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Nova · Professor Researcher · re-ranking top 20…
Joshua B Plotkin

Joshua B Plotkin

· PhdVerified

University of Pennsylvania · Computational Biology

Active 1979–2024

h-index72
Citations25.0k
Papers28076 last 5y
Funding
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Research topics

  • Computer Science
  • Artificial Intelligence
  • Psychology
  • Machine Learning
  • Sociology
  • Biology
  • Microeconomics
  • Linguistics
  • Ecology
  • Neuroscience
  • Developmental psychology
  • Medicine
  • Anthropology
  • Mathematics
  • Social psychology
  • Environmental resource management
  • Economics

Selected publications

  • Evolution of prosocial behaviours in multilayer populations

    Nature Human Behaviour · 2022 · 114 citations

    Senior authorCorresponding
    • Psychology
    • Social psychology
    • Developmental psychology
  • What we talk about when we talk about colors

    Proceedings of the National Academy of Sciences · 2021 · 39 citations

    Senior authorCorresponding
    • Computer Science
    • Artificial Intelligence
    • Sociology

    Names for colors vary widely across languages, but color categories are remarkably consistent. Shared mechanisms of color perception help explain consistent partitions of visible light into discrete color vocabularies. But the mappings from colors to words are not identical across languages, which may reflect communicative needs-how often speakers must refer to objects of different color. Here we quantify the communicative needs of colors in 130 different languages by developing an inference algorithm for this problem. We find that communicative needs are not uniform: Some regions of color space exhibit 30-fold greater demand for communication than other regions. The regions of greatest demand correlate with the colors of salient objects, including ripe fruits in primate diets. Our analysis also reveals a hidden diversity in the communicative needs of colors across different languages, which is partly explained by differences in geographic location and the local biogeography of linguistic communities. Accounting for language-specific, nonuniform communicative needs improves predictions for how a language maps colors to words, and how these mappings vary across languages. Our account closes an important gap in the compression theory of color naming, while opening directions to study cross-cultural variation in the need to communicate different colors and its impact on the cultural evolution of color categories.

  • A machine-vision approach for automated pain measurement at millisecond timescales

    eLife · 2020 · 82 citations

    • Computer Science
    • Artificial Intelligence
    • Machine Learning

    Objective and automatic measurement of pain in mice remains a barrier for discovery in neuroscience. Here, we capture paw kinematics during pain behavior in mice with high-speed videography and automated paw tracking with machine and deep learning approaches. Our statistical software platform, PAWS (Pain Assessment at Withdrawal Speeds), uses a univariate projection of paw position over time to automatically quantify seven behavioral features that are combined into a single, univariate pain score. Automated paw tracking combined with PAWS reveals a behaviorally divergent mouse strain that displays hypersensitivity to mechanical stimuli. To demonstrate the efficacy of PAWS for detecting spinally versus centrally mediated behavioral responses, we chemogenetically activated nociceptive neurons in the amygdala, which further separated the pain-related behavioral features and the resulting pain score. Taken together, this automated pain quantification approach will increase objectivity in collecting rigorous behavioral data, and it is compatible with other neural circuit dissection tools for determining the mouse pain state.

  • Evolutionary games with environmental feedbacks

    Nature Communications · 2020 · 301 citations

    • Computer Science
    • Ecology
    • Computer Science

    Strategic interactions arise in all domains of life. This form of competition often plays out in dynamically changing environments. The strategies employed in a population may alter the state of the environment, which may in turn feedback to change the incentive structure of strategic interactions. Feedbacks between strategies and the environment are common in social-ecological systems, evolutionary-ecological systems, and even psychological-economic systems. Here we develop a framework of 'eco-evolutionary game theory' that enables the study of strategic and environmental dynamics with feedbacks. We consider environments governed either by intrinsic growth, decay, or tipping points. We show how the joint dynamics of strategies and the environment depend on the incentives for individuals to lead or follow behavioral changes, and on the relative speed of environmental versus strategic change. Our analysis unites dynamical phenomena that occur in settings as diverse as human decision-making, plant nutrient acquisition, and resource harvesting. We discuss implications in fields ranging from ecology to economics.

Frequent coauthors

  • R Vyborny-Abstract Analysis

    University of Queensland

    49 shared
  • Walter D. Neumann

    University of North Carolina at Chapel Hill

    49 shared
  • C. J. Ash

    University College London

    49 shared
  • E Strzelecki-Analysis

    Monash University

    49 shared
  • S. D. VANSTONE

    Cardiff University

    49 shared
  • Robert Hofer

    Monash University

    49 shared
  • Anne Penfold

    49 shared
  • K Pearson

    Procter & Gamble (United States)

    49 shared
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