Localized estimation of electromagnetic sources underlying event-related fields using recurrent neural networks

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dc.contributor.authorJamie A. O’Reilly
dc.contributor.authorJudy D. Zhu
dc.contributor.authorPaul F. Sowman
dc.date.accessioned2026-05-08T19:17:51Z
dc.date.issued2023-8-1
dc.description.abstract. This work builds on recent developments of RNNs for modelling event-related neural responses by incorporating biophysical constraints from the forward model, thus taking a significant step towards greater biological realism and introducing the possibility of exploring how input manipulations may influence localised neural activity.
dc.identifier.doi10.1088/1741-2552/acef94
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/16206
dc.publisherJournal of Neural Engineering
dc.subjectNeural dynamics and brain function
dc.subjectBlind Source Separation Techniques
dc.subjectNeural Networks and Applications
dc.titleLocalized estimation of electromagnetic sources underlying event-related fields using recurrent neural networks
dc.typeArticle

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