OSCR

Imprecision in Vision: Lessons From Neural Circuits in the Fly.

Overview

Authors: Mathias F Wernet1, Marion Silies2
  1. Fachbereich Biologie, Chemie & Pharmazie, Institut Für Biologie – Neurobiologie, Berlin, Germany
  2. Institute of Developmental Biology and Neurobiology, Johannes‐Gutenberg University Mainz, Mainz, Germany
Institutions: Johannes Gutenberg University Mainz (Germany)
Dates: published online 3 March 2026; in print March 2026
Type: Review · Language: English
License: CC BY
Identifiers: DOI 10.1002/bies.70122 · PMID 41777098 · PMCID PMC12957902 · OpenAlex W7133523808
Open access: hybrid, a free copy (OpenAlex)
Status: dead link
Categories: drosophila (organism), cellular / molecular (subfield)
Methods: Machine learning
Keywords: cell type, connectome, Drosophila, heterogeneity, synaptic connectivity, visual system
MeSH: Drosophila melanogaster*, Neural Pathways*, Vision, Ocular*, Visual Perception*, Animals, Synapses (* major topic)
Topic: Visual perception and processing mechanisms (Cognitive Neuroscience, Neuroscience), according to OpenAlex
Funding: German Research Foundation; Deutsche Forschungsgemeinschaft
Citations: not cited yet (Europe PMC); 106 references in the paper

Abstract

Visual systems appear like homogenous structures, where identical functional units repeat themselves across the eye. This architecture is thought to ensure a uniform sampling of the surrounding environment. Furthermore, anatomically and functionally identical properties of single units belonging to the same cell type, yet located across retinotopical positions are thought to ensure translational invariance. At the same time, regional differences and stochastic variations in microcircuit architecture have been linked to the processing of specific visual features. Recent access to connectomic datasets has revealed heterogeneity in visual circuitry that is at odds with these criteria: Cells considered to belong to the same type are variable in number and identity of connected partners, as well as in the relative number of synapses. This variable connectivity suggests that heterogeneous computations, even within defined cell types, is the rule, rather than the exception. It is therefore an exciting question whether these network properties increase functional variability, or even functional robustness, of visual processing.

Reproduced under the paper's license (CC BY), from the paper cited above.

Code

No file of the authors' code could be read here: it is described below, and read at its source.

Silieslab/Bioessays_2026_WernetSilies

License: none: the authors keep all their rights
State: the link is dead, verified on 30 September 2026
Evidence: found in the paper
Software Heritage: not archived
Found in: “Data Availability Statement”
Not found: README, license file, CITATION.cff, environment file, tests, continuous integration, documentation
Availability: 1 check, the latest on 30 September 2026: the link is dead
  • 30 September 2026: the link is dead

The paper's code and data availability statement is in the Data section.

Tracing map

Proposed by the machine: these links were found in the paper and verified at the source, without human review. The map will receive a Zenodo DOI once one of the paper's authors has validated it with their ORCID.

What the map holds:

  • 1 repository of the authors' code, each at its verified commit, with its license and how the link was found in the paper;
  • 0 scripts, each with its path and the digest of its content;
  • no match between paragraphs and code yet;
  • neither the text of the paper nor the code itself.

Its JSON (tracing-map.json) is deposited on Zenodo with its DOI once the map is validated.

Data

No dataset and no data link were found in the paper.

Data Availability Statement

Code related to the production of figures in this article is available at github.com/Silieslab/Bioessays_2026_WernetSilies.

Reproduced under the paper's license (CC BY), from the paper cited above.

Versions

The history of this record: each version stored by the harvester or made by a correction of its authors or of the maintainers of its code, and what changed in its facts. The texts of the paper (its abstract, its availability statements) are not part of it; versions that changed only those are not listed.

Version 1, 30 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 2 authors, 6 keywords, 6 MeSH terms, 2 funders, 106 references.

Cite

This paper

Wernet, M. F., & Silies, M. (2026). Imprecision in Vision: Lessons From Neural Circuits in the Fly. BioEssays : news and reviews in molecular, cellular and developmental biology, 48(3), e70122. https://doi.org/10.1002/bies.70122

BibTeX

@article{wernet2026imprecision,
author = {Wernet, Mathias F and Silies, Marion},
title = {{Imprecision in Vision: Lessons From Neural Circuits in the Fly}},
journal = {BioEssays : news and reviews in molecular, cellular and developmental biology},
year = {2026},
month = mar,
volume = {48},
number = {3},
pages = {e70122},
publisher = {Wiley},
issn = {0265-9247},
doi = {10.1002/bies.70122},
url = {https://doi.org/10.1002/bies.70122},
pmid = {41777098},
pmcid = {PMC12957902}
}

RIS

TY - JOUR
AU - Wernet, Mathias F
AU - Silies, Marion
TI - Imprecision in Vision: Lessons From Neural Circuits in the Fly
T2 - BioEssays : news and reviews in molecular, cellular and developmental biology
J2 - Bioessays
PY - 2026
DA - 2026/03/01
VL - 48
IS - 3
SP - e70122
SN - 0265-9247
PB - Wiley
DO - 10.1002/bies.70122
UR - https://doi.org/10.1002/bies.70122
LA - en
ER -

CSL-JSON

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