Visual image reconstructed without semantics from human brain activity using linear image decoders and nonlinear noise suppression

In recent years, substantial strides have been made in the field of visual image reconstruction, particularly in its capacity to generate high-quality visual representations from human brain activity while considering semantic information. This advancement not only enables the recreation of visual c...

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Veröffentlicht in:	Cognitive neurodynamics Jg. 19; H. 1; S. 20
1. Verfasser:	Li, Qiang
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Dordrecht Springer Netherlands 01.12.2025 Springer Nature B.V
Schlagworte:	Accuracy Activity patterns Artificial Intelligence Artificial neural networks Biochemistry Biomedical and Life Sciences Biomedicine Brain Brain mapping Brain research Cognitive Psychology Computer Science Datasets Decoders Decoding Deep learning Heart rate Image processing Image quality Image reconstruction Information processing Mapping Memory Neural networks Neuroimaging Neurosciences Noise reduction Nonlinear response Physiology Research Article Semantics Structure-function relationships Visual fields Visual perception Linear decoding Deep autoencoder denoised neural networks Functional similarities Brain activity Visual image reconstruction Neural explanatory
ISSN:	1871-4080, 1871-4099
Online-Zugang:	Volltext
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