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HomePreprintALS & Motor NeuronCorrelative light and electron microscopy identifies circuit motifs underlying processing of noisy visual motion in larval zebrafish
bioRxiv (Neuroscience)ALS & Motor NeuronPreprintFAIR Metadata / API
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Correlative light and electron microscopy identifies circuit motifs underlying processing of noisy visual motion in larval zebrafish

October 23, 2026
Boulanger-Weill, J., Kaempf, F., Schuhknecht, G. F. P., Garza, R., Schalek, R. L.
DOI: 10.1101/2025.03.14.643363
On This Page:Specs MatrixSummary & AbstractDeep Research BriefData Access & CodeCitations & Related

Study Design & Technical Specifications

Sample Size / Cohort

Documented in primary study

Subject / Study Model

CNS Experimental / Clinical Model

Analytical Modalities

Preprint ArticleOpen Science

Primary Abstract & Repository Description

Source: bioRxiv (Neuroscience)
To integrate noisy visual motion, vertebrate circuits must transform transient sensory signals into persistent, lateralized activity. The synaptic architecture supporting this computation remains unclear. We combined calcium imaging and correlative electron microscopy (EM) in larval zebrafish with an independent whole-brain EM dataset, reconstructing 1,246 neurons in and connected to the anterior hindbrain, a region previously implicated in the temporal integration of visual evidence. We identified four broad functional and morphological classes interconnected through recurrent excitation, interhemispheric and ipsilateral inhibitory motifs, as well as long-range inputs from rostral visual regions. We then trained bilateral neural networks constrained by the measured neuron-to-neuron connectivity as a fixed anatomical mask, while optimizing unknown physiological weights. These models reproduced population dynamics and predicted responses to previously untested motion stimuli. Shuffling connectivity or selectively removing recurrent connections impaired model performance, whereas removing an equivalent number of random connections across the network had much smaller effects. Our results identify an anatomical network compatible with visual-motion integration and implicate specific recurrent connections in its computational dynamics. Together, our results link functional dynamics with synaptic architecture in a vertebrate sensorimotor circuit and provide a framework for interpre...
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Editorial Critique, Methodological Value & Reusability Guide

Structured via CNS Domain Knowledge Engine

1. Scientific Context & Premise

Primary Premise (bioRxiv (Neuroscience)): "To integrate noisy visual motion, vertebrate circuits must transform transient sensory signals into persistent, lateralized activity." Within Amyotrophic Lateral Sclerosis (ALS) & Motor Neuron Disease, this work examines bioRxiv Preprint, neuroscience, ALS in relation to plasma/CSF Neurofilament Light Chain (NfL), C9orf72/SOD1/FUS genetics, cryptic exon biomarkers, and ALSFRS-R slopes. Authored by Boulanger-Weill, J., Kaempf, F., Schuhknecht, G. F. P..

2. Study Architecture & Findings

Study Architecture: Experimental / Clinical CNS Design (primary study cohort) utilizing Preprint Article, Open Science [DOI: 10.1101/2025.03.14.643363]. Key reported conclusion: "Together, our results link functional dynamics with synaptic architecture in a vertebrate sensorimotor circuit and provide a framework for interpre..."

3. Secondary Analysis & Reusability

Secondary Analysis Applications: (1) Cross-referencing Preprint Article, Open Science variables (bioRxiv Preprint, neuroscience, ALS) against open repositories in Amyotrophic Lateral Sclerosis (ALS) & Motor Neuron Disease; (2) Benchmarking feature distributions and effect sizes reported in "Correlative light and electron microscopy identifies circuit motifs underlying p"; (3) Informing cohort stratification and endpoint selection.

4. Methodological Caveats & Governance

Preprint Status: This record is an unrefereed preprint; findings should be verified against subsequent peer-reviewed publication. When integrating these Preprint Article, Open Science findings, account for cohort-specific inclusion criteria (primary study cohort), potential site/instrument batch effects, and repository license terms (cc_by_nc).

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Data Access, Reproducibility & Analysis Starter Guide

FAIR Open Science & Clinical Metadata Verification Protocol

FAIR Metadata / API

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Open the primary repository directly or download structured metadata (JSON / CSV) in one click.

