Evidence map›Paper›PMID 38645100›Full record

ArticlebioRxiv : the preprint server for biology2024

Enabling Electric Field Model of Microscopically Realistic Brain.

Zhen Qi, Gregory M Noetscher, Alton Miles, Konstantin Weise, Thomas R Knösche, Cameron R Cadman, Alina R Potashinsky, Kelu Liu, William A Wartman, Guillermo Nunez Ponasso and 5 more

Open access · greenAbstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. 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

15 authors at 6 institutions in 2 countries.

Zhen Qi
Gregory M NoetscherORCID 0000-0001-9786-7206
Alton Miles
Konstantin Weise
Thomas R Knösche
Cameron R Cadman
Alina R Potashinsky
Kelu Liu
William A Wartman
Guillermo Nunez PonassoORCID 0000-0002-2938-6782
Marom Bikson
Hanbing Lu
Aapo R Nummenmaa
Sergey N Makaroff
Worcester Polytechnic Institute · USNational Institutes of Health · USCity College of New York · USLeipzig University of Applied Sciences · DEMassachusetts General Hospital · USMax Planck Institute for Human Cognitive and Brain Sciences · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Modeling brain stimulation at the microscopic scale may reveal new paradigms for various stimulation modalities. We present the largest map to date of extracellular electric field distributions within a layer L2/L3 mouse primary visual cortex brain sample. This was enabled by the automated analysis of serial section electron microscopy images with improved handling of image defects, covering a volume of 250 × 140 × 90 μm Significance statement: This study is arguably the first attempt to model brain stimulation at the microscopic scale, enabled by automated analysis of modern scanning electron microscopy images of the brain. It concentrates on modeling microscopic perturbations of the extracellular electric field caused by the physical cell structure and is applicable to any type of brain stimulation. Data availability statement: Post-processed cell CAD models (383, stl format), microcapillary CAD models (34, stl format), post-processed neuron morphologies (267, swc format), extracellular electric field and potential distributions at different polarizations (267x3, MATLAB format), *.ses projects files for biophysical modeling with Neuron software (267x2, Neuron format), and computed neuron activating thresholds at different conditions (267x8, Excel tables, without the sample polarization correction from Section 2.8) are made available online through

Identifiers

PMID38645100
PMCPMC11030228
OpenAlexW4394695457

What OpenQuestion holds

Textmetadata
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.