Simulation Models for Theoretical Life Science Research

Topic Description

Empirical life science research can require extensive resources. Adhering to well-established theories limits costly ‘dead-ends’. Under such constraints, are alternative theories possible? One approach to theoretical life science research is generating computational simulations to explore a large hypothesis space. This approach can facilitate going beyond well-established theories, by identifying hypotheses that show promise for pursuing empirically.

In this project, you will conduct theoretical research and develop computational simulations for theory assessment. The focus will be on a sub-area (e.g. predator-prey dynamics, habitat degradation, etc.) or an interface between sub-areas (e.g. stress disorders and niche construction). Rather than fitting existing data, the models you develop will be oriented towards future empirical research (beyond the scope of the project itself).

This project is open to variations depending on your research background and interests. Specific proposals may draw on multiple bodies of literature, including neurobiology, ecology, ethology, evolutionary theory, biological psychiatry, neuroeconomics, decision theory, ecological psychology, cognitive robotics, artificial life, and others.

Skills Required:

Software development skills

Knowledge of appropriate theoretical and empirical background literature

Knowledge of Bayesian statistics/maths useful

Experience with modelling and/or simulations useful

Background Reading:

Linson, A., Parr, T. & Friston, K., 2020. Active inference, stressors, and psychological trauma: A neuroethological model of (mal)adaptive explore-exploit dynamics in ecological context. Behavioural Brain Research, 380, p.112421. doi: 10.1016/j.bbr.2019.112421

Linson, A. & Friston, K., 2019. Reframing PTSD for computational psychiatry with the active inference framework. Cognitive Neuropsychiatry, 24(5), pp.347-368. doi: 10.1080/13546805.2019.1665994

Linson, A., Clark, A., Ramamoorthy, S. & Friston K., 2018. The active inference approach to ecological perception: General information dynamics for natural and artificial embodied cognition. Frontiers in Robotics and AI, 5, doi: 10.3389/frobt.2018.00021

Linson, A. & Calvo, P., 2020. Zoocentrism in the weeds? Cultivating plant models for cognitive yield. Biol Philos 35, 49. https://doi.org/10.1007/s10539-020-09766-y

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