Open Primary Data (bioRxiv (Neuroscience))Download Data

This resource is indexed under FAIR (Findable, Accessible, Interoperable, and Reusable) open-science metadata standards, enabling programmatic cross-referencing across Europe PMC, Semantic Scholar, ClinicalTrials.gov, and CNS Open Data.

Programmatic Data Retrieval (Python Starter Code & Recommended SDKs)

Python Quickstart: Query Europe PMC & Semantic Scholar Metadata

# Fetch structured bibliographic & open-access data via Europe PMC REST API
import urllib.request
import urllib.parse
import json

query = "DOI:\"10.1101/2025.03.14.643363\""
url = f"https://www.ebi.ac.uk/europepmc/webservices/rest/search?query={urllib.parse.quote(query)}&format=json&resultType=core"

with urllib.request.urlopen(url, timeout=10) as response:
    payload = json.loads(response.read().decode("utf-8"))
    results = payload.get("resultList", {}).get("result", [])
    if results:
        record = results[0]
        print("Title:", record.get("title"))
        print("Journal / Source:", record.get("journalTitle") or record.get("bookOrReportDetails"))
        print("Cited By Count:", record.get("citedByCount", 0))

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Standardized 4-Step Workflow & Governance Checklist

Standardized Acquisition & Preprocessing Workflow

1. Programmatic Metadata & Full-Text OA Retrieval

Query Europe PMC or Crossref REST APIs using the persistent DOI/URL to retrieve structured XML full text, supplementary tables, and grant links.

2. Study Design & Cohort Eligibility Screening

Extract sample size, inclusion/exclusion criteria, and primary outcome endpoints for systematic review (PRISMA) inclusion.

3. Data Availability & Supplementary Repository Linkage

Locate accession numbers (GEO, SRA, OpenNeuro, DANDI, Zenodo, Figshare) referenced in the Data Availability section.

4. Citation Graph & Replication Tracking

Monitor supporting and contrasting citations over time to verify whether key findings have been independently replicated.

Reproducibility & Governance Checklist

  • Verify whether the source is a peer-reviewed journal publication or an unrefereed preprint before clinical citation.
  • Check supplementary data licenses (CC-BY / CC0) when extracting figures or summary statistics for meta-analyses.
  • Cross-reference NCT clinical trial identifiers when evaluating therapeutic efficacy or biomarker endpoints.

Tags & Modalities

Preprint ArticleOpen Science#bioRxiv Preprint#neuroscience#ALS

Bibliometrics, Peer-Review Status & Citation Export

Cross-referenced via Semantic Scholar, Europe PMC & bioRxiv

1. Citation Metrics & Context Breakdown

8
Total Citations
0
Influential Citations

Citation Context Breakdown

Supporting: 2
Mentioning: 6
Contrasting: 0

2. Peer-Review Validation & Revision History

Preprint Article (bioRxiv / medRxiv — Awaiting Peer Review)

This article is indexed as an unrefereed preprint. Our ingestion pipeline periodically queries Europe PMC and bioRxiv/medRxiv APIs to automatically link the final peer-reviewed journal DOI once published.

Preprint Revision History

v12025-03-15
10.1101/2025.03.14.643363
v22025-06-01
10.1101/2025.03.14.643363
v32026-10-23
10.1101/2025.03.14.643363

3. Standardized Academic Citation & BibTeX Export

Selected Format (APA)
Boulanger-Weill, J. et al. (2026). Correlative light and electron microscopy identifies circuit motifs underlying processing of noisy visual motion in larval zebrafish. bioRxiv (Neuroscience). https://doi.org/10.1101/2025.03.14.643363
BibTeX Entry (LaTeX / Reference Managers)
@article{j.2026bior,
  title = {Correlative light and electron microscopy identifies circuit motifs underlying processing of noisy visual motion in larval zebrafish},
  author = {Boulanger-Weill, J. and Kaempf, F. and Schuhknecht, G. F. P. and Garza, R. and Schalek, R. L.},
  year = {2026},
  journal = {bioRxiv (Neuroscience)},
  howpublished = {\url{https://doi.org/10.1101/2025.03.14.643363}},
  doi = {10.1101/2025.03.14.643363},
  note = {CNS Open Data: als}
}

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This page provides structured scientific metadata, methodological critiques, and open-data reusability guidelines intended strictly for neuroscience researchers and data scientists. It does not constitute medical advice, clinical diagnosis, or treatment recommendations.

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