Evidence map›Paper›PMID 38790447›Full record

ArticleBrain sciences2024

Error Function Optimization to Compare Neural Activity and Train Blended Rhythmic Networks.

Jassem Bourahmah, Akira Sakurai, Paul S Katz, Andrey L Shilnikov

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In one paragraph

Article in Brain sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Jassem BourahmahNeuroscience Institute, Georgia State University, 100 Piedmont Ave., Atlanta, GA 30303, USA.
Akira SakuraiNeuroscience Institute, Georgia State University, 100 Piedmont Ave., Atlanta, GA 30303, USA.ORCID 0000-0003-2858-1620
Paul S KatzNeuroscience & Behavior Graduate Program, Department of Biology, University of Massachusetts, Amherst, MA 01003, USAORCID 0000-0003-0786-1287
Andrey L ShilnikovDepartment of Mathematics & Statistics, Neuroscience Institute, Georgia State University, 100 Piedmont Ave., Atlanta, GA 30303, USA.ORCID 0000-0002-4879-4327

Funding

Brain and Behaviours program by Georgia State University 45672National Science Foundation IOS-1455527
6 · The paper itself

Abstract

We present a novel set of quantitative measures for "likeness" (error function) designed to alleviate the time-consuming and subjective nature of manually comparing biological recordings from electrophysiological experiments with the outcomes of their mathematical models. Our innovative "blended" system approach offers an objective, high-throughput, and computationally efficient method for comparing biological and mathematical models. This approach involves using voltage recordings of biological neurons to drive and train mathematical models, facilitating the derivation of the error function for further parameter optimization. Our calibration process incorporates measurements such as action potential (AP) frequency, voltage moving average, voltage envelopes, and the probability of post-synaptic channels. To assess the effectiveness of our method, we utilized the sea slug

Indexed as

blended approachCPGmodel trainingneural networkparameter optimization

Identifiers

PMID38790447
PMCPMC11117979

What OpenQuestion holds

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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.