Neural network features distinguish chemosensory stimuli in Caenorhabditis elegans

How, Javier J, Navlakha, Saket, Chalasani, Sreekanth H (November 2021) Neural network features distinguish chemosensory stimuli in Caenorhabditis elegans. PLoS Computational Biology, 17 (11). e1009591. ISSN 1553-7358

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URL: https://www.ncbi.nlm.nih.gov/pubmed/34752447
DOI: 10.1371/journal.pcbi.1009591

Abstract

Nervous systems extract and process information from the environment to alter animal behavior and physiology. Despite progress in understanding how different stimuli are represented by changes in neuronal activity, less is known about how they affect broader neural network properties. We developed a framework for using graph-theoretic features of neural network activity to predict ecologically relevant stimulus properties, in particular stimulus identity. We used the transparent nematode, Caenorhabditis elegans, with its small nervous system to define neural network features associated with various chemosensory stimuli. We first immobilized animals using a microfluidic device and exposed their noses to chemical stimuli while monitoring changes in neural activity of more than 50 neurons in the head region. We found that graph-theoretic features, which capture patterns of interactions between neurons, are modulated by stimulus identity. Further, we show that a simple machine learning classifier trained using graph-theoretic features alone, or in combination with neural activity features, can accurately predict salt stimulus. Moreover, by focusing on putative causal interactions between neurons, the graph-theoretic features were almost twice as predictive as the neural activity features. These results reveal that stimulus identity modulates the broad, network-level organization of the nervous system, and that graph theory can be used to characterize these changes.

Item Type: Paper
Subjects: bioinformatics
organism description > animal > C elegans
bioinformatics > computational biology > algorithms
organism description > animal
bioinformatics > computational biology
organs, tissues, organelles, cell types and functions > tissues types and functions > neural networks
organs, tissues, organelles, cell types and functions > tissues types and functions > sensory feedback
CSHL Authors:
Communities: CSHL labs > Navlakha lab
SWORD Depositor: CSHL Elements
Depositing User: CSHL Elements
Date: 9 November 2021
Date Deposited: 10 Nov 2021 16:40
Last Modified: 24 Jan 2024 20:58
PMCID: PMC8604368
URI: https://repository.cshl.edu/id/eprint/40414

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