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  Identifying endogenous rhythmic spatio-temporal patterns in micro-electrode array recordings

Besserve, M., Panagiotaropoulos, T., Crocker, B., Kapoor, V., Tolias, A., Panzeri, S., et al. (2012). Identifying endogenous rhythmic spatio-temporal patterns in micro-electrode array recordings. Poster presented at 9th Annual Computational and Systems Neuroscience Meeting (Cosyne 2012), Salt Lake City, UT, USA.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-B844-E Version Permalink: http://hdl.handle.net/21.11116/0000-0001-19D4-4
Genre: Poster

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 Creators:
Besserve, M1, 2, 3, Author              
Panagiotaropoulos, T1, 2, Author              
Crocker, B1, 2, Author              
Kapoor, V1, 2, Author              
Tolias, A, Author              
Panzeri, S, Author              
Logothetis, NK1, 2, Author              
Affiliations:
1Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497798              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              
3Dept. Empirical Inference, Max Planck Institute for Intelligent Systems, Max Planck Society, DE, ou_1497647              

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 Abstract: Microelectrode arrays are a privileged recording modality to study neural processes with a very fine spatial and temporal resolution. They capture the activity of small populations and permit assessment of synergistic interactions between cells. Patterns of rhythmic ongoing activity are of particular interest because they reflect the intrinsic dynamics of neural populations and the way such dynamics may optimize the processing of incoming information. In this study, we identify the various coherent spatio-temporal patterns of rhythmic activity occurring across time using a two steps approach. First, signals were bandpass filtered in a relevant frequency band and subsequently Hilbert-transformed. Second, the complex patterns of activity occurring across time were clustered using a graph cut algorithm based on a phase shift invariant similarity measure. This invariance is a key-property of our approach to isolate wave propagation phenomena. We apply our method to Local Field Potentials recorded in the inferior convexity of the Prefrontal Cortex (icPFC) in two anesthetized macaques using a multi electrode array. We found a dominant travelling wave pattern in the beta band (15-25Hz), propagating along the ventral-dorsal plane, emerging and vanishing across time both in the absence of visual stimulation (spontaneous activity) and during binocular stimulation with movie clips. By computing mutual information, we showed that the amplitude of this wave actually carries sensory information during the presentation of several movies. Altogether, our analysis provides evidence for travelling wave phenomena reflecting the distributed computation in icPFC, which is known to be involved in higher order sensory processing. More generally, our approach enables the unsupervised analysis of the complex spatio-temporal neural dynamics in ongoing signals, providing key information to understand cooperative mechanisms in spatially distributed neural populations.

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 Dates: 2012-02
 Publication Status: Published in print
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 Identifiers: BibTex Citekey: BesserveBPCKTPL2012
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Title: 9th Annual Computational and Systems Neuroscience Meeting (Cosyne 2012)
Place of Event: Salt Lake City, UT, USA
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Title: 9th Annual Computational and Systems Neuroscience Meeting (Cosyne 2012)
Source Genre: Proceedings
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Pages: - Volume / Issue: - Sequence Number: II-26 Start / End Page: 114 - 115 Identifier: -