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A transcriptomic axis predicts state modulation of cortical interneurons

View ORCID ProfileStephane Bugeon, Joshua Duffield, View ORCID ProfileMario Dipoppa, Anne Ritoux, Isabelle Prankerd, Dimitris Nicolout-sopoulos, David Orme, View ORCID ProfileMaxwell Shinn, Han Peng, Hamish Forrest, Aiste Viduolyte, View ORCID ProfileCharu Bai Reddy, Yoh Isogai, View ORCID ProfileMatteo Carandini, View ORCID ProfileKenneth D. Harris
doi: https://doi.org/10.1101/2021.10.24.465600
Stephane Bugeon
1UCL Queen Square Institute of Neurology, University College London, London, UK
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  • For correspondence: s.bugeon@ucl.ac.uk kenneth.harris@ucl.ac.uk
Joshua Duffield
1UCL Queen Square Institute of Neurology, University College London, London, UK
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Mario Dipoppa
1UCL Queen Square Institute of Neurology, University College London, London, UK
2Columbia University Center for Theoretical Neuroscience, New York NY, USA
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Anne Ritoux
1UCL Queen Square Institute of Neurology, University College London, London, UK
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Isabelle Prankerd
1UCL Queen Square Institute of Neurology, University College London, London, UK
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Dimitris Nicolout-sopoulos
1UCL Queen Square Institute of Neurology, University College London, London, UK
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David Orme
1UCL Queen Square Institute of Neurology, University College London, London, UK
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Maxwell Shinn
1UCL Queen Square Institute of Neurology, University College London, London, UK
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Han Peng
3Department of Physics, University of Oxford, Oxford, UK
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Hamish Forrest
1UCL Queen Square Institute of Neurology, University College London, London, UK
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Aiste Viduolyte
1UCL Queen Square Institute of Neurology, University College London, London, UK
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Charu Bai Reddy
1UCL Queen Square Institute of Neurology, University College London, London, UK
5UCL Institute of Ophthalmology, University College London, London, UK
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Yoh Isogai
4UCL Sainsbury-Wellcome Centre, University College London, London, UK
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Matteo Carandini
5UCL Institute of Ophthalmology, University College London, London, UK
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Kenneth D. Harris
1UCL Queen Square Institute of Neurology, University College London, London, UK
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  • For correspondence: s.bugeon@ucl.ac.uk kenneth.harris@ucl.ac.uk
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Abstract

Transcriptomics has revealed the exquisite diversity of cortical inhibitory neurons1–7, but it is not known whether these fine molecular subtypes have correspondingly diverse activity patterns in the living brain. Here, we show that inhibitory subtypes in primary visual cortex (V1) have diverse correlates with brain state, but that this diversity is organized by a single factor: position along their main axis of transcriptomic variation. We combined in vivo 2-photon calcium imaging of mouse V1 with a novel transcriptomic method to identify mRNAs for 72 selected genes in ex vivo slices. We used transcriptomic clusters (t-types)4 to classify inhibitory neurons imaged in layers 1-3 using a three-level hierarchy of 5 Families, 11 Classes, and 35 t-types. Visual responses differed significantly only across Families, but modulation by brain state differed at all three hierarchical levels. Nevertheless, this diversity could be predicted from the first transcriptomic principal component, which predicted a cell type’s brain state modulation and correlations with simultaneously recorded cells. Inhibitory t-types with narrower spikes, lower input resistance, weaker adaptation, and less axon in layer 1 as determined in vitro8 fired more in resting, oscillatory brain states. Transcriptomic types with the opposite properties fired more during arousal. The former cells had more inhibitory cholinergic receptors, and the latter more excitatory receptors. Thus, despite the diversity of V1 inhibitory neurons, a simple principle determines how their joint activity shapes state-dependent cortical processing.

Competing Interest Statement

The authors have declared no competing interest.

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Posted November 10, 2021.
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A transcriptomic axis predicts state modulation of cortical interneurons
Stephane Bugeon, Joshua Duffield, Mario Dipoppa, Anne Ritoux, Isabelle Prankerd, Dimitris Nicolout-sopoulos, David Orme, Maxwell Shinn, Han Peng, Hamish Forrest, Aiste Viduolyte, Charu Bai Reddy, Yoh Isogai, Matteo Carandini, Kenneth D. Harris
bioRxiv 2021.10.24.465600; doi: https://doi.org/10.1101/2021.10.24.465600
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A transcriptomic axis predicts state modulation of cortical interneurons
Stephane Bugeon, Joshua Duffield, Mario Dipoppa, Anne Ritoux, Isabelle Prankerd, Dimitris Nicolout-sopoulos, David Orme, Maxwell Shinn, Han Peng, Hamish Forrest, Aiste Viduolyte, Charu Bai Reddy, Yoh Isogai, Matteo Carandini, Kenneth D. Harris
bioRxiv 2021.10.24.465600; doi: https://doi.org/10.1101/2021.10.24.465600

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