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  On the Structure of Neuronal Population Activity under Fluctuations in Attentional State

Ecker, A., Denfield, G., Bethge, M., & Tolias, A. (2016). On the Structure of Neuronal Population Activity under Fluctuations in Attentional State. Journal of Neuroscience, 36(5), 1775-1789. doi:10.1523/JNEUROSCI.2044-15.2016.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0000-7A30-1 Version Permalink: http://hdl.handle.net/21.11116/0000-0000-7A31-0
Genre: Journal Article

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Ecker, AS1, 2, 3, Author              
Denfield, GH, Author
Bethge, M1, 2, Author              
Tolias, AS2, 3, Author              
Affiliations:
1Research Group Computational Vision and Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497805              
2Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              
3Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497798              

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 Abstract: Attention is commonly thought to improve behavioral performance by increasing response gain and suppressing shared variability in neuronal populations. However, both the focus and the strength of attention are likely to vary from one experimental trial to the next, thereby inducing response variability unknown to the experimenter. Here we study analytically how fluctuations in attentional state affect the structure of population responses in a simple model of spatial and feature attention. In our model, attention acts on the neural response exclusively by modulating each neuron's gain. Neurons are conditionally independent given the stimulus and the attentional gain, and correlated activity arises only from trial-to-trial fluctuations of the attentional state, which are unknown to the experimenter. We find that this simple model can readily explain many aspects of neural response modulation under attention, such as increased response gain, reduced individual and shared variability, increased correlations with firing rates, limited range correlations, and differential correlations. We therefore suggest that attention may act primarily by increasing response gain of individual neurons without affecting their correlation structure. The experimentally observed reduction in correlations may instead result from reduced variability of the attentional gain when a stimulus is attended. Moreover, we show that attentional gain fluctuations, even if unknown to a downstream readout, do not impair the readout accuracy despite inducing limited-range correlations, whereas fluctuations of the attended feature can in principle limit behavioral performance.

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 Dates: 2016-02
 Publication Status: Published in print
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 Identifiers: DOI: 10.1523/JNEUROSCI.2044-15.2016
BibTex Citekey: EckerDBT2016
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Title: Journal of Neuroscience
Source Genre: Journal
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Pages: - Volume / Issue: 36 (5) Sequence Number: - Start / End Page: 1775 - 1789 Identifier: -