ArticlePNAS nexus2026
Preserving predictive information under biologically plausible compression.
Article in PNAS nexus, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Convergent motifs of early olfactory processing are recapitulated by layer-wise efficient coding.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Convergent motifs of early olfactory processing are recapitulated by layer-wise efficient coding.bioRxiv : the preprint server for biology · 2025Article
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Authors and funding
4 authors.
Funding
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Abstract
Retinal ganglion cells show high convergence onto their downstream projections, which poses a problem for information transfer: how can information be preserved through a synaptic layer that has significantly more inputs than outputs? Lossy compression suggests many efficient, yet computation-agnostic, methods for reading out input stimuli or activity patterns. Focusing on prediction as a ubiquitous computation in the brain, we compare compressions that explicitly retain predictive information to common neural compression frameworks that do not. We find evidence that compressing retinal inputs to perform optimal predictive computations allows putative downstream neurons to predict the future near-optimally across natural scenes. Other sensory systems also exhibit compression in their processing hierarchies, and we hope that our framework will be useful in cases where it is not yet known how information about a specific computation is maintained under compression.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.