EconPapers    
Economics at your fingertips  
 

Recurrent interactions in local cortical circuits

Simon Peron (), Ravi Pancholi, Bettina Voelcker, Jason D. Wittenbach, H. Freyja Ólafsdóttir, Jeremy Freeman and Karel Svoboda
Additional contact information
Simon Peron: Howard Hughes Medical Institute
Ravi Pancholi: New York University
Bettina Voelcker: New York University
Jason D. Wittenbach: Howard Hughes Medical Institute
H. Freyja Ólafsdóttir: Howard Hughes Medical Institute
Jeremy Freeman: Howard Hughes Medical Institute
Karel Svoboda: Howard Hughes Medical Institute

Nature, 2020, vol. 579, issue 7798, 256-259

Abstract: Abstract Most cortical synapses are local and excitatory. Local recurrent circuits could implement amplification, allowing pattern completion and other computations1–4. Cortical circuits contain subnetworks that consist of neurons with similar receptive fields and increased connectivity relative to the network average5,6. Cortical neurons that encode different types of information are spatially intermingled and distributed over large brain volumes5–7, and this complexity has hindered attempts to probe the function of these subnetworks by perturbing them individually8. Here we use computational modelling, optical recordings and manipulations to probe the function of recurrent coupling in layer 2/3 of the mouse vibrissal somatosensory cortex during active tactile discrimination. A neural circuit model of layer 2/3 revealed that recurrent excitation enhances sensory signals by amplification, but only for subnetworks with increased connectivity. Model networks with high amplification were sensitive to damage: loss of a few members of the subnetwork degraded stimulus encoding. We tested this prediction by mapping neuronal selectivity7 and photoablating9,10 neurons with specific selectivity. Ablation of a small proportion of layer 2/3 neurons (10–20, less than 5% of the total) representing touch markedly reduced responses in the spared touch representation, but not in other representations. Ablations most strongly affected neurons with stimulus responses that were similar to those of the ablated population, which is also consistent with network models. Recurrence among cortical neurons with similar selectivity therefore drives input-specific amplification during behaviour.

Date: 2020
References: Add references at CitEc
Citations: View citations in EconPapers (6)

Downloads: (external link)
https://www.nature.com/articles/s41586-020-2062-x Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:nature:v:579:y:2020:i:7798:d:10.1038_s41586-020-2062-x

Ordering information: This journal article can be ordered from
https://www.nature.com/

DOI: 10.1038/s41586-020-2062-x

Access Statistics for this article

Nature is currently edited by Magdalena Skipper

More articles in Nature from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().

 
Page updated 2025-03-19
Handle: RePEc:nat:nature:v:579:y:2020:i:7798:d:10.1038_s41586-020-2062-x