ArticleFrontiers in computational neuroscience2022
Decoding Digital Visual Stimulation From Neural Manifold With Fuzzy Leaning on Cortical Oscillatory Dynamics.
Article in Frontiers in computational neuroscience, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed, 5 citations in OpenAlex.
- Long-range correlations in alpha-band of electroencephalogram: a nonlinear embedding and detrended fluctuation analysis.Frontiers in neuroinformatics · 2026Article
- Get a New Perspective on EEG: Convolutional Neural Network Encoders for Parametric t-SNE.Brain sciences · 2023Article
- Brain inspired neuronal silencing mechanism to enable reliable sequence identification.Scientific reports · 2022Article
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6 authors at 1 institution in 1 country.
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Abstract
A crucial point in neuroscience is how to correctly decode cognitive information from brain dynamics for motion control and neural rehabilitation. However, due to the instability and high dimensions of electroencephalogram (EEG) recordings, it is difficult to directly obtain information from original data. Thus, in this work, we design visual experiments and propose a novel decoding method based on the neural manifold of cortical activity to find critical visual information. First, we studied four major frequency bands divided from EEG and found that the responses of the EEG alpha band (8-15 Hz) in the frontal and occipital lobes to visual stimuli occupy a prominent place. Besides, the essential features of EEG data in the alpha band are further mined
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