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Document Type

Open Access Dissertation

Degree Name

Doctor of Philosophy (PhD)

Degree Program

Neuroscience and Behavior

Year Degree Awarded

2015

Month Degree Awarded

September

First Advisor

Heather N. Richardson

Second Advisor

Jeffrey Podos

Subject Categories

Applied Behavior Analysis | Behavioral Neurobiology | Behavior and Ethology | Cognitive Neuroscience | Developmental Biology | Developmental Neuroscience

Abstract

Impulsive choice is defined as the preference for a small immediate reward over a larger delayed reward. Individual variablity in impulsive choice correlates with many socially relevant behaviors. Although forms of impulsive choice have been studied in both behavioral ecology and psychology, the exchange of knowledge between these fields is just beginning. Drawing from both of these fields will improve our research methods allowing for a more detailed understanding of this complex behavior. Existing tasks to measure impulsive choice conflate the delay and quantity of the reward. To address this, I have drawn from foraging research to establish a method to isolate each single parameter: either the delay, or quantity of the reward. The isolation of one of these parameters at a time is a central theme in this thesis. I have applied these new methods to explore the behavioral components of impulsive choice. Contrary to an assumption in the existing literature, I find that impulsive choice and delay discounting are distinct behaviors; quantity may in fact be a larger contributer to impulsive choice than delay. Next, I assess the relationship between the delay component of impulsive choice and alcohol addiction. The data suggest that the delay component of impulsive choice is associated with alcohol consumption, but causal hypotheses are not supported. Instead the data suggest that this component of impulsive choice and acohol consumption may share a common mechanism. Lastly, I propose a novel neural circuitry that could underly impulsive choice behaviors. I conduct a preliminary test of a prediction of the model. The results suggest the present model may be incorrect. This, however, highlights the usefulness of the novel methods presented in this dissertation as they allow for more detailed testing of specific models of this complex behavior.

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