Evidence map›Paper›PMID 34995519›Full record

ReviewCell2022

Fluorescence imaging of large-scale neural ensemble dynamics.

Tony Hyun Kim, Mark J Schnitzer

Open access · greenAbstract readReview
In one paragraph

Review in Cell, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 99 papers.

0numbers the graph read from it
0cells of the map it votes in
99citing papers in PubMed
16.6field-weighted citation impact, top 1% of its field
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

99 citing papers in PubMed, 152 citations in OpenAlex.

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  17. Review
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39 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Tony Hyun KimJames Clark Center for Biomedical Engineering & Sciences, Stanford University, Stanford, CA 94305, USA; CNC Program, Stanford University, Stanford, CA 94305, USA; Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA. Electronic address: kimth@stanford.edu.
Mark J SchnitzerJames Clark Center for Biomedical Engineering & Sciences, Stanford University, Stanford, CA 94305, USA; CNC Program, Stanford University, Stanford, CA 94305, USA; Howard Hughes Medical Institute, Stanford University, Stanford, CA 94305, USA. Electronic address: mschnitz@stanford.edu.
Stanford University · US

Funding

Generation of novel cell type specific mouse genetic toolsU19MH114830 · NIMH · ALLEN INSTITUTE · PI ZENG, HONGKUI · 2017 to 2021
$64.7M
Transgenic mice and multiplexed, multi-beam instrumentation for large-scale optical experiments on brain states and ensemble cellular dynamics in behaving animalsUF1NS107610 · NINDS · STANFORD UNIVERSITY · PI SCHNITZER, MARK J, ZENG, HONGKUI · 2018 to 2018
$2.9M
Octopus microscopy for imaging multiple brain areas concurrentlyR01MH103116 · NIMH · STANFORD UNIVERSITY · PI SCHNITZER, MARK J · 2013 to 2016
$1.3M
Howard Hughes Medical InstituteNIMH NIH HHS R01 MH103116NIMH NIH HHS U19 MH114830NINDS NIH HHS UF1 NS107610
6 · The paper itself

Abstract

Recent progress in fluorescence imaging allows neuroscientists to observe the dynamics of thousands of individual neurons, identified genetically or by their connectivity, across multiple brain areas and for extended durations in awake behaving mammals. We discuss advances in fluorescent indicators of neural activity, viral and genetic methods to express these indicators, chronic animal preparations for long-term imaging studies, and microscopes to monitor and manipulate the activity of large neural ensembles. Ca

Indexed as

AnimalsBrain MappingCalciumMiceMicroscopy, Fluorescence, MultiphotonModels, AnimalNeocortexNeuronsNeurosciencesOptical ImagingCalcium

Identifiers

PMID34995519
PMCPMC8849612
OpenAlexW4205560034

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.