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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 objective indicator of...
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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 issue in practical...
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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 possessing multiple...
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Classification algorithm for motor imagery fusing CNN and attentional mechanisms based on functional near-infrared spectroscopy brain image
With the continuing development of brain–computer interface technology, the analysis and interpretation of brain signals are becoming increasingly...
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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 potential to automatically...
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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 fractional (VOF) calculus...
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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 control the robot, which not only...
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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; direct pathway (DP) which...
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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 time domain or frequency...
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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 patterns. In this study, we...
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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 hallucinations. This mental...
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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 suddenness and...
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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 calcium ([Ca 2+ ]), inositol 1,...
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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 electrode. In an experiment...
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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 assist disabled subjects to...
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Decoded EEG neurofeedback-guided cognitive reappraisal training for emotion regulation
Neurofeedback, when combined with cognitive reappraisal, offers promising potential for emotion regulation training. However, prior studies have...
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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 cooperation can be beneficial...
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SST-CRAM: spatial-spectral-temporal based convolutional recurrent neural network with lightweight attention mechanism for EEG emotion recognition
Through emotion recognition with EEG signals, brain responses can be analyzed to monitor and identify individual emotional states. The success of...
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Time-varying EEG networks of major depressive disorder during facial emotion tasks
Depression is a mental disease involved in emotional and cognitive impairments. Neuroimaging studies have found abnormalities in the structure and...
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Deep-learning-optimized microstate network analysis for early Parkinson’s disease with mild cognitive impairment
Graph-theory-based topological impairment of the whole-brain network has been verified to be one of the characteristics of mild cognitive impairment...
