Evidence map›Paper›PMID 39669416›Full record

ArticleOpen research Europe2023

Parametrizing analog multi-compartment neurons with genetic algorithms.

Raphael Stock, Jakob Kaiser, Eric Müller, Johannes Schemmel, Sebastian Schmitt

Abstract read
In one paragraph

Article in Open research Europe, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. 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

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Raphael StockKirchhoff Institute for Physics, Heidelberg University, Heidelberg, 69120, Germany.ORCID https://orcid.org/0009-0008-5531-1072
Jakob KaiserKirchhoff Institute for Physics, Heidelberg University, Heidelberg, 69120, Germany.ORCID https://orcid.org/0000-0002-3586-2634
Eric MüllerEuropean Institute for Neuromorphic Computing, Heidelberg University, Heidelberg, 69120, Germany.
Johannes SchemmelKirchhoff Institute for Physics, Heidelberg University, Heidelberg, 69120, Germany.
Sebastian SchmittDepartment for Neuro- and Sensory Physiology, University Medical Center Göttingen, Göttingen, 37077, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Finding appropriate model parameters for multi-compartmental neuron models can be challenging. Parameters such as the leak and axial conductance are not always directly derivable from neuron observations but are crucial for replicating desired observations. The objective of this study is to replicate the attenuation behavior of an excitatory postsynaptic potential (EPSP) traveling along a linear chain of compartments on the analog BrainScaleS-2 neuromorphic hardware platform. Methods: In the present publication we use genetic algorithms to find suitable model parameters. They promise parameterization without domain knowledge of the neuromorphic substrate or underlying neuron model. To validate the results of the genetic algorithms, a comprehensive grid search was conducted. Furthermore, trial-to-trial variations in the analog system are counteracted utilizing spike-triggered averaging. Results and conclusions: The algorithm successfully replicated the desired EPSP attenuation behavior in both single and multi-objective searches illustrating the applicability of genetic algorithms to parameterize analog neuromorphic hardware.

Indexed as

analog computinggenetic algorithmmulti-compartmentneuromorphic

Identifiers

PMID39669416
PMCPMC11635192

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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.