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07/19/2023
Perturbing a Neural Network to Infer Effective Connectivity: Evidence from Synthetic EEG Data
Identifying causal relationships among distinct brain areas, known as ef...
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12/10/2022
A Hybrid Brain-Computer Interface Using Motor Imagery and SSVEP Based on Convolutional Neural Network
The key to electroencephalography (EEG)-based brain-computer interface (...
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11/10/2022
Multi-objective optimization via evolutionary algorithm (MOVEA) for high-definition transcranial electrical stimulation of the human brain
Transcranial temporal interference stimulation (tTIS) has been reported ...
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10/08/2022
Explainable fMRI-based Brain Decoding via Spatial Temporal-pyramid Graph Convolutional Network
Brain decoding, aiming to identify the brain states using neural activit...
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08/09/2022
Partial Least Square Regression via Three-factor SVD-type Manifold Optimization for EEG Decoding
Partial least square regression (PLSR) is a widely-used statistical mode...
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07/14/2022
Immunofluorescence Capillary Imaging Segmentation: Cases Study
Nonunion is one of the challenges faced by orthopedics clinics for the t...
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06/07/2022
Transfer learning to decode brain states reflecting the relationship between cognitive tasks
Transfer learning improves the performance of the target task by leverag...
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12/02/2021
Embedding Decomposition for Artifacts Removal in EEG Signals
Electroencephalogram (EEG) recordings are often contaminated with artifa...
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11/30/2021
Deep Auto-encoder with Neural Response
Artificial intelligence and neuroscience are deeply interactive. Artific...
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02/18/2021
Edge Sparse Basis Network: An Deep Learning Framework for EEG Source Localization
EEG source localization is an important technical issue in EEG analysis....
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02/05/2021
Machine Learning Applications on Neuroimaging for Diagnosis and Prognosis of Epilepsy: A Review
Machine learning is playing an increasing important role in medical imag...
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01/20/2021
Riemannian-based Discriminant Analysis for Feature Extraction and Classification
Discriminant analysis, as a widely used approach in machine learning to ...
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01/18/2021
HyperNTF: A Hypergraph Regularized Nonnegative Tensor Factorization for Dimensionality Reduction
Most methods for dimensionality reduction are based on either tensor rep...
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10/05/2020
Bigeminal Priors Variational auto-encoder
Variational auto-encoders (VAEs) are an influential and generally-used c...
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07/16/2020
Detecting Out-of-distribution Samples via Variational Auto-encoder with Reliable Uncertainty Estimation
In unsupervised learning, variational auto-encoders (VAEs) are an influe...
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09/18/2019
Diversity-enabled sweet spots in layered architectures and speed-accuracy trade-offs in sensorimotor control
Nervous systems sense, communicate, compute, and actuate movement using ...
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06/13/2019