Active Psychology & Behaviour Brain & Nervous System

A whole-brain model of stimulus valence integration: From sensory processing to adaptive behaviour

Summary

Original abstract (not yet simplified)

Approach or avoidance of meaningful stimuli with positive or negative valence underlie many adaptive, goal-directed behaviours. Stimulus valence can be innate or learned upon experience, and both must be integrated continuously to guide behaviour in each moment. In the insect brain, this integration occurs in the convergence of two pathways, encoding innate and learned valences, the lateral horn and the...

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Approach or avoidance of meaningful stimuli with positive or negative valence underlie many adaptive, goal-directed behaviours. Stimulus valence can be innate or learned upon experience, and both must be integrated continuously to guide behaviour in each moment. In the insect brain, this integration occurs in the convergence of two pathways, encoding innate and learned valences, the lateral horn and the mushroom body, respectively. Prior research has focused on encoding stimulus identity separately for innate or learned valence and learned behaviour initiation. However, insights into the interaction and integration of innate and learned valences are sparse. Deploying the available synaptic-level connectome of the entire Drosophila larva brain, I will implement the first whole-brain model to dynamically investigate processing from sensory input to behaviour. After creating the network architecture from the connectome, I will fit the model parameters using calcium imaging data that quantifies the response of key neurons in the valence integration circuit to sensory stimuli before, during, and after learning. Using the resulting comprehensive model, I will investigate the mechanisms of valence integration and examine the contributions of innate and learned valence in each moment. This multidisciplinary approach combines the complementary benefits of model and lab experiments. I will use the model to infer the functional roles of individual circuit components. Predictions from these simulations will be tested in naturalistic experiments using camera tracking of freely behaving larvae to quantify changes in approach and avoidance behaviour to sensory stimuli before, during, and after learning as proxies for innate and learned valence. Optogenetic activation or inactivation of neurons will allow me to test model predictions directly.This project aims to understand how stored and new information about sensory stimuli interact to influence animal behaviour jointly.

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