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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...
Stability of synchronization manifolds and its nonlinear behaviour in memristive coupled discrete neuron model
Stability of synchronization manifolds and its nonlinear behaviour in memristive coupled discrete neuron model
In this study, we investigate the impact of first and second-order coupling strengths on the stability of a synchronizatio...
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...
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...
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 ...
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 ...
Investigating the impact of hearing loss on attentional networks among older individuals: an event-related potential study
Investigating the impact of hearing loss on attentional networks among older individuals: an event-related potential study
Attention is a core cognitive domain crucial in facilitating day-to-day life. Using an attention network test (ANT) along ...
Setting a double-capacitive neuron coupled with Josephson junction and piezoelectric source
Setting a double-capacitive neuron coupled with Josephson junction and piezoelectric source
Perception of voice means acoustic electric conversion in the auditory system, and changes of external magnetic field can ...
Multi-scale modeling to investigate the effects of transcranial magnetic stimulation on morphologically-realistic neuron with depression
Multi-scale modeling to investigate the effects of transcranial magnetic stimulation on morphologically-realistic neuron with depression
Transcranial magnetic stimulation (TMS) is a non-invasive neuromodulation technique to activate or inhibit the activity of...
Controlling Alzheimer’s disease by deep brain stimulation based on a data-driven cortical network model
Controlling Alzheimer’s disease by deep brain stimulation based on a data-driven cortical network model
This work aims to explore the control effect of DBS on Alzheimer's disease (AD) from a neurocomputational perspective....
Attention-based cross-frequency graph convolutional network for driver fatigue estimation
Attention-based cross-frequency graph convolutional network for driver fatigue estimation
Fatigue driving significantly contributes to global vehicle accidents and fatalities, making driver fatigue level estimati...
Deep source transfer learning for the estimation of internal brain dynamics using scalp EEG
Deep source transfer learning for the estimation of internal brain dynamics using scalp EEG
Electroencephalography (EEG) provides high temporal resolution neural data for brain-computer interfacing via noninvasive ...
STEADYNet: Spatiotemporal EEG analysis for dementia detection using convolutional neural network
STEADYNet: Spatiotemporal EEG analysis for dementia detection using convolutional neural network
Dementia is a neuro-degenerative disorder with a high death rate, mainly due to high human error, time, and cost of the cu...
STGAT-CS: spatio-temporal-graph attention network based channel selection for MI-based BCI
STGAT-CS: spatio-temporal-graph attention network based channel selection for MI-based BCI
Brain-computer interface (BCI) based on the motor imagery paradigm typically utilizes multi-channel electroencephalogram (...
EEG-based classification of Alzheimer’s disease and frontotemporal dementia: a comprehensive analysis of discriminative features
EEG-based classification of Alzheimer’s disease and frontotemporal dementia: a comprehensive analysis of discriminative features
Alzheimer’s disease (AD) and frontotemporal dementia (FTD) are two main types of dementia. These diseases have simil...
Electroencephalogram criticality in cognitive impairment: a monitoring biomarker?
Electroencephalogram criticality in cognitive impairment: a monitoring biomarker?
Critical states present scale-free dynamics, optimizing neuronal complexity and serving as a potential biomarker in cognit...
Coherence-based channel selection and Riemannian geometry features for magnetoencephalography decoding
Coherence-based channel selection and Riemannian geometry features for magnetoencephalography decoding
Magnetoencephalography (MEG) records the extremely weak magnetic fields on the surface of the scalp through highly sensiti...
Multiple time delay induced Hopf bifurcation of a cortex - basal ganglia model for Parkinson’s Disease
Multiple time delay induced Hopf bifurcation of a cortex - basal ganglia model for Parkinson’s Disease
Exploring the origin of beta - band oscillation in the cortex - basal ganglia model plays an important role in understandi...
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