Responses of pyramidal cell somata and apical dendrites in mouse visual cortex over multiple days

Author:

Gillon Colleen J.ORCID,Lecoq Jérôme A.ORCID,Pina Jason E.ORCID,Ahmed Ruweida,Billeh Yazan N.ORCID,Caldejon Shiella,Groblewski Peter,Henley Timothy M.ORCID,Kato India,Lee EricORCID,Luviano Jennifer,Mace Kyla,Nayan Chelsea,Nguyen Thuyanh V.,North Kat,Perkins Jed,Seid Sam,Valley Matthew T.,Williford Ali,Bengio YoshuaORCID,Lillicrap Timothy P.,Zylberberg Joel,Richards Blake A.ORCID

Abstract

AbstractThe apical dendrites of pyramidal neurons in sensory cortex receive primarily top-down signals from associative and motor regions, while cell bodies and nearby dendrites are heavily targeted by locally recurrent or bottom-up inputs from the sensory periphery. Based on these differences, a number of theories in computational neuroscience postulate a unique role for apical dendrites in learning. However, due to technical challenges in data collection, little data is available for comparing the responses of apical dendrites to cell bodies over multiple days. Here we present a dataset collected through the Allen Institute Mindscope’s OpenScope program that addresses this need. This dataset comprises high-quality two-photon calcium imaging from the apical dendrites and the cell bodies of visual cortical pyramidal neurons, acquired over multiple days in awake, behaving mice that were presented with visual stimuli. Many of the cell bodies and dendrite segments were tracked over days, enabling analyses of how their responses change over time. This dataset allows neuroscientists to explore the differences between apical and somatic processing and plasticity.

Funder

Gouvernement du Canada | Natural Sciences and Engineering Research Council of Canada

Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada

Canadian Institute for Advanced Research

Allen Institute Falconwood Foundation

Alfred P. Sloan Foundation

Publisher

Springer Science and Business Media LLC

Subject

Library and Information Sciences,Statistics, Probability and Uncertainty,Computer Science Applications,Education,Information Systems,Statistics and Probability

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