Please use this identifier to cite or link to this item: http://dr.iiserpune.ac.in:8080/xmlui/handle/123456789/8870
Title: Network modeling and behavioral characterization of Hydra contraction dynamics
Authors: Fairhall, Adrienne
GUPTA, DIVYANSH
Dept. of Biology
20191007
Keywords: Computational neuroscience
Biophysics
Invertebrate neurophysiology
Animal behavior
Issue Date: May-2024
Citation: 57
Abstract: Hydra is a cnidarian possessing some of the earliest extant nervous systems compris- ing of nerve nets of diffusely spread neurons that coordinate its behavior without any centralization. It is also a well studied model organism in developmental biology for its remarkable ability to regenerate. With its simple nervous system it exhibits a behavioral repertoire comprising of spontaneous contractions and multi-step whole-body coordi- nated behaviors like somersaulting and prey-capture for feeding. How the nerve net of Hydra orchestrates these movements is not understood. Recent advances in genomics and calcium imaging allow for unprecedented insights into large scale neural recordings, the size of hydra also makes it particularly appealing for complete observations of neural activity and behavior. Using a two population network model driven by mechanosensitivity incorporating gap junctions and mutual inhibition we model the neural activity that controls these spontaneous contractions and put together ideas about the neurophysiology of Hydra into a coherent mechanistic model. I extract neural activity and behavior from a dataset comprising of calcium imaging videos of freely behaving animals in a petri-dish before being bisected, into two halves which were then imaged separately over the course of regeneration, and use these to constrain and validate the model. I show that this model captures the switching of activity between the sub-networks and the recovery of the contraction behaviour after bisection, but misses higher order variation in the activity which might be light-driven or affected by many other sources of variability in the animal’s neural circuitry including interactions with other sub-networks, neuropeptides and a stochastic water influx. This model could serve as the basis for future work incorporating more detail from Hydra neurophysiology as it gets discovered and provide a more comprehensive understanding of the hydra nervous system.
URI: http://dr.iiserpune.ac.in:8080/xmlui/handle/123456789/8870
Appears in Collections:MS THESES

Files in This Item:
File Description SizeFormat 
20191007_Divyansh_Gupta_MS_ThesisMS Thesis5.46 MBAdobe PDFView/Open    Request a copy


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.