SOURCE-LINKED INTELLIGENCE

Personalized priors: How individual differences in internal models explain idiosyncrasies in natural vision

CORDIS · observation · Publication date unknown

ral and neural levels. Second, we will harness variations in people’s drawings to determine the critical features of internal models that guide scene vision. Third, we will enrich the currently best deep learning models of vision with information about internal models to obtain computational predictions for individual scene perception. Finally, we will systematically investigate how individual differences in internal models mimic idiosyncrasies in visual and linguistic experience, functional brain architecture, and scene exploration. Our project will illuminate natural vision from a new angle – starting from a characterization of individual people’s internal models of the world. Through this change of perspective, we can make true progress in understanding what exactly is predicted in the predictive brain. Predictive processing, internal models, natural vision, scene perception, visual cortex, drawing, fMRI, EEG, deep neural network models, representational similarity analysis

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recordType

award

status

SIGNED

region

EU

value

1484625

unit

EUR