Learning-related fine-scale specificity imaged in motor cortex circuits of behaving mice

Takaki Komiyama (), Takashi R. Sato, Daniel H. O’Connor, Ying-Xin Zhang, Daniel Huber, Bryan M. Hooks, Mariano Gabitto and Karel Svoboda
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Takaki Komiyama: Janelia Farm Research Campus, HHMI, Ashburn, Virginia 20147, USA
Takashi R. Sato: Janelia Farm Research Campus, HHMI, Ashburn, Virginia 20147, USA
Daniel H. O’Connor: Janelia Farm Research Campus, HHMI, Ashburn, Virginia 20147, USA
Ying-Xin Zhang: Janelia Farm Research Campus, HHMI, Ashburn, Virginia 20147, USA
Daniel Huber: Janelia Farm Research Campus, HHMI, Ashburn, Virginia 20147, USA
Bryan M. Hooks: Janelia Farm Research Campus, HHMI, Ashburn, Virginia 20147, USA
Mariano Gabitto: University of California at San Diego, La Jolla, California 92093, USA
Karel Svoboda: Janelia Farm Research Campus, HHMI, Ashburn, Virginia 20147, USA

Nature, 2010, vol. 464, issue 7292, 1182-1186

Abstract: Cortical circuits: learning to behave Although it is generally accepted that specific cortical circuits drive behavioural execution, the relationship between task performance and modulation within the circuit is unknown. Taking advantage of a technique that allows simultaneous activity monitoring of many neurons within the same circuit, Komiyama et al. imaged activity in two motor cortical areas in mice involved in the control of licking. In both areas there were cells that are preferentially excited in different trial types and predict different actions. These neurons were spatially intermingled. However, nearby neurons showed pronounced temporally coincident activity. These temporal correlations were particularly high for pairs of neurons with similar response types, and increased with learning. These correlations provide direct evidence for rapid changes in cortical microcircuits underlying flexible behaviour.

Date: 2010
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DOI: 10.1038/nature08897

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