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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Unlimited Associative Learning (UAL) is proposed by Ginsburg and Jablonka as a transition marker for consciousness.
“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
Employing polarized, threshold-like elements in line with McCulloch-Pitts logic may facilitate the early development of multilayer processing structures, including interneurons, re-entrant closed loops and memory circuits capable of learning.
“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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BackgroundWhy learn? The adaptive value of associative learning in wild populations
Morand‐Ferron, J. (2017) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2017.03.008 · Cited by 89 · see citing works
Gonçalves, A., & Biro, D. (2018) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2017.0263 · Cited by 88 · see citing works
Cooperation came first: Evolution and human cognition
Hayes, S. C., & Sanford, B. T. (2013) · Journal of the Experimental Analysis of Behavior · doi:10.1002/jeab.64 · Cited by 85 · see citing works
“Indeed, major evolutionary biologists now argue that learning was itself responsible for the “Cambrian explosion”—the increase in speciation and phenotypic diversity that occurred 520–540 million years ago (Ginsburg & Jablonka, 2010).”
BackgroundTaking the Operant Paradigm into the Field: Associative Learning in Wild Great Tits
Morand‐Ferron, J., Hamblin, S., Cole, E. F., Aplin, L. M., & Quinn, J. L. (2015) · PLoS ONE · doi:10.1371/journal.pone.0133821 · Cited by 79 · see citing works
“Associative learning—a behavioural modification following reinforcement, based on associations between stimuli, or between stimuli and responses–has been found in all bilateral animals tested to date [15,16].”
InfluentialThe Measurement Problem of Consciousness
Browning, H., Veit, W., & University of Arkansas Press (2020) · Philosophical Topics · doi:10.5840/philtopics20204815 · Cited by 78 · see citing works
Keijzer, F. (2015) · Biology & Philosophy · doi:10.1007/s10539-015-9483-1 · Cited by 78 · see citing works
“A single-cell sensor can signal the presence or intensity of an environmental feature—such as light—but sensor arrays enable organisms to become sensitive to patterns across extended surface arrays (Gibson 1966; Braitenberg 1984).”
BackgroundThe Cambrian explosion and the origins of embodied cognition.
Trestman, M. (2013) · Biological Theory · doi:10.1007/s13752-013-0102-6 · Cited by 70 · see citing works
“2009; Oliver and Greene 2009), as well as by destabilizing the genome through changes in epigenetic marks, ‘‘which can lead to altered patterns of mitotic and meiotic pairing, to chromosomal re-patterning, to mutation-prone repair, as well as triggering transposition’’ (Ginsburg and Jablonka 2010).”
BackgroundInfluentialLearning and the Evolution of Conscious Agents
Jablonka, E., & Ginsburg, S. (2022) · Biosemiotics · doi:10.1007/s12304-022-09501-y · Cited by 61 · see citing works
“We suggested that the evolution of learning – especially of UAL which appeared during this era – was one of the factors that drove the great Cambrian explosion (Ginsburg & Jablonka, 2010).”
BackgroundSelf-citationPhylogenetic origins of biological cognition: convergent patterns in the early evolution of learning
van Duijn, M. (2017) · Interface Focus · doi:10.1098/rsfs.2016.0158 · Cited by 60 · see citing works
Associative learning in the box jellyfish Tripedalia cystophora
Bielecki, J., Nielsen, S. K. D., Nachman, G., & Garm, A. L. (2023) · Current Biology · doi:10.1016/j.cub.2023.08.056 · Cited by 52 · see citing works
The evolutionary origins of the Global Neuronal Workspace in vertebrates
Zacks, O., & Jablonka, E. (2023) · Neuroscience of Consciousness · doi:10.1093/nc/niad020 · Cited by 47 · see citing works
“According to this proposal, consciousness first emerged in the vertebrate lineage during the Cambrian (Ginsburg and Jablonka 2007b, 2010, 2019; Feinberg and Mallatt 2013, 2016), and selection for increasingly open-ended learning was the driving force leading to the evolution of the GNW/UAL architecture.”
BackgroundSelf-citationSynthetic biology routes to bio-artificial intelligence
Nesbeth, D., Zaikin, A. A., Saka, Y., Romano, M. C., Giuraniuc, C. V., Игоревич, К. О., & Laptyeva, T. V. (2016) · Essays in Biochemistry · doi:10.1042/ebc20160014 · Cited by 45 · see citing works
“Such classical associative learning is advantageous because it enables an organism to anticipate and adapt to environmental changes quickly and has been observed in all animals with bilateral symmetry so far studied [20].”
