Representational geometry reveals how neuronal diversity supports perceptual performance
Saraf, S.; Movshon, J. A.; Chung, S.
Show abstract
A complete understanding of population coding requires connecting multiple levels of neural processing: individual responses, population representations, and behavior. We link these by relating the distribution of neuronal tuning properties to a populations representational geometry and its efficiency for perceptual tasks. We use theory, analysis of recordings from macaque primary visual cortex (V1), and simulations to reveal how diversity of tuning amplitude and bandwidth enhances the population code for visual discrimination and identification. Both types of diversity drive different, but complementary changes to the representational geometry. Amplitude diversity increases the Euclidean distance between the responses to different stimuli, while bandwidth diversity creates a larger angular distance between them. The first utilizes the range of firing rates available to neurons, and the second exploits the high-dimensional nature of population responses. Population codes can be improved using these two different geometric changes, and amplitude and bandwidth diversity provide biological mechanisms for doing so. HighlightsO_LI- Perceptual performance is improved both by increased diversity of response amplitude and increased diversity of tuning bandwidth. C_LIO_LI- Both kinds of diversity improve visual discrimination and identification. C_LIO_LI- Amplitude diversity improves discrimination more, and bandwidth diversity improves identification more. C_LIO_LI- Representational geometry reveals the mechanisms of these effects. C_LI
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Near-optimal combination of disparity across a log-polar scaled visual field 96%
- Constrained inference in sparse coding reproduces contextual effects and predicts laminar neural dynamics 96%
- Tuned normalization in perceptual decision-making circuits can explain seemingly suboptimal confidence behavior 96%
Similar papers in this journal
- Predicting the partition of behavioral variability in speed perception with naturalistic stimuli 96%
- Robust associative learning is sufficient to explain structural and dynamical properties of local cortical circuits 95%
- Dendritic spikes expand the range of well-tolerated population noise structures 95%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.