Separation of multiple evoked responses using differential amplitude and latency variability

dc.creatorKnuth, Kevin H.
dc.creatorTruccolo, Wilson A.
dc.creatorBressler, Steven L.
dc.creatorDing, Mingzhou
dc.date2002-04-29
dc.date.accessioned2026-07-07T05:47:30Z
dc.date.available2026-07-07T05:47:30Z
dc.descriptionIn neuroelectrophysiology one records electric potentials or magnetic fields generated by ensembles of synchronously active neurons in response to externally presented stimuli. These evoked responses are often produced by multiple generators in the presence of ongoing background activity. While source localization techniques or current source density estimation are usually used to identify generators, application of blind source separation techniques to obtain independent components has become more popular. We approach this problem by applying the Bayesian methodology to a more physiologically-realistic source model. As it is generally accepted that single trials vary in amplitude and latency, we incorporate this variability into the model. Rather than making the unrealistic assumption that these cortical components are independent of one another, our algorithm utilizes the differential amplitude and latency variability of the evoked waveforms to identify the cortical components. The algorithm is applied to intracortically-recorded local field potentials in monkeys performing a visuomotor task.
dc.description6 pages, 2 figures, presented at ICA 2001 Meeting, Dec 9-12, 2001, San Diego CA. (electronic proceedings file 100-knuth.pdf)
dc.identifierhttps://arxiv.org/abs/physics/0204085
dc.identifierhttp://arxiv.org/abs/physics/0204085
dc.identifierProceedings of the Third International Workshop on Independent Component Analysis and Blind Signal Separation (ICA 2001), p. 463, 2001
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/84678
dc.subjectMedical Physics
dc.subjectBiological Physics
dc.subjectData Analysis, Statistics and Probability
dc.subjectNeurons and Cognition
dc.titleSeparation of multiple evoked responses using differential amplitude and latency variability
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