Economic decision making in primate anterior cingulate cortex- behavioral and electrophysiological study

Andreu Guarro, Meritxell

Economic decision making in primate anterior cingulate cortex- behavioral and electrophysiological study

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Andreu Guarro, M. Economic decision making in primate anterior cingulate cortex- behavioral and electrophysiological study. 2017. handle: http://hdl.handle.net/10230/32896

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Abstract

Dorsal anterior cingulate cortex (dACC) is related to cognitive function and seems to have an important role in decision-making. After training, rhesus macaques can serve as a good model to study choice behaviour. During decision, a lot of factors are considered but will focus on the values of presented offers and their probabilities. The aim of this project is to find a model that would accurately describe variables which guide the animal behaviour during a gambling task and to test if these variables are encoded in dACC. To achieve these objectives, an analysis of behavioral data was performed, making a comparison between models of expected and subjective offers' value. The model of expected value was done considering each offer as the sum of the two values (gain and loss) multiply by the correspondent probability. Then, extending this concept, the model of subjective value was defined according to the prospect theory. Also, an analysis of the electrophysiological data was done, looking for neural correlates of model variables. The results have shown that the animals learnt the task and made their decisions considering the relevant task parameters. In addition, we found that the model based on prospect theory better explains animal behavior than the expected value model. Moreover, an overweight of the parameters related to gains and an underweight of the ones related to losses was observed. Analysis of the firing rates of dACC neurons revealed encoding of offer values in correspondence with the behavioral models. In addition, there was a clear distinction in neuronal activity between gains and losses. These results confirm the relation with dACC and decision making, and the fact that the different parameters are weighted before being analyzed when a decision has to be made. In this case, wins were more relevant than losses. The natural extension of this work for the future would be to model transformation of probabilities apart from offer values in order to understand better the decision process. Also, making similar studies in other brain areas could help to answer which areas contribute in the process and how the information is linked among them. These types of studies can help us to understand the decision mechanisms in a better way.