ArticleEvolution; international journal of organic evolution2014
The evolution of phenotypic correlations and "developmental memory".
Article in Evolution; international journal of organic evolution, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.
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Who cites it
47 citing papers in PubMed.
- Heuristically Adaptive Diffusion-Model Evolutionary Strategy.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- The variability of evolvability: Properties of dynamic fitness landscapes determine how phenotypic variability evolves.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Gene expression evolution is predicted by stronger indirect selection at more pleiotropic genes.Evolution letters · 2025Article
- Histopathology of Diabetic Nephropathy: Beyond Glomerular Basement Membrane Thickening.Cureus · 2025Review
- Implications From the Analogous Relationship Between Evolutionary and Learning Processes.BioEssays : news and reviews in molecular, cellular and developmental biology · 2025Review
- Natural Induction: Spontaneous Adaptive Organisation without Natural Selection.Entropy (Basel, Switzerland) · 2024Article
- On the evolutionary origin of discrete phenotypic plasticity.G3 (Bethesda, Md.) · 2024Article
- Evolutionary Implications of Self-Assembling Cybernetic Materials with Collective Problem-Solving Intelligence at Multiple Scales.Entropy (Basel, Switzerland) · 2024Article
- Vertically inherited microbiota and environment modifying behaviours conceal genetic variation in dung beetle life history.Proceedings. Biological sciences · 2024Article
- A neural network-based model framework for cell-fate decisions and development.Communications biology · 2024Article
- Evolution of biological cooperation: an algorithmic approach.Scientific reports · 2024Article
- Article
- Agency, Goal-Directed Behavior, and Part-Whole Relationships in Biological Systems.Biological theory · 2024Article
- Plasticity-led evolution as an intrinsic property of developmental gene regulatory networks.Scientific reports · 2023Article
- Rules of teeth development align microevolution with macroevolution in extant and extinct primates.Nature ecology & evolution · 2023Article
- Developmental bias predicts 60 million years of wing shape evolution.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Darwin's agential materials: evolutionary implications of multiscale competency in developmental biology.Cellular and molecular life sciences : CMLS · 2023Review
- Learning in Transcriptional Network Models: Computational Discovery of Pathway-Level Memory and Effective Interventions.International journal of molecular sciences · 2022Article
- Computational modelling of plasticity-led evolution.Biophysical reviews · 2022Review
- Genetic influences on dentognathic morphology in the Jirel population of Nepal.Anatomical record (Hoboken, N.J. : 2007) · 2022Article
Corrections and comments
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5 authors.
Funding
Abstract
Development introduces structured correlations among traits that may constrain or bias the distribution of phenotypes produced. Moreover, when suitable heritable variation exists, natural selection may alter such constraints and correlations, affecting the phenotypic variation available to subsequent selection. However, exactly how the distribution of phenotypes produced by complex developmental systems can be shaped by past selective environments is poorly understood. Here we investigate the evolution of a network of recurrent nonlinear ontogenetic interactions, such as a gene regulation network, in various selective scenarios. We find that evolved networks of this type can exhibit several phenomena that are familiar in cognitive learning systems. These include formation of a distributed associative memory that can "store" and "recall" multiple phenotypes that have been selected in the past, recreate complete adult phenotypic patterns accurately from partial or corrupted embryonic phenotypes, and "generalize" (by exploiting evolved developmental modules) to produce new combinations of phenotypic features. We show that these surprising behaviors follow from an equivalence between the action of natural selection on phenotypic correlations and associative learning, well-understood in the context of neural networks. This helps to explain how development facilitates the evolution of high-fitness phenotypes and how this ability changes over evolutionary time.
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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.