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Sequential and efficient neural-population coding of complex task information

Citation

Koay, Sue Ann (2021), Sequential and efficient neural-population coding of complex task information, Dryad, Dataset, https://doi.org/10.5061/dryad.cvdncjt53

Abstract

Condensed neural and behavioral data, included secondary results from model fits and analyses. This dataset contains all information required to recreate figures from the paper.

Methods

Transgenic mice expressing the calcium-sensitive fluorescent indicator GCamp6f were trained in the Accumulating Towers task and two-photon calcium imaging was performed of functionally identified primary and secondary visual cortical areas, as well as retrosplenial cortex. Regions of interest representing putative single neurons were extracted using a semi-customized demixing and deconvolution procedure. Behavioral data were separately collected by a computer that ran a virtual reality control engine, and synchronized with imaging data via a synchronization timestamp sent to the imaging computer at every graphics refresh cycle.

Funding

National Institutes of Health, Award: 5U01NS090541

National Institutes of Health, Award: 1U19NS104648