ArticleProceedings of the National Academy of Sciences of the United States of America2022
Developmental and evolutionary constraints on olfactory circuit selection.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed.
- Input density tunes Kenyon cell sensory responses in the Drosophila mushroom body.Current biology : CB · 2023Article
- Hacking brain development to test models of sensory coding.bioRxiv : the preprint server for biology · 2023Article
- Distinctive properties of biological neural networks and recent advances in bottom-up approaches toward a better biologically plausible neural network.Frontiers in computational neuroscience · 2023Review
- Biologically plausible local synaptic learning rules robustly implement deep supervised learning.Frontiers in neuroscience · 2023Article
- Article
- Trading mental effort for confidence in the metacognitive control of value-based decision-making.eLife · 2021Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
SignificanceIn this work, we explore the hypothesis that biological neural networks optimize their architecture, through evolution, for learning. We study early olfactory circuits of mammals and insects, which have relatively similar structure but a huge diversity in size. We approximate these circuits as three-layer networks and estimate, analytically, the scaling of the optimal hidden-layer size with input-layer size. We find that both longevity and information in the genome constrain the hidden-layer size, so a range of allometric scalings is possible. However, the experimentally observed allometric scalings in mammals and insects are consistent with biologically plausible values. This analysis should pave the way for a deeper understanding of both biological and artificial networks.
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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.