BackgroundWhat kind of memory has evolution wrought?
Otgaar, H., & Howe, M. L. (2013) · Memory · doi:10.1080/09658211.2013.800355 · Cited by 43 · see citing works
“…traces, provided organisms that possessed it with at least three survival-related advantages that the earlier form of memory did not provide (Ginsburg & Jablonka, 2010a, p. 114; emphases in original): First, the binding of stimuli, which at the previous stage of evolution (before…”
BackgroundInfluentialDimensions of integration in interdisciplinary explanations of the origin of evolutionary novelty
Love, A. C., & Lugar, G. L. (2013) · Studies in History and Philosophy of Science Part C Studies in History and Philosophy of Biological and Biomedical Sciences · doi:10.1016/j.shpsc.2013.09.008 · Cited by 43 · see citing works
“Although these types of analyses do appear, including intriguing appeals to associative learning and embodied cognition (Ginsburg & Jablonka, 2010; Trestman, 2013), we are not attempting fossil record; this mode of inference appears to be one of the few means available for & Ostrovsky, 2012, p.…”
BackgroundDixon, M. R., Hayes, S. C., Stanley, C., Law, S., & al-Nasser, T. (2020) · The Psychological Record · doi:10.1007/s40732-020-00436-9 · Cited by 42 · see citing works
“…stimuli and virtually all life forms do so; with the advent of operant and classical conditioning during the Cambrian period over 540 million years ago (Ginsburg & Jablonka, 2010) that ability extended usefully to stimuli that merely predicted aversive events within the lifetime of the individual.”
BackgroundBiochemically plausible models of habituation for single-cell learning
Eckert, L., Vidal-Saez, M. S., Zhao, Z., García‐Ojalvo, J., Martinez-Corral, R., & Gunawardena, J. (2024) · Current Biology · doi:10.1016/j.cub.2024.10.041 · Cited by 41 · see citing works
“60 Learning in single cells that are components of multi-cellular organisms is not obviously supported by this evolutionary rationale.”
Hayes, S. C., Hofmann, S. G., & Stanton, C. E. (2020) · Journal of Contextual Behavioral Science · doi:10.1016/j.jcbs.2020.08.009 · Cited by 39 · see citing works
Synthetic associative learning in engineered multicellular consortia
Macía, J., Vidiella, B., & Solé, R. V. (2017) · Journal of The Royal Society Interface · doi:10.1098/rsif.2017.0158 · Cited by 40 · see citing works
“d[A2] dt = γA2LasI − δA[A2] +DA([Ae]− [A2]) (18) d[A1] dt = DA([Ae]− [A1])− δA[A1] (19) d[Ae] dt = DA([A1] + [A2]− 2[Ae])− δA[Ae] (20)”
Clinical psychology is an applied evolutionary science
Hayes, S. C., Hofmann, S. G., & Wilson, D. S. (2020) · Clinical Psychology Review · doi:10.1016/j.cpr.2020.101892 · Cited by 45 · see citing works
Functional Contextualism and Contextual Behavioral Science
Biglan, A., & Hayes, S. C. (2015) · Wiley eBooks · doi:10.1002/9781118489857.ch4 · Cited by 42 · see citing works
Transitions in cognitive evolution
Barron, A. B., Halina, M., & Klein, C. (2023) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2023.0671 · Cited by 39 · see citing works
Who needs a brain? Slime moulds, behavioural ecology and minimal cognition
Smith‐Ferguson, J., & Beekman, M. (2019) · Adaptive Behavior · doi:10.1177/1059712319826537 · Cited by 39 · see citing works
“The hierarchy of learning continues up from operant conditioning, but we will set our bar at associative learning, as this is often cited as the most fundamental instance of ‘true’ learning (Ginsburg & Jablonka, 2010; Skinner, 1981).”
BackgroundLearning in Cnidaria: A systematic review
Cheng, K. (2021) · Learning & Behavior · doi:10.3758/s13420-020-00452-3 · Cited by 39 · see citing works
Events in Early Nervous System Evolution
Paulin, M. G., & Cahill‐Lane, J. (2021) · Topics in Cognitive Science · doi:10.1111/tops.12461 · Cited by 35 · see citing works
Fundamental constraints to the logic of living systems
Solé, R., Kempes, C. P., Corominas-Murtra, B., De Domenico, M., Kolchinsky, A., Lachmann, M., Libby, E., Saavedra, S., Smith, E., & Wolpert, D. (2024) · Interface Focus · doi:10.1098/rsfs.2024.0010 · Cited by 34 · see citing works
“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].”
