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  Decoding complex sounds from auditory cortex responses without knowledge of precise stimulus timing

Kayser, C., Panzeri, S., & Logothetis, N. (2010). Decoding complex sounds from auditory cortex responses without knowledge of precise stimulus timing. Frontiers in Computational Neuroscience, 2010(Conference Abstract: Bernstein Conference on Computational Neuroscience). doi:10.3389/conf.fncom.2010.51.00008.

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Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-BE1E-3 Version Permalink: http://hdl.handle.net/21.11116/0000-0002-AFBD-5
Genre: Meeting Abstract

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 Creators:
Kayser, C1, 2, 3, Author              
Panzeri, S2, 3, Author              
Logothetis, NK2, 3, Author              
Affiliations:
1Research Group Physiology of Sensory Integration, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497808              
2Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497798              
3Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              

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 Abstract: Sensory systems can recognize complex stimuli even when these appear at unexpected times. While much work quantifies the stimulus information carried by neural responses, most studies measure spike times with respect to a stimulus-related time frame, and thus implicitly assume a precise ‘clock’ registering the timing of sensory and neural events (Panzeri TINS 10). However, sensory systems may not have such a clock, and likely rely on intrinsic mechanisms to measure the timing of sensory and neural events. This raises the questions of how well different sensory stimuli can be discriminated in the absence of a perfect clock, and what neural codes could mediate ‘clock-free’ sensory representations. Addressing these questions, we used the primate auditory cortex as a model system and investigated the information carried by different putative neural codes that do not rely on the precise knowledge of stimulus timing. Our approach builds on the observation that in auditory cortex theta rhythm network activity is entrained by complex sounds (Kayser Neuron 09). As such, the phase of slow rhythms can serve as an intrinsic temporal frame of reference. We show that a spike pattern code based on inter-spike interval (ISI) distributions can discriminate different complex sounds, and does so significantly better when referenced to the local theta rhythm. More specifically, we used 200 ms long sliding windows to mimic uncertainty about stimulus onset, and within each window discriminated different naturalistic sounds using either spike counts, ISI distributions and combined ISI and theta-phase distributions. The combined ISI-phase code provided about a 50 increase of stimulus-related information compared to spike counts. These results suggest that combining different intrinsic time scales, such as ISI’s and slow rhythms, allows the construction of neural codes that carry considerable information about sensory stimuli without making reference to the timing of external events.

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 Dates: 2010-09
 Publication Status: Published online
 Pages: -
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 Rev. Type: -
 Identifiers: DOI: 10.3389/conf.fncom.2010.51.00008
BibTex Citekey: KayserPL2010
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Title: Bernstein Conference on Computational Neuroscience (BCCN 2010)
Place of Event: Berlin, Germany
Start-/End Date: 2010-09-27 - 2010-10-01

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Title: Frontiers in Computational Neuroscience
Source Genre: Journal
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Publ. Info: Lausanne : Frontiers Research Foundation
Pages: - Volume / Issue: 2010 (Conference Abstract: Bernstein Conference on Computational Neuroscience) Sequence Number: - Start / End Page: - Identifier: Other: 1662-5188
CoNE: https://pure.mpg.de/cone/journals/resource/1662-5188