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The evolution of associative learning: A factor in the Cambrian explosion
Abstract
The Cambrian explosion is probably the most spectacular diversification in evolutionary history, and understanding it has been a challenge for biologists since the time of Darwin. We propose that one of the key factors that drove this great diversification was associative learning. Although the evolutionary emergence of associative learning required only small modifications in already existing memory mechanisms and may have occurred in parallel in several groups, once this type of learning appeared on the evolutionary scene, it led to extreme diversifying selection at the ecological level: it enabled animals to exploit new niches, promoted new types of relations and arms races, and led to adaptive responses that became fixed through genetic accommodation processes. This learning-based diversification was accompanied by neurohormonal stress, which led to an ongoing destabilization and re-patterning of the epigenome, which, in turn, enabled further morphological, physiological, and behavioral diversification. Our hypothesis combines several previous ideas about the dynamics of the Cambrian explosion and provides a unifying framework that includes both ecological and genomic factors. We conclude by suggesting research directions that would clarify the timing and manner in which associative learning evolved, and the effects it had on the evolution of nervous systems, genomes, and animal morphology.
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“This is similar to the process of Unlimited Associative Learning (UAL) - the ability to group different sensory stimuli into a single compound percept that can be used in learning - proposed in work by Ginsburg and Jablonka as a transition marker for consciousness (Ginsburg and Jablonka 2007a,b, 2010, 2019; Bronfman et al. 2016)”
From The Measurement Problem of Consciousness (2020) · cites this paper as Ginsburg and Jablonka 2007a,b, 2010, 2019
In the citing paper
“This approach may facilitate the early development of multilayer processing structures, including interneurons as a crucial innovation, re-entrant closed loops and memory circuits capable of learning [274,275].”
From Fundamental constraints to the logic of living systems (2024) · cites this paper as [274]
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“environment, whether by animals and toddlers, or by any individual immersed in a new environment [38].”
BackgroundCrayfish Learning: Addiction and the Ganglionic Brain
van Staaden, M. J., & Huber, R. (2018) · Perspectives on Behavior Science · doi:10.1007/s40614-018-00181-z · Cited by 10
“…(Pandey, Mersha, & Dhillon, 2013), chemical modulation (Blenau & Thamm, 2011), receptor elements (Katz & Lillvis, 2014), as well as neural functioning (Kravitz, 2000; Egnor & Branson, 2016), and likely trace back at least to the early evolution of bilateral metazoans (Ginsburg & Jablonka, 2010).”
BackgroundMemories people no longer believe in can still affect them in helpful and harmful ways
Burnell, R., Nash, R. A., Umanath, S., & Garry, M. (2022) · Memory & Cognition · doi:10.3758/s13421-022-01328-9 · Cited by 11
“For example, humans’ ability to remember where to find food and water provides obvious survival advantages (Ginsburg & Jablonka, 2010).”
BackgroundA biphasic relational approach to the evolution of human consciousness
Hayes, S. C., & Hofmann, S. G. (2023) · International Journal of Clinical and Health Psychology · doi:10.1016/j.ijchp.2023.100380 · Cited by 10
Howe, M. L. (2015) · Wiley eBooks · doi:10.1002/9781118963418.childpsy206 · Cited by 9
Pereira, S., & van der Kooy, D. (2013) · Worm · doi:10.4161/worm.22725 · Cited by 8
Švorcová, J., & Kleisner, K. (2018) · Biosemiotics · doi:10.1007/s12304-018-9328-9 · Cited by 8
“…board may well inspire us to reconceptualise the evolution of instinctive and inborn behaviour in animals, because transgenerational epigenetics offers an entirely different view of how instincts and other automatized functions (habits) emerge (Ginsburg and Jablonka 2010; Robinson and Barron 2017).”
