Evidence map›Paper›PMID 36909631›Full record

ArticlebioRxiv : the preprint server for biology2023

BrainLine: An Open Pipeline for Connectivity Analysis of Heterogeneous Whole-Brain Fluorescence Volumes.

Thomas L Athey, Matthew A Wright, Marija Pavlovic, Vikram Chandrashekhar, Karl Deisseroth, Michael I Miller, Joshua T Vogelstein

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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

7 authors.

Thomas L AtheyDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.
Matthew A WrightDepartment of Psychiatry, Weill Cornell Medicine, New York, NY, USA.
Marija PavlovicDepartment of Bioengineering, Stanford University, Stanford, CA, USA.
Vikram ChandrashekharDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.
Karl DeisserothDepartment of Bioengineering, Stanford University, Stanford, CA, USA.
Michael I MillerDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.
Joshua T VogelsteinDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.

Funding

Project 2 MeasurementU19AG033655 · NIA · JOHNS HOPKINS UNIVERSITY · PI Arnold Bakker · 2014 to 2026
$51.5M
Brain networks in mouse models of agingR01AG066184 · NIA · DUKE UNIVERSITY · PI BADEA, ALEXANDRA · 2019 to 2023
$3.8M
Accessible technologies for high-throughput, whole-brain reconstructions of molecularly characterized mammalian neuronsRF1MH121539 · NIMH · JOHNS HOPKINS UNIVERSITY · PI MILLER, MICHAEL I, MUELLER, ULRICH · 2019 to 2019
$3.6M
DISSECTION OF THE ROLE OF SEROTONIN CIRCUITS IN REWARD AND AVERSIONK08MH113039 · NIMH · WEILL MEDICAL COLL OF CORNELL UNIV · PI WRIGHT, MATTHEW A · 2017 to 2021
$939k
NIA NIH HHS R01 AG066184NIA NIH HHS U19 AG033655NIMH NIH HHS K08 MH113039NIMH NIH HHS RF1 MH121539
6 · The paper itself

Abstract

Whole-brain fluorescence images require several stages of computational processing to fully reveal the neuron morphology and connectivity information they contain. However, these computational tools are rarely part of an integrated pipeline. Here we present BrainLine, an open-source pipeline that interfaces with existing software to provide registration, axon segmentation, soma detection, visualization and analysis of results. By implementing a feedback based training paradigm with BrainLine, we were able to use a single learning algorithm to accurately process a diverse set of whole-brain images generated by light-sheet microscopy. BrainLine is available as part of our Python package brainlit: http://brainlit.neurodata.io/ .

Identifiers

PMID36909631
PMCPMC10002688

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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.