Responses to inconsistent stimuli in pyramidal neurons: An open science dataset
Brain Imaging, Neuroimaging, Neuroscience and ePoster by Colleen J. Gillon, Colleen J Gillon, Jérôme A. Lecoq, Jerome A Lecoq, Jason E. Pina, Jason E Pina and 14 more
Part of COSYNE 2023 posters, University of Toronto; Allen Institute for Brain Science; York University; Centre for Vision Research, Department of Physics and Astronomy
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Abstract
Pyramidal neurons have apical dendrites that are both physically and electrically segregated from their cell bodies. In sensory cortex, these apical dendrites receive primarily top-down signals from associative and motor regions, while the cell bodies and nearby dendrites of these same pyramidal neurons are mostly targeted by bottom-up or locally recurrent inputs from the sensory periphery. Due to these differences, a number of theories in computational neuroscience postulate a unique role for apical dendrites in shaping sensory processing and plasticity in the face of new or surprising stimuli. Despite this strong interest, technical challenges in data collection mean that there is very little data available on which these ideas can be tested. Here we present an openly available dataset that fills this gap and was collected through an expertly designed and operated data collection pipeline. This dataset contains high-quality two-photon calcium imaging from both the apical dendrites and the cell bodies of visual cortical pyramidal neurons in awake, behaving mice over multiple days as they are presented with consistent and inconsistent visual stimuli. Many cell bodies and dendrite segments could be 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, and sets an example for supporting reproducibility and reusability in neuroscience.
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- Session
- Poster Session II
- Citation
- Colleen J. Gillon, Colleen J Gillon, Jérôme A. Lecoq et al. (2023). Responses to inconsistent stimuli in pyramidal neurons: An open science dataset. COSYNE 2023. https://doi.org/10.57736/9bcc-02b5 (opens in a new tab)
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