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Targeted micro-fiber arrays for measuring and manipulating localized multi-scale neural dynamics over large, deep brain volumes during behavior.

Authors :
Vu MT
Brown EH
Wen MJ
Noggle CA
Zhang Z
Monk KJ
Bouabid S
Mroz L
Graham BM
Zhuo Y
Li Y
Otchy TM
Tian L
Davison IG
Boas DA
Howe MW
Source :
BioRxiv : the preprint server for biology [bioRxiv] 2023 Nov 17. Date of Electronic Publication: 2023 Nov 17.
Publication Year :
2023

Abstract

Neural population dynamics relevant for behavior vary over multiple spatial and temporal scales across 3-dimensional volumes. Current optical approaches lack the spatial coverage and resolution necessary to measure and manipulate naturally occurring patterns of large-scale, distributed dynamics within and across deep brain regions such as the striatum. We designed a new micro-fiber array and imaging approach capable of chronically measuring and optogenetically manipulating local dynamics across over 100 targeted locations simultaneously in head-fixed and freely moving mice. We developed a semi-automated micro-CT based strategy to precisely localize positions of each optical fiber. This highly-customizable approach enables investigation of multi-scale spatial and temporal patterns of cell-type and neurotransmitter specific signals over arbitrary 3-D volumes at a spatial resolution and coverage previously inaccessible. We applied this method to resolve rapid dopamine release dynamics across the striatum volume which revealed distinct, modality specific spatiotemporal patterns in response to salient sensory stimuli extending over millimeters of tissue. Targeted optogenetics through our fiber arrays enabled flexible control of neural signaling on multiple spatial scales, better matching endogenous signaling patterns, and spatial localization of behavioral function across large circuits.<br />Competing Interests: DECLARATION OF INTERESTS The authors declare no competing interests

Details

Language :
English
Database :
MEDLINE
Journal :
BioRxiv : the preprint server for biology
Accession number :
38014018
Full Text :
https://doi.org/10.1101/2023.11.17.567425