Evidence map›Paper›PMID 38014018›Full record

ArticlebioRxiv : the preprint server for biology2023

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

Mai-Anh T Vu, Eleanor H Brown, Michelle J Wen, Christian A Noggle, Zicheng Zhang, Kevin J Monk, Safa Bouabid, Lydia Mroz, Benjamin M Graham, Yizhou Zhuo and 6 more

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

16 authors.

Mai-Anh T VuDepartment of Psychological & Brain Sciences, Boston University, Boston, MA, USA.ORCID 0000-0003-4766-1159
Eleanor H BrownGraduate Program for Neuroscience, Boston University, Boston, MA, USA.
Michelle J WenDepartment of Psychological & Brain Sciences, Boston University, Boston, MA, USA.
Christian A NoggleDepartment of Psychological & Brain Sciences, Boston University, Boston, MA, USA.
Zicheng ZhangDepartment of Biology, Boston University, Boston, MA, USA.
Kevin J MonkDepartment of Biology, Boston University, Boston, MA, USA.
Safa BouabidDepartment of Psychological & Brain Sciences, Boston University, Boston, MA, USA.
Lydia MrozDepartment of Psychological & Brain Sciences, Boston University, Boston, MA, USA.
Benjamin M GrahamDepartment of Psychological & Brain Sciences, Boston University, Boston, MA, USA.
Yizhou ZhuoState Key Laboratory of Membrane Biology, Peking University School of Life Sciences, Beijing, China.
Yulong LiState Key Laboratory of Membrane Biology, Peking University School of Life Sciences, Beijing, China.
Timothy M OtchyDepartment of Biology, Boston University, Boston, MA, USA.
Lin TianDepartment of Biochemistry and Molecular Medicine, University of California, Davis, CA.
Ian G DavisonDepartment of Biology, Boston University, Boston, MA, USA.ORCID 0000-0003-0998-7676
David A BoasDepartment of Biomedical Engineering, Boston University, Boston, MA, USA.
Mark W HoweDepartment of Psychological & Brain Sciences, Boston University, Boston, MA, USA.

Funding

Striatum Wide Dynamics and Neuromodulation of Cell-Type Specific Striatum Populations during LearningR01MH125835 · NIMH · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI HOWE, MARK W · 2021 to 2025
$3.0M
Sensory-motor strategies for odor-guided navigationRF1NS128975 · NINDS · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI DAVISON, IAN GORDON · 2022 to 2022
$1.2M
Subcellular Mapping and Post-Synaptic Impacts of Striatal Dopamine Release During BehaviorF32MH120894 · NIMH · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI VU, MAI-ANH · 2019 to 2022
$244k
Social Information Processing in the Vomeronasal System during Active BehaviorF32DC020665 · NIDCD · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI MONK, KEVIN JAMES · 2023 to 2025
$233k
Establishing a Spatial Map of Dopamine Reward Prediction Error Computations and their Function in Distinct Associative Learning Processes Across the Striatum: a Methodological FrameworkF31NS127536 · NINDS · BOSTON UNIVERSITY MEDICAL CAMPUS · PI BROWN, ELEANOR · 2022 to 2024
$111k
NIDCD NIH HHS F32 DC020665NIMH NIH HHS F32 MH120894NIMH NIH HHS R01 MH125835NINDS NIH HHS F31 NS127536NINDS NIH HHS RF1 NS128975
6 · The paper itself

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.

Identifiers

PMID38014018
PMCPMC10680831

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.