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[2308.06578] The time is ripe to reverse engineer an entire nervous system: simulating behavior from neural interactions

arxiv.org · 873 words · saved by 1 readers

Abstract:Just like electrical engineers understand how microprocessors execute programs in terms of how transistor currents are affected by their inputs, neuroscientists want to understand behavior production in terms of how neuronal outputs are affected by their inputs and internal states. This dependency of neuronal outputs on inputs can be described by a state-dependent input-output (IO)-function. However, to reliably identify these IO-functions, we need to perturb each input and combinations of inputs while observing all the outputs. Here, we argue that such completeness is possible in C. elegans; a complete description that goes all the way from the activity of every neuron to predict behavior. The established and growing toolkit of optophysiology can non-invasively capture and control every neuron's activity and scale to countless experiments. The information from many such experiments can be pooled while capturing the inter-individual variability because neuronal identity and function are largely conserved across individuals. Just like electrical engineers use transistor IO-functions to simulate program execution, we argue that neuronal IO-functions could be used to simulate the impressive breadth of brain states and behaviors of C. elegans.

[2308.06578] The time is ripe to reverse engineer an entire nervous system: simulating behavior from neural interactions --> Quantitative Biology > Neurons and Cognition arXiv:2308.06578 (q-bio) [Submitted on 12 Aug 2023 ( v1 ), last revised 18 Sep 2024 (this version, v5)] Title: The time is ripe to reverse engineer an entire nervous system: simulating behavior from neural interactions Authors: Gal Haspel (NJIT), Ben Baker (Colby College), Isabel Beets (KU Leuven), Edward S Boyden (MIT), Jeffrey Brown (MIT), George Church (Harvard University), Netta Cohen (University of Leeds), Daniel Colon-Ra

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