Towards characterizing the distinct contributions of genetically defined neuron populations in value-based decision making

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Abstract/Contents

Abstract: Animals must constantly engage in economic choice behaviors, evaluating the available options in their environments and deciding which to pursue. However, how these decisions are computed in the brain remains poorly understood. One reason for this is because most studies of this form of decision-making have been performed in primates, for which we currently lack tools for recording and manipulating the activity of defined cell types. Here, in preliminary work I analyze single cell activity data from mice and reveal differential responses to cue and reward in excitatory and inhibitory populations of neurons. This highlights the need for the development of economic choice paradigms that can be integrated with animal models and tools for the manipulation of genetically defined cell types. To meet this need, my honors thesis implements a head-fixed, value-based decision-making paradigm in mice. Using the behavioral apparatus and training protocol designed, mice learned to choose between two olfactory cues that predicted the delivery of one of the two reward types (sugar water or water). Analysis of choice data reveals that mice make appropriate decisions based on reward type and amount, suggesting they integrate information about both reward quality and quantity to guide behavior. With this paradigm in mice, we will be able to exploit the genetic accessibility of the mouse to probe neural circuits that mediate economic decisions.

Author	Mudipalli, Rachana
Thesis advisor	Deisseroth, Karl
Thesis advisor	Gore, Felicity
Thesis advisor	Boahen, Kwabena
Degree granting institution	Stanford University
Department	Department of Bioengineering

Subject	Choice (Psychology)
Subject	Neurosciences
Subject	Calcium imaging
Subject	Neural circuitry
Subject	Choice (Psychology) > Economic aspects
Subject	Reward (Psychology)
Subject	Substance abuse
Subject	Drug addiction
Subject	Decision making > Psychological aspects
Subject	Bioengineering
Subject	Orbitofrontal Cortex
Genre	Text
Genre	Thesis

DOI	https://doi.org/10.25740/dz767bb5203
Location	https://purl.stanford.edu/dz767bb5203

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License: This work is licensed under a Creative Commons Attribution Non Commercial 4.0 International license (CC BY-NC).

Preferred citation: Mudipalli, R. (2022). Towards characterizing the distinct contributions of genetically defined neuron populations in value-based decision making. Stanford Digital Repository. Available at https://purl.stanford.edu/dz767bb5203

Undergraduate Theses, School of Engineering

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