ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2022
Computational Inference of Synaptic Polarities in Neuronal Networks.
Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed, 9 citations in OpenAlex.
- A positive statistical benchmark to assess network agreement.Nature communications · 2023Article
- NeuronAlg: An Innovative Neuronal Computational Model for Immunofluorescence Image Segmentation.Sensors (Basel, Switzerland) · 2023Article
- Computational Inference of Synaptic Polarities in Neuronal Networks.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2022Article
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Authors and funding
3 authors at 1 institution in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Synaptic polarity, that is, whether synapses are inhibitory (-) or excitatory (+), is challenging to map, despite being a key to understand brain function. Here, synaptic polarity is inferred computationally considering three experimental scenarios, depending on the nature of available input data, using the Caenorhabditis elegans connectome as an example. First, the inputs consist of detailed neurotransmitter (NT) and receptor (R) gene expression, integrated through the connectome model (CM). The CM formulates the problem through a wiring rule network that summarizes how NT-R pairs govern synaptic polarity, and resolves 356 synaptic polarities in addition to the 1752 known polarities. Second, known synaptic polarities are considered as an input, in addition to the NT and R gene expression data, but without wiring rules. These data train the spatial connectome model, which infers the polarity of 81% of the CM-resolved connections at
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Registered trials
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.