Evidence map›Paper›PMID 37274203›Full record

ArticleFrontiers in neuroscience2023

Retinal ganglion cells undergo cell type-specific functional changes in a computational model of cone-mediated retinal degeneration.

Aiwen Xu, Michael Beyeler

Open access · goldAbstract read
In one paragraph

Article in Frontiers in neuroscience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.7field-weighted citation impact, top 34% 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

2 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Aiwen XuDepartment of Computer Science, University of California, California, Santa Barbara, CA, United States.
Michael BeyelerDepartment of Computer Science, University of California, California, Santa Barbara, CA, United States.
University of California, Santa Barbara · US

Funding

Virtual prototyping for retinal prosthesis patientsR00EY029329 · NEI · UNIVERSITY OF CALIFORNIA SANTA BARBARA · PI BEYELER, MICHAEL · 2020 to 2022
$633k
NEI NIH HHS R00 EY029329
6 · The paper itself

Abstract

Introduction: Understanding the retina in health and disease is a key issue for neuroscience and neuroengineering applications such as retinal prostheses. During degeneration, the retinal network undergoes complex and multi-stage neuroanatomical alterations, which drastically impact the retinal ganglion cell (RGC) response and are of clinical importance. Here we present a biophysically detailed Methods: The model included 11, 138 cells belonging to nine different cell types (cone photoreceptors, horizontal cells, ON/OFF bipolar cells, ON/OFF amacrine cells, and ON/OFF ganglion cells) confined to a 300 × 300 × 210μm patch of the parafoveal retina. After verifying that the model reproduced seminal findings about the light response of retinal ganglion cells (RGCs), we systematically introduced anatomical and neurophysiological changes (e.g., reduced light sensitivity of photoreceptor, cell death, cell migration) to the network and studied their effect on network activity. Results: The model was not only able to reproduce common findings about RGC activity in the degenerated retina, such as hyperactivity and increased electrical thresholds, but also offers testable predictions about the underlying neuroanatomical mechanisms. Discussion: Overall, our findings demonstrate how biophysical changes typified by cone-mediated retinal degeneration may impact retinal responses to light and electrical stimulation. These insights may further our understanding of retinal processing and inform the design of retinal prostheses.

Indexed as

computational modelsretinaretinal degenerationretinal ganglion cellsretina model

Identifiers

PMID37274203
PMCPMC10233015
OpenAlexW4377023576

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.