BackgroundEvidence of anticipatory immune and hormonal responses to predation risk in an echinoderm
Hamel, J., Jobson, S. M., Caulier, G., & Mercier, A. (2021) · Scientific Reports · doi:10.1038/s41598-021-89805-0 · Cited by 34 · see citing works
The teleological transitions in evolution: A Gántian view
Ginsburg, S., & Jablonka, E. (2015) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2015.04.007 · Cited by 32 · see citing works
Self-citationWhy is the Rescorla-Wagner model so influential?
Soto, F. A., Vogel, E. H., Uribe-Bahamonde, Y. E., & Perez, O. D. (2023) · Neurobiology of Learning and Memory · doi:10.1016/j.nlm.2023.107794 · Cited by 31 · see citing works
Physiology restores purpose to evolutionary biology
Noble, R., & Noble, D. (2022) · Biological Journal of the Linnean Society · doi:10.1093/biolinnean/blac049 · Cited by 31 · see citing works
The representation of animal behaviour in the fossil record
Hsieh, S., & Plotnick, R. E. (2020) · Animal Behaviour · doi:10.1016/j.anbehav.2020.09.010 · Cited by 28 · see citing works
The Evolutionary Origin of Associative Learning
Pontes, A. C., Mobley, R. B., Ofria, C., Adami, C., & Dyer, F. C. (2019) · The American Naturalist · doi:10.1086/706252 · Cited by 28 · see citing works
Past, present, and future mass extinctions
Elewa, A. M. T., & Abdelhady, A. A. (2019) · Journal of African Earth Sciences · doi:10.1016/j.jafrearsci.2019.103678 · Cited by 28 · see citing works
Stanton, L. A., Bridge, E. S., Huizinga, J., & Benson‐Amram, S. (2022) · Journal of Experimental Biology · doi:10.1242/jeb.243726 · Cited by 27 · see citing works
Carrying the baton: Evolution science and a contextual behavioral analysis of language and cognition
Hayes, S. C., Sanford, B. T., & Chin, F. T. (2017) · Journal of Contextual Behavioral Science · doi:10.1016/j.jcbs.2017.01.002 · Cited by 27 · see citing works
The evolution of continuous learning of the structure of the environment
Kolodny, O., Edelman, S., & Lotem, A. (2014) · Journal of The Royal Society Interface · doi:10.1098/rsif.2013.1091 · Cited by 26 · see citing works
Krause, M. A. (2015) · Animal Cognition · doi:10.1007/s10071-015-0854-4 · Cited by 26 · see citing works
“Ginsburg and Jablonka (2010) explore this common observation by integrating comparative methods, the fossil record, and geological findings to speculate on the origins of associative learning.”
BackgroundAwareness and integrated information theory identify plant meristems as sites of conscious activity
TREWAVAS, A. J. (2021) · PROTOPLASMA · doi:10.1007/s00709-021-01633-1 · Cited by 25 · see citing works
“For example, Ginsburg and Jablonka (2010) state that during evolution, behaviour becomes more complex, and they quote the evolution of open-ended associative learning as an example (Bronfman et al. 2016).”
BackgroundWhere Actions Meet Outcomes: Medial Prefrontal Cortex, Central Thalamus, and the Basal Ganglia
Mair, R. G., Francoeur, M. J., Krell, E. M., & Gibson, B. M. (2022) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2022.928610 · Cited by 32 · see citing works
“The elaboration of these circuits during vertebrate evolution has been linked to the development of neural systems that underlie more abstract processes of human cognition (Ginsburg and Jablonka, 2010, 2021; Koechlin, 2014; Cisek, 2019).”