From Teleonomy to Mentally Driven Goal-Directed Behavior: Evolutionary Considerations
Jablonka, E., & Ginsburg, S. (2023) · The MIT Press eBooks · doi:10.7551/mitpress/14642.003.0010 · Cited by 8
Self-citationElimari, N., & Lafargue, G. (2023) · Consciousness and Cognition · doi:10.1016/j.concog.2023.103505 · Cited by 10
Coolidge, F. L. (2020) · doi:10.1093/oso/9780190940942.001.0001 · Cited by 11
Contextual Behavioral Science as a Distinct Form of Behavioral Research and Practice
Hayes, S. C. (2021) · Springer eBooks · doi:10.1007/978-3-030-77395-3_16 · Cited by 8
A neural network model for the evolution of learning in changing environments
Kozielska, M., & Weissing, F. J. (2024) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1011840 · Cited by 6
On the Problem of the Interpretation of Symbols and Symbolism in Archaeology
Coolidge, F. L., Overmann, K. A., & Wynn, T. A. (2023) · Oxford University Press eBooks · doi:10.1093/oxfordhb/9780192895950.013.1 · Cited by 6
Growing Confidence and Remaining Uncertainty About Animal ConsciousnessPreprint
Irwin, L. N. (2024) · Qeios · doi:10.32388/kovd1z · Cited by 5
Vertebrate decision making leads to the interdependence of behaviour and wellbeing
Giske, J., Budaev, S. V., Eliassen, S., Higginson, A. D., Jørgensen, C., & Mangel, M. (2025) · Animal Behaviour · doi:10.1016/j.anbehav.2025.123101 · Cited by 5
“In this way, vertebrates have used their ‘ prediction machine ’ (Bubic et al., 2010) for ‘ mental time-trav-elling ’ since the Cambrian explosion (Ginsburg & Jablonka, 2010).”
What could evolve in the evolution of memory?
Leadbeater, E., & Watrobska, C. (2025) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2024.0109 · Cited by 5
“It optimizes behaviour, shapes sophisticated phenotypic plasticity and is present in some form in nearly all tested animal species, including molluscs, arthropods, annelids and nematodes [1–3].”
Cognitive Twists: The Coevolution of Learning and Genes in Human Cognition
Tramacere, A., & Mafessoni, F. (2022) · Review of Philosophy and Psychology · doi:10.1007/s13164-022-00670-w · Cited by 6
Metadata
- Authors
- Ginsburg, S., & Jablonka, E.
- Affiliations
- Open University of Israel (IL)
- Tel Aviv University (IL)
- Corresponding author
- Jablonka, Eva
- Venue
- Journal of Theoretical Biology
- Publisher
- Elsevier BV
- Published
- 2010-09
- Volume
- 266
- Issue
- 1
- Pages
- 11-20
- ISSN
- 0022-5193 (ISSN-L)
- OpenAlex
- W2162225069
- Cited by
- 184
- References
- 101
- Citations by year
- 2026: 5 · 2025: 13 · 2024: 17 · 2023: 17 · 2022: 20 · 2021: 17 · 2020: 31 · 2019: 14 · 2018: 9 · 2017: 7 · 2016: 8 · 2015: 8 · 2014: 5 · 2013: 8 · 2012: 3
- FWCI
- 2.95
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Theoretical Biology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Agricultural and Biological Sciences › Animal Science and Zoology › Marine Invertebrate Physiology and Ecology
- Physical Sciences › Earth and Planetary Sciences › Paleontology › Evolution and Paleontology Studies
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Evolution and Genetic Dynamics
- Keywords
- Cambrian explosion, associative learning, evolutionary diversification, memory mechanisms, diversifying selection, arms race, genetic accommodation, epigenome, nervous system evolution, animal morphology, animal behavior
- MeSH terms
- Adaptation, Biological, Animals, Association Learning, Behavior, Animal, Biological Evolution, Memory, Nervous System Physiological Phenomena, Phylogeny, Selection, Genetic, Stress, Physiological, Stress, Psychological, Neurotransmitter Agents, Evolution, Molecular, Epigenesis, Genetic, Ecological and Environmental Phenomena
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