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  Simultaneous recordings of multi-unit activity (MUA) and surface EEG in alert macaques during presentation of movie clips

Whittingstall, K., & Logothetis, N. (2008). Simultaneous recordings of multi-unit activity (MUA) and surface EEG in alert macaques during presentation of movie clips. Poster presented at 38th Annual Meeting of the Society for Neuroscience (Neuroscience 2008), Washington, DC, USA.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0003-8B62-2 Version Permalink: http://hdl.handle.net/21.11116/0000-0003-8B63-1
Genre: Poster

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Whittingstall, KS1, 2, 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              

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 Abstract: Despite the ubiquitous use of EEG in the field of neuroscience, its exact relation to the underlying neural activity (such as MUA) remains poorly understood. Here, we present data from simultaneous recordings of surface EEG and MUA in area V1 of two behaving monkeys during the presentation of natural movie scenes. As expected, MUA responses varied considerably with the natural stimuli used. The EEG signal also differed across movies, indicating that it was, at the very least, sensitive enough to differentiate the activity elicited from different movies. Firstly, we correlated the stimulus-evoked EEG with the MUA, and observed that negative-going EEG deflections corresponded to increases in MUA activity (R=-0.12 ±0.03). We then filtered the EEG signal into different oscillatory bands, and found that elevated periods of MUA activity corresponded to elevated periods of EEG gamma power (R=0.28 ±0.04). To investigate whether the underlying MUA could be modeled with the EEG, we used a general linear model (GLM) in which both evoked and induced oscillatory signals were used as regressors. Across movies, we found that such a model could significantly reconstruct the MUA (R2=0.19±0.03). This goodness-of-fit varied depending on which oscillatory band of the EEG signal was used in the GLM model (highest fit for gamma, lowest for alpha). These findings indicate that (1) the surface EEG signal contains information from which underlying MUA activity can be reconstructed and (2) certain bands of the EEG signal may be better predictors of MUA activity than others. Such information could be useful in further understanding the specific neural correlates of the comprehensive EEG signal.

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 Dates: 2008-11
 Publication Status: Published in print
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Title: 38th Annual Meeting of the Society for Neuroscience (Neuroscience 2008)
Place of Event: Washington, DC, USA
Start-/End Date: 2008-11-15 - 2008-11-19

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Title: 38th Annual Meeting of the Society for Neuroscience (Neuroscience 2008)
Source Genre: Proceedings
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Pages: - Volume / Issue: - Sequence Number: 769.19 Start / End Page: - Identifier: -