BackgroundLiefting, M., Hoedjes, K. M., Lann, C. L., Smid, H. M., & Ellers, J. (2018) · Evolution · doi:10.1111/evo.13498 · Cited by 23 · see citing works
Components of change and the evolution of learning in theory and experiment
Dunlap, A. S., Austin, M. W., & Dexheimer, A. F. (2018) · Animal Behaviour · doi:10.1016/j.anbehav.2018.05.024 · Cited by 22 · see citing works
Modern psychotherapy as a multidimensional multilevel evolutionary process
Hayes, S. C., & Sanford, B. T. (2015) · Current Opinion in Psychology · doi:10.1016/j.copsyc.2015.01.009 · Cited by 23 · see citing works
“Because of such processes, contingency learning has been proposed as the single most important factor contributing to the ‘Cambrian Explosion’ — the proliferation of species seen 540 Mya — when contingency learning first appeared [14].”
BackgroundThe major evolutionary transitions and codes of life
Kun, Á. (2021) · Biosystems · doi:10.1016/j.biosystems.2021.104548 · Cited by 20 · see citing works
Neuroecology beyond the brain: learning in Echinodermata
Freas, C. A., & Cheng, K. (2021) · Learning & Behavior · doi:10.3758/s13420-021-00492-3 · Cited by 20 · see citing works
“In Cnidaria, only a single well-structured study on sea anemones provides solid evidence for classical conditioning (Haralson et al., 1975), which leaves doubts about the robustness of the evidence (Bronfman et al., 2016; Cheng, 2021; Ginsburg & Jablonka, 2010).”
BackgroundResponse to comment on 'Lack of evidence for associative learning in pea plants'
Markel, K. (2020) · eLife · doi:10.7554/elife.61689 · Cited by 19 · see citing works
“, 2016), in addition to questions regarding the molecular mechanisms and evolutionary history of learning (Ginsburg and Jablonka, 2010).”
BackgroundProvenance of life: Chemical autonomous agents surviving through associative learning
Bartlett, S., & Louapre, D. (2022) · Physical review. E · doi:10.1103/physreve.106.034401 · Cited by 18 · see citing works
A double error dynamic asymptote model of associative learning.
Kokkola, N. H., Mondragón, E., & Alonso, E. (2019) · Psychological Review · doi:10.1037/rev0000147 · Cited by 17 · see citing works
Bronfman, Z. Z., Ginsburg, S., & Jablonka, E. (2021) · Journal of Artificial Intelligence and Consciousness · doi:10.1142/s2705078521500168 · Cited by 12 · see citing works
Self-citationThe Co‐Emergence of the Self and Autobiographical Memory: An Adaptive View of Early Memory
Howe, M. L. (2013) · doi:10.1002/9781118597705.ch23 · Cited by 16 · see citing works
Hsieh, S., Plotnick, R. E., & Bush, A. M. (2022) · Paleobiology · doi:10.1017/pab.2021.46 · Cited by 18 · see citing works
The PROUST hypothesis: the embodiment of olfactory cognition
Jacobs, L. F. (2022) · Animal Cognition · doi:10.1007/s10071-022-01734-1 · Cited by 15 · see citing works
“Spatial orientation to odors may arguably have been the class of associative learning that was the impetus for the radiation of animal phyla in the Cambrian (Ginsburg and Jablonka 2010; Jacobs 2012).”
BackgroundHow experimental neuroscientists can fix the hard problem of consciousness
Klein, C., & Barron, A. B. (2020) · Neuroscience of Consciousness · doi:10.1093/nc/niaa009 · Cited by 15 · see citing works
“The capacities necessary for conscious experience might be things like the functions supporting conscious experience such as selective attention, integrative and interactive processing of exteroceptive and interoceptive information, a unified spatial and temporal framework for sensory information, or unlimited associa…”
BackgroundGodfrey‐Smith, P. (2017) · Biology & Philosophy · doi:10.1007/s10539-017-9569-z · Cited by 14 · see citing works
“Ginsburg and Jablonka single out associative learning as especially important (Parker 2003; Ginsburg and Jablonka 2010).”
