English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Journal Article

Attentional fluctuations induce shared variability in macaque primary visual cortex

MPS-Authors
/persons/resource/persons83805

Bethge,  M
Max Planck Institute for Biological Cybernetics, Max Planck Society;
Research Group Computational Vision and Neuroscience, Max Planck Institute for Biological Cybernetics, Max Planck Society;

External Resource
Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)
There are no public fulltexts stored in PuRe
Supplementary Material (public)
There is no public supplementary material available
Citation

Denfield, G., Ecker, A., Shinn, T., Bethge, M., & Tolias, A. (2018). Attentional fluctuations induce shared variability in macaque primary visual cortex. Nature Communications, 9: 2654, pp. 1-14. doi:10.1038/s41467-018-05123-6.


Cite as: https://hdl.handle.net/21.11116/0000-0000-C2BE-F
Abstract
Variability in neuronal responses to identical stimuli is frequently correlated across a population. Attention is thought to reduce these correlations by suppressing noisy inputs shared by the population. However, even with precise control of the visual stimulus, the subject’s attentional state varies across trials. While these state fluctuations are bound to induce some degree of correlated variability, it is currently unknown how strong their effect is, as previous studies generally do not dissociate changes in attentional strength from changes in attentional state variability. We designed a novel paradigm that does so and find both a pronounced effect of attentional fluctuations on correlated variability at long timescales and attention-dependent reductions in correlations at short timescales. These effects predominate in layers 2/3, as expected from a feedback signal such as attention. Thus, significant portions of correlated variability can be attributed to fluctuations in internally generated signals, like attention, rather than noise.