Research

Developing exploration behavior

Tracking genetically identical individuals from day 1 of their life to understand the development of intelligent behavior

Research Unit: 1

Project Number: 21

Example Behavior:
Individual Intelligence

Disciplines:
Behavioral Biology

 

Principal Investigators:
Max Wolf
Jens Krause

Postdoctoral Researchers:
Ulrike Scherer
David Bierbach

External Collaborators:
Sean Ehlman

 

Expected Project Duration
2020 - 2024

← Projects Overview

Developing exploration behavior

Tracking genetically identical individuals from day 1 of their life to understand the development of intelligent behavior

©SCIoI

A human or a robot in an escape room face a task that closely resembles that of a newborn biological organism: being initially completely ignorant about the specifics of the current environment, the task is to develop intelligent (i.e. adaptable, general, cost-effective and goal-directed) behavior. While evolution has made biological organisms extremely good in solving such tasks, very little is known about the behavioral mechanisms underlying this ability. The objectives of this project are (i) to use a high-resolution tracking system and a powerful biological model system – the naturally clonal fish Amazon molly (Poecilia formosa) – to track the exact behavioral-experiential trajectories of a large number of genetically identical individuals from day 1 of their life and (ii) to produce algorithmic models of exploration behavior that both predict real world behavioral-experiential trajectories of newborn individuals and perform well when implemented in agents in large-scale virtual experiments simulating a broad range of conditions and related tasks. Throughout, we will aim to generate improved synthetic artifacts (algorithms and computer simulations) and a deeper understanding of how newborn biological organisms develop intelligent behavior.

Snell-Rood, E., & Ehlman, S. (2023). Developing the genotype-to-phenotype relationship in evolutionary theory: a primer of developmental features. Evolution and Development, 1–17. https://doi.org/10.1111/ede.12434
Scherer, U., Ehlman, S. M., Bierbach, D., Krause, J., & Wolf, M. (2023). Reproductive individuality of clonal fish raised in near-identical environments and its link to early-life behavioral individuality. Nature Communications. https://doi.org/10.1038/s41467-023-43069-6
Scherer, U., Laskowki, K., Kressler, M., Ehlman, S. M., Wolf, M., & Bierbach, D. (2023). Perceived predation risk affects the development of among-individual behavioral variation in a naturally clonal freshwater fish. BioRxiv. https://doi.org/10.1101/2023.11.25.568653
McNamara, J., & Wolf, M. (2022). Social interaction can select for reduced ability. Proceedings of the Royal Society B: Biological Sciences. https://doi.org/10.1098/rspb.2022.1788
Makowicz, A. M., Bierbach, D., Richardson, C., & Hughes, K. A. (2022). Cascading indirect genetic effects in a clonal vertebrate. Proceedings of the Royal Society B: Biological Sciences, 289(1978). https://doi.org/10.1098/rspb.2022.0731
Lu, Y., Bierbach, D., Ormanns, J., Warren, W. C., Walter, R. B., & Schartl, M. (2021). Fixation of allelic gene expression landscapes and expression bias pattern shape the transcriptome of the clonal Amazon molly. Genome Research. https://doi.org/10.1101/gr.268870.120
Laskowski, K. L., Seebacher, F., Habedank, M., Meka, J., & Bierbach, D. (2021). Two Locomotor Traits Show Different Patterns of Developmental Plasticity Between Closely Related Clonal and Sexual Fish. Frontiers in Physiology, 12, 740604. https://doi.org/10.3389/fphys.2021.740604
Laskowski, K., Bierbach, D., Jolles, J., Doran, C., & Wolf, M. (2022). The emergence and development of behavioral individuality in clonal fish. Nature Communications. https://doi.org/10.1038/s41467-022-34113-y
Ehlman, S., Scherer, U., & Wolf, M. (2022). Developmental feedbacks and the emergence of individuality. Royal Society Open Science. https://doi.org/10.1098/rsos.221189
Ehlman, S., Scherer, U., Bierbach, D., Francisco, F., Laskowski, K., Krause, J., & Wolf, M. (2023). Leverging big data to uncover the eco-evolutionary factors shaping behavioural development. Proceedings of the Royal Society B. https://doi.org/10.1098/rspb.2022.2115

Research

An overview of our scientific work

See our Research Projects