Off-manifold coding in visual cortex revealed by sleep
de Oliveira, E. F.; Kim, S.; Qiu, T. S.; Peyrache, A.; Batista-Brito, R.; Sjulson, L.
Show abstract
Low-dimensional neural manifolds are controversial in part because it is unclear how to reconcile them with high-dimensional representations observed in areas such as primary visual cortex (V1). We addressed this by recording neuronal activity in V1 during slow-wave sleep, enabling us to identify internally-generated low-dimensional manifold structure and evaluate its role during visual processing. We found that movements and visual stimuli were both encoded in the "on-manifold" subspace preserved during sleep. However, only stimuli were encoded in the "off-manifold" subspace, which contains activity patterns that are less likely than chance to occur spontaneously during sleep. This off-manifold activity comprises sparse firing in neurons with the strongest low-dimensional modulation by movement, which paradoxically prevents movement-evoked activity from interfering with stimulus representations. These results reveal an unexpected link between low-dimensional dynamics and sparse coding, which together create a protected off-manifold coding space keeping high-dimensional representations separable from movement-evoked activity.
Matching journals
The top 4 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- A precise and adaptive neural mechanism for predictive temporal processing in the frontal cortex 97%
- Simultaneous, cortex-wide and cellular-resolution neuronal population dynamics reveal an unbounded scaling of dimensionality with neuron number 97%
- Excitation creates a distributed pattern of cortical suppression due to varied recurrent input 97%
"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.