Hunger And Thirst Guided Decision Making Via Hippocampal Encoding Of Internal State

Lead Research Organisation: University College London
Department Name: Neuroscience Physiology and Pharmacology

Abstract

In order to survive, animals must act to address their core physiological needs. For example, when an animal is hungry, it must alter its behaviour in order to increase the likelihood of finding food. Similarly, when thirsty, it must increase the likelihood of finding water. Such flexible and dynamic changes to behavioural goals are crucial for correct planning of ingestive behaviour, and their dysfunction is thought to be a major factor in disorders such as obesity and anorexia.

Key to such behaviour is the ability to understand that the outcome associated with an action or cue in the environment is often different dependent on your internal state. As a result, it is often proposed that internal state can act as a context - where appropriate behaviour can be learnt differentially, dependent on whether the animal is hungry or thirsty. However, how peripheral signals of hunger and thirst are integrated into the wider neural circuits essential for contextual planning and decision making - crucial to support such flexible goal directed behaviour - remains unclear.

In this proposal we will investigate the hypothesis that the ventral hippocampus - an area key for contextual learning - is crucial to allow flexible behaviour guided by internal state. We will use a combination of state-of-the-art imaging, electrophysiology and optogenetics to directly investigate at the synaptic, cellular and circuit level how hunger and thirst information are represented in the hippocampus, and how this information is used to guide internal state dependent decision making.

Our overarching aim is to provide a molecules-to-circuits-to-behaviour description of how internal state information signalled in the periphery can be utilised to guide decision-making behaviour. Our goal is that this research will provide a mechanistic framework to understand how these processes fail in preclinical models of eating disorders, and provide avenues to more effective treatments for these disorders.

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