Evidence map›Paper›PMID 36993596›Full record

ArticlebioRxiv : the preprint server for biology2023

Mesoscale volumetric light field (MesoLF) imaging of neuroactivity across cortical areas at 18 Hz.

Tobias Nöbauer, Yuanlong Zhang, Hyewon Kim, Alipasha Vaziri

Open access · greenAbstract readPreprint
PubMed Full text at PMC Publisher
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, 1 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 1 institution in 2 countries.

Tobias NöbauerLaboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY, USA.
Yuanlong ZhangLaboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY, USA.
Hyewon KimLaboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY, USA.
Alipasha VaziriLaboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY, USA.
Rockefeller University · US

Funding

Lensless, high-speed and multi-region volumetric Ca2+ imaging of up to 1cm2 brain surface across model animalsRF1NS110501 · NINDS · ROCKEFELLER UNIVERSITY · PI ROBINSON, JACOB T., VAZIRI, ALIPASHA · 2019 to 2019
$2.8M
Cortex-wide volumetric imaging of neuronal activity.U01NS103488 · NINDS · ROCKEFELLER UNIVERSITY · PI VAZIRI, ALIPASHA · 2017 to 2019
$2.7M
In vivo Imaging of Neuroactivity in the Deep Forward Scattering Regime Using Speckle Identification and Demixing (SPID) MicroscopyRF1NS113251 · NINDS · ROCKEFELLER UNIVERSITY · PI GIGAN, SYLVAIN, VAZIRI, ALIPASHA · 2019 to 2019
$2.1M
NINDS NIH HHS RF1 NS110501NINDS NIH HHS RF1 NS113251NINDS NIH HHS U01 NS103488
6 · The paper itself

Abstract

Various implementations of mesoscopes provide optical access for calcium imaging across multi-millimeter fields-of-view (FOV) in the mammalian brain. However, capturing the activity of the neuronal population within such FOVs near-simultaneously and in a volumetric fashion has remained challenging since approaches for imaging scattering brain tissues typically are based on sequential acquisition. Here, we present a modular, mesoscale light field (MesoLF) imaging hardware and software solution that allows recording from thousands of neurons within volumes of 4000 × 200 μm, located at up to 400 μm depth in the mouse cortex, at 18 volumes per second. Our optical design and computational approach enable up to hour-long recording of ~10,000 neurons across multiple cortical areas in mice using workstation-grade computing resources.

Identifiers

PMID36993596
PMCPMC10055306
OpenAlexW4328052743

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.