dorsal/arxiv
View SchemaSeparation of multiple evoked responses using differential amplitude and latency variability
| Authors | Kevin H. Knuth, Wilson A. Truccolo, Steven L. Bressler, Mingzhou Ding |
|---|---|
| Categories | |
| ArXiv ID | physics/0204085 |
| URL | https://arxiv.org/abs/physics/0204085 |
| Journal | Proceedings of the Third International Workshop on Independent Component Analysis and Blind Signal Separation (ICA 2001), p. 463, 2001 |
Abstract
In 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.
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"abstract": "In neuroelectrophysiology one records electric potentials or magnetic fields\ngenerated by ensembles of synchronously active neurons in response to\nexternally presented stimuli. These evoked responses are often produced by\nmultiple generators in the presence of ongoing background activity. While\nsource localization techniques or current source density estimation are usually\nused to identify generators, application of blind source separation techniques\nto obtain independent components has become more popular.\n We approach this problem by applying the Bayesian methodology to a more\nphysiologically-realistic source model. As it is generally accepted that single\ntrials vary in amplitude and latency, we incorporate this variability into the\nmodel. Rather than making the unrealistic assumption that these cortical\ncomponents are independent of one another, our algorithm utilizes the\ndifferential amplitude and latency variability of the evoked waveforms to\nidentify the cortical components. The algorithm is applied to\nintracortically-recorded local field potentials in monkeys performing a\nvisuomotor task.",
"arxiv_id": "physics/0204085",
"authors": [
"Kevin H. Knuth",
"Wilson A. Truccolo",
"Steven L. Bressler",
"Mingzhou Ding"
],
"categories": [
"physics.med-ph",
"physics.bio-ph",
"physics.data-an",
"q-bio.NC"
],
"journal_ref": "Proceedings of the Third International Workshop on Independent\n Component Analysis and Blind Signal Separation (ICA 2001), p. 463, 2001",
"title": "Separation of multiple evoked responses using differential amplitude and latency variability",
"url": "https://arxiv.org/abs/physics/0204085"
},
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