Decision-Making: A Multi-Stage Approach
Decision-making is a crucial element in many disciplines such as psychology, neuroscience, economics, and machine learning. Tests of decision-making typically present one of two stimulus possibilities and participants decide which one was presented. Such decision-making is usually modeled using one-stage drift diffusion models. However, these classical models fail to explain the results of two-stimulus, feature fusion paradigms, where the second stimulus influences decisions more strongly than the first one.
The main goal of the project is to provide a new, biologically plausible model of multi-stage decision-making. At each retinotopic location, there are two-stage decision making units, whose outputs are integrated across space and time.To estimate parameters of the model, we will experimentally determine the key values in psychophysical experiments.
Mot-clé: Decision-making, feature integration, computational modeling, drift diffusion modelsretourner