ERC Consolidator Grant · 2023
Flexible Dimensionality of Representational Spaces in Category Learning
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 expansion. Yet, dimensionality compression and expansion both have advantages and disadvantages, and some studies find dimensionality compression where others find expansion. This raises the hitherto…
From the public funding record at EU CORDIS. Describes the funded project, not the reviews below.