BackgroundSurvival circuits and therapy: from automaticity to the conscious experience of fear and anxiety
Hayes, S. C., & Hofmann, S. G. (2018) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2018.02.006 · Cited by 13 · see citing works
Open problems in synthetic multicellularity
Solé, R. V., Pueyo, N. C., Pla, J., García‐Ojalvo, J., Montserrat, N., & Levin, M. G. (2024) · npj Systems Biology and Applications · doi:10.1038/s41540-024-00477-8 · Cited by 13 · see citing works
Bodily Complexity: Integrated Multicellular Organizations for Contraction-Based Motility
Arnellos, A., & Keijzer, F. (2019) · Frontiers in Physiology · doi:10.3389/fphys.2019.01268 · Cited by 13 · see citing works
Behavioural adjustments enable the colonization of subterranean environments
Lunghi, E., Mammola, S., Martínez, A., & Hesselberg, T. (2023) · Zoological Journal of the Linnean Society · doi:10.1093/zoolinnean/zlad133 · Cited by 12 · see citing works
Defending the Pathological Complexity Thesis
Veit, W. (2023) · Biological Theory · doi:10.1007/s13752-023-00430-8 · Cited by 11 · see citing works
Premises for digital twins reporting on Atlantic salmon wellbeing
Giske, J., Dumitru, M. L., Enberg, K., Folkedal, O., Handeland, S. O., Higginson, A. D., Opdal, A. F., Rønnestad, I., Salvanes, A. G. V., Vollset, K. W., et al. (2025) · Behavioural Processes · doi:10.1016/j.beproc.2025.105163 · Cited by 11 · see citing works
Figdor, C. (2022) · Biology & Philosophy · doi:10.1007/s10539-022-09880-z · Cited by 11 · see citing works
“CSS lies behind the realization in behavioral ecology that distinct species are not nec- level does not entail homology at others, and co-evolution often occurs with temporal lags between appearances of novel characters at distinct levels (Erwin 2021; Corballis 2000; Ginsburg and Jablonka 2010).”
BackgroundAre ants botanists? Ant associative learning of plant chemicals mediates foraging for carbohydrates
Nelson, A. S., Zapata, G. D., Sentner, K. T., & Mooney, K. A. (2019) · Ecological Entomology · doi:10.1111/een.12794 · Cited by 11 · see citing works
“In turn, associative learning is considered to result in the evolution of new traits (e.g. anti-predator defences in prey) (Ginsburg & Jablonka, 2010) and to structure populations and communities of associated species (Ishii & Shimada, 2010).”
BackgroundHow Purposive Agency Became Banned from Evolutionary Biology
Noble, D., & Noble, R. (2023) · The MIT Press eBooks · doi:10.7551/mitpress/14642.003.0015 · Cited by 11 · see citing works
Assessment of operant learning and memory in mice born through ICSI
Lewon, M., Wang, Y., Peters, C. M., Peterson, M., Zheng, H., Wang, Z., Hayes, L. J., & Yan, W. (2020) · Human Reproduction · doi:10.1093/humrep/deaa167 · Cited by 10 · see citing works
An Evolutionary Perspective on Embodiment
Cisek, P. (2021) · Springer eBooks · doi:10.1007/978-3-030-78471-3_24 · Cited by 8 · see citing works
The evolution of working memory
Coolidge, F. L., & Wynn, T. (2020) · L’Année psychologique · doi:10.3917/anpsy1.202.0103 · Cited by 10 · see citing works
Unde venisti PGRMC? Grand-Scale Biology from Early Eukaryotes and Eumetazoan Animal Origins
Cahill, M. A. (2022) · Frontiers in Bioscience-Landmark · doi:10.31083/j.fbl2711317 · Cited by 9 · see citing works
Jaillard, B., Deleporte, P., Loreau, M., & Violle, C. (2018) · PLoS ONE · doi:10.1371/journal.pone.0201135 · Cited by 9 · see citing works
“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 9 · see citing works
“…(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 9 · see citing works
“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 9 · see citing works
Howe, M. L. (2015) · Wiley eBooks · doi:10.1002/9781118963418.childpsy206 · Cited by 9 · see citing works
Pereira, S., & van der Kooy, D. (2013) · Worm · doi:10.4161/worm.22725 · Cited by 8 · see citing works
Švorcová, J., & Kleisner, K. (2018) · Biosemiotics · doi:10.1007/s12304-018-9328-9 · Cited by 8 · see citing works
“…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 · see citing works
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Coolidge, F. L. (2020) · doi:10.1093/oso/9780190940942.001.0001 · Cited by 10 · see citing works
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 7 · see citing works
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 · see citing works
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 · see citing works
Growing Confidence and Remaining Uncertainty About Animal ConsciousnessPreprint
Irwin, L. N. (2024) · Qeios · doi:10.32388/kovd1z · Cited by 6 · see citing works
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 · see citing works
“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 · see citing works
“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 5 · see citing works
- 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
- Physical Sciences › Earth and Planetary Sciences › Paleontology › 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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