CORDIS Project
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This project investigates how the human visual system learns to classify complex, high-dimensional inputs. By exploring the balance between dimensionality compression and expansion, it aims to understand the neural mechanisms behind flexible learning strategies in visual tasks.
Our visual system frequently has to classify complex, high dimensional inputs. A key learning objective of the brain is thus to identify diagnostic dimensions.
Often, tasks require simultaneous consideration of multiple dimensions.
Yet, learning many dimensions is computationally challenging.
Here, I ask how the visual system tackles the challenge of learning high dimensional tasks.
Some theories suggest that the brain does so by compressing dimensions, while others suggest dimensionality expans…
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