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Mr Nikitas Angeletos Chrysaitis (Institute for Adaptive and Neural Computation, University of Edinburgh)7/19/22, 2:30 PMPredictive Processes and Statistical LearningTalk
Bayesian and predictive coding theories of cognition view perception as the combination of sensory inputs with prior knowledge of the environment. On average, this process results in more accurate and faster perceptual judgements, as long as this knowledge is accurate. To be optimal, priors should update in the face of new information. Past studies have shown that this is indeed the case for...
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Davide Giana (SISSA)7/19/22, 2:50 PMPredictive Processes and Statistical LearningTalk
Perceptual memories are the storage of our experiences; they are the basis for understanding the external world and guiding our decisions. Despite fast-paced research, behavioural and cognitive constructs tend to be custom built around a preferred task and general principles across tasks seem to be missing.
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To address these issues, we aim to build a computational model comprised of... -
Magda del Rio7/19/22, 3:10 PMPredictive Processes and Statistical LearningTalk
Our perception does not depend exclusively on the immediate sensory input. We exploit the statistical regularities in the environment, leading, e.g., to attractive perceptual choice history biases in a stable world, yet the conditions and mechanisms facilitating this flexible use of prior information to predict the future are unclear. Here we use a standard perceptual decision-making task and...
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