10 found
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  1.  63
    Distributed Adaptations: Can a Species Be Adapted While No Single Individual Carries the Adaptation?Ehud Lamm & Oren Kolodny - 2022 - Frontiers in Ecology and Evolution 10.
    Species’ adaptation to their environments occurs via a range of mechanisms of adaptation. These include genetic adaptations as well as non-traditional inheritance mechanisms such as learned behaviors, niche construction, epigenetics, horizontal gene transfer, and alteration of the composition of a host’s associated microbiome. We propose to supplement these with another modality of eco-evolutionary dynamics: cases in which adaptation to the environment occurs via what may be called a “distributed adaptation,” in which the adaptation is not conferred via something carried by (...)
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  2. Learning a Generative Probabilistic Grammar of Experience: A Process‐Level Model of Language Acquisition.Oren Kolodny, Arnon Lotem & Shimon Edelman - 2014 - Cognitive Science 38 (4):227-267.
    We introduce a set of biologically and computationally motivated design choices for modeling the learning of language, or of other types of sequential, hierarchically structured experience and behavior, and describe an implemented system that conforms to these choices and is capable of unsupervised learning from raw natural-language corpora. Given a stream of linguistic input, our model incrementally learns a grammar that captures its statistical patterns, which can then be used to parse or generate new data. The grammar constructed in this (...)
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  3.  31
    Juvenile zebra finches learn the underlying structural regularities of their fathers’ song.Otília Menyhart, Oren Kolodny, Michael H. Goldstein, Timothy J. DeVoogd & Shimon Edelman - 2015 - Frontiers in Psychology 6.
  4.  18
    Learning a Generative Probabilistic Grammar of Experience: A Process‐Level Model of Language Acquisition.Oren Kolodny, Arnon Lotem & Shimon Edelman - 2015 - Cognitive Science 39 (2):227-267.
    We introduce a set of biologically and computationally motivated design choices for modeling the learning of language, or of other types of sequential, hierarchically structured experience and behavior, and describe an implemented system that conforms to these choices and is capable of unsupervised learning from raw natural‐language corpora. Given a stream of linguistic input, our model incrementally learns a grammar that captures its statistical patterns, which can then be used to parse or generate new data. The grammar constructed in this (...)
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  5.  14
    The bottleneck may be the solution, not the problem.Arnon Lotem, Oren Kolodny, Joseph Y. Halpern, Luca Onnis & Shimon Edelman - 2016 - Behavioral and Brain Sciences 39:e83.
    As a highly consequential biological trait, a memory “bottleneck” cannot escape selection pressures. It must therefore co-evolve with other cognitive mechanisms rather than act as an independent constraint. Recent theory and an implemented model of language acquisition suggest that a limit on working memory may evolve to help learning. Furthermore, it need not hamper the use of language for communication.
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  6.  69
    Human major transitions from the perspective of distributed adaptations.Ehud Lamm, Meir Finkel & Oren Kolodny - 2023 - Proceedings of the Royal Society of London B 378 (1872):11.
    Distributed adaptations are cases in which adaptation is dependent on the population as a whole: the adaptation is conferred by a structural or compositional aspect of the population; the adaptively relevant information cannot be reduced to information possessed by a single individual. Possible examples of human-distributed adaptations are song lines, traditions, trail systems, game drive lanes and systems of water collection and irrigation. Here we discuss the possible role of distributed adaptations in human cultural macro-evolution. Several kinds of human-distributed adaptations (...)
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  7.  9
    Are both necessity and opportunity the mothers of innovations?Gili Greenbaum, Laurel Fogarty, Heidi Colleran, Oded Berger-Tal, Oren Kolodny & Nicole Creanza - 2019 - Behavioral and Brain Sciences 42.
    Baumard's perspective asserts that “opportunity is the mother of innovation,” in contrast to the adage ascribing this role to necessity. Drawing on behavioral ecology and cognition, we propose that both extremes – affluence and scarcity – can drive innovation. We suggest that the types of innovations at these two extremes differ and that both rely on mechanisms operating on different time scales.
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  8.  14
    Differential application of cultural practices at the family and individual levels may alter heritability estimates.Oren Kolodny, Marcus W. Feldman, Arnon Lotem & Yoav Ram - 2022 - Behavioral and Brain Sciences 45:e167.
    Uchiyama et al. emphasize that culture evolves directionally and differentially as a function of selective pressures in different populations. Extending these principles to the level of families, lineages, and individuals exposes additional challenges to estimating heritability. Cultural traits expressed differentially as a function of the genetics whose influence they mask or unmask render inseparable the influences of culture and genetics.
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  9.  22
    Beyond uncertainty: A broader scope for “incentive hope” mechanisms and its implications.Omer Linkovski, Noam Weinbach, Shimon Edelman, Marcus W. Feldman, Arnon Lotem & Oren Kolodny - 2019 - Behavioral and Brain Sciences 42.
    We propose that food-related uncertainty is but one of multiple cues that predicts harsh conditions and may activate “incentive hope.” An evolutionarily adaptive response to these would have been to shift to a behavioral-metabolic phenotype geared toward facing hardship. In modernity, this phenotype may lead to pathologies such as obesity and hoarding. Our perspective suggests a novel therapeutic approach.
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  10.  29
    Reconciling genetic evolution and the associative learning account of mirror neurons through data-acquisition mechanisms.Arnon Lotem & Oren Kolodny - 2014 - Behavioral and Brain Sciences 37 (2):210-211.