly templates and auditory responses during sleep in the hippocampus and auditory cortex
Sleep supports memory processing, and hippocampal sharp-wave ripples (SWRs) are associated with the re-expression of wakin...
Analytical exploration of fractional neural wave structures and their stability characteristics
Analytical exploration of fractional neural wave structures and their stability characteristics
The nonlinear fractional soliton neuron model is used in many complicated domains, including fluid mechanics, applied scie...
Rosmarinic acid mitigates age-related loss of EEG complexity in temporal cortex: a recurrence quantification analysis
Rosmarinic acid mitigates age-related loss of EEG complexity in temporal cortex: a recurrence quantification analysis
Physiological aging is associated with progressive changes in brain function, including neural oscillations. Recurrence Qu...
Study of sequential emotional dynamics: a LSDVG approach with reduced electrode configuration
Study of sequential emotional dynamics: a LSDVG approach with reduced electrode configuration
Emotion recognition plays a prominent role in adaptive healthcare and human-computer interaction. Among various techniques...
Acas-eer: attention-based CNN architecture search with spatial-spectral feature for emotional EEG recognition
Acas-eer: attention-based CNN architecture search with spatial-spectral feature for emotional EEG recognition
Electroencephalogram (EEG)-based analysis of emotional states is important for health assessment, emotion monitoring, and ...
Fundamental questions on closed-loop neuromodulation: a control theory perspective
Fundamental questions on closed-loop neuromodulation: a control theory perspective
Closed-loop neuromodulation aims to adjust therapeutic stimulation in real time based on ongoing neural or physiological s...
Robust decoding for MI-EEG: a hybrid transformer network using multi-perspective collaborative attention and dynamic hyperbolic tangent
Robust decoding for MI-EEG: a hybrid transformer network using multi-perspective collaborative attention and dynamic hyperbolic tangent
Deep learning methods have been extensively applied in brain-computer interface (BCI) systems based on motor imagery (MI) ...
Mechanisms of taVNS-induced working memory enhancement: a multimodal fNIRS–HRV–MEP study
Mechanisms of taVNS-induced working memory enhancement: a multimodal fNIRS–HRV–MEP study
Transcutaneous auricular vagus nerve stimulation (taVNS) has emerged as a promising neuromodulation technique for enhancin...
Changes in aperiodic EEG activity following acupuncture stimulation in stroke
Changes in aperiodic EEG activity following acupuncture stimulation in stroke
Electroencephalography (EEG) enables the direct measurement of stroke-related brain activity, which is crucial for objecti...
The AHEPA EEG benchmark: setting the standard for machine learning in dementia diagnosis, a scoping review
The AHEPA EEG benchmark: setting the standard for machine learning in dementia diagnosis, a scoping review
Accurate and reproducible electroencephalography (EEG)-based classification of dementia remains a key challenge in computa...
Firing behaviors of a neuron with two memristor channels
Firing behaviors of a neuron with two memristor channels
The nonlinear circuit can achieve the functionality and controllability by adding functional electronic components. A nonl...
Do all roads lead to Rome? The challenges of building brain-like machines
Do all roads lead to Rome? The challenges of building brain-like machines
Revealing the working mechanisms of the brain and constructing brain-like machines has long been a goal of humanity. Howev...
Reliable resting-state EEG connectivity measures reveal brain network destabilization and cognitive decoupling following prolonged extreme working conditions
Reliable resting-state EEG connectivity measures reveal brain network destabilization and cognitive decoupling following prolonged extreme working conditions
This study aimed to characterize alterations in functional brain network organization in miners with approximately ten yea...
Enhancing performance of SSVEP-based visual acuity via exploiting subject-specific information
Enhancing performance of SSVEP-based visual acuity via exploiting subject-specific information
This study sought to enhance visual acuity assessment using steady-state visual evoked potentials (SSVEPs) through subject...
A hybrid deep learning architectures and feature extraction techniques for alzheimer disease recognition
A hybrid deep learning architectures and feature extraction techniques for alzheimer disease recognition
Alzheimer's disease (AD) is one of the common forms of dementia and is tremendously increasing throughout the world. T...
Analyzing mental disorders with a CNN-GRU deep learning model on motor activity
Analyzing mental disorders with a CNN-GRU deep learning model on motor activity
Mood disorders can significantly interfere with daily life, ranging from mild to severe, impacting relationships, work, an...
Dynamics study of double-column model and its application in epilepsy EEG
Dynamics study of double-column model and its application in epilepsy EEG
The human brain constitutes a highly complex nonlinear network, comprising billions of interconnected neurons capable of r...
Msst-eegnet: multi-scale spatio-temporal feature extraction using inception and temporal pyramid pooling for motor imagery classification
Msst-eegnet: multi-scale spatio-temporal feature extraction using inception and temporal pyramid pooling for motor imagery classification
Motor imagery classification is an essential component of Brain-computer interface systems to interpret and recognize brai...
Towards a transparent and interpretable AI model for medical image classifications
Towards a transparent and interpretable AI model for medical image classifications
The integration of artificial intelligence (AI) into medicine is remarkable, offering advanced diagnostic and therapeutic ...
Electroencephalography evidence of functional connectivity modulation and its correlation with bimanual visuomotor learning
Electroencephalography evidence of functional connectivity modulation and its correlation with bimanual visuomotor learning
Recent studies have shown that neuroplasticity related to sensorimotor adaptation can occur within short time frames, rang...
Effects of different frequencies of transcranial alternating current stimulation on emotion and emotion regulation
Effects of different frequencies of transcranial alternating current stimulation on emotion and emotion regulation
Emotion regulation is crucial in daily life, and transcranial alternating current stimulation (tACS) has the potential to ...
Dynamical insights from a heterogeneous whole-brain model of pre vs. post visual-motor task
Dynamical insights from a heterogeneous whole-brain model of pre vs. post visual-motor task
Visual-motor task processing relies on neurovascular coupling (NVC), a neuro-hemodynamic interaction phenomenon. The brain...
Complex nonlinear mechanisms for reduced response of hair bundle modulated by efferent nerve for protecting auditory function
Complex nonlinear mechanisms for reduced response of hair bundle modulated by efferent nerve for protecting auditory function
As the ear’s sensory receptors, hair cells detect sound vibrations via their hair bundles. A recent experimental rep...
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