Evidence map›Paper›PMID 36823333›Full record

ArticleNature methods2023

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 read
In one paragraph

Article in Nature methods, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
12.9field-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

17 citing papers in PubMed, 36 citations in OpenAlex.

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  6. Light-field deep learning enables high-throughput, scattering-mitigated calcium imaging.Proceedings of the National Academy of Sciences of the United States of America · 2025
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors at 1 institution in 2 countries.

Tobias Nöbauer *Laboratory of Neurotechnology and Biophysics, The Rockefeller University, New York, NY, USA.ORCID http://orcid.org/0000-0001-9959-4539
Yuanlong Zhang *Laboratory 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. vaziri@rockefeller.edu.ORCID http://orcid.org/0000-0001-8346-7551
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 in the mammalian brain; however, capturing the activity of the neuronal population within such fields of view near-simultaneously and in a volumetric fashion has remained challenging as 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 ⌀ 4 × 0.2 mm, located at up to 350 µm depth in the mouse cortex, at 18 volumes per second and an effective voxel rate of ~40 megavoxels per second. Using our optical design and computational approach we show recording of ~10,000 neurons across multiple cortical areas in mice using workstation-grade computing resources.

Indexed as

BrainNeuronsAnimalsMammalsMiceNeuroimagingSoftware

Identifiers

PMID36823333
PMCPMC11057224
OpenAlexW4321611173

What OpenQuestion holds

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Registered trials

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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.