Hedonic foraging: A computational framework for understanding behavior
As a side project, I cultivate a strong interest in understanding the computational and neurobiological mechanisms of behavior (e.g., Penacchio & Clemente, 2024). Integrating hedonic evaluation—the process of assigning hedonic value (Berridge & Kringelbach, 2008, 2015)—and active inference—the theoretical framework that posits that behavior is governed by the imperative of minimizing variational free energy, a proxy for the divergence between actual and preferred states (Parr et al., 2022; Pezzulo et al., 2024) (Friston, 2010; Parr et al., 2022)—, we propose hedonic foraging as the mechanism through which reward maximization drives behavior in organisms with a reward system, with hedonic evaluation monitoring and motivating free energy minimization. This project has been awarded a Johanna Quandt Young Academy Fellowship within the Academy topic Complexity.
References
Bengtsson, S. L., Nagy, Z., Skare, S., Forsman, L., Forssberg, H., & Ullén, F. (2005). Extensive piano practicing has regionally specific effects on white matter development. Nature Neuroscience, 8(9), 1148–1150.
https://doi.org/10.1038/nn1516
Berridge, K. C., & Kringelbach, M. L. (2008). Affective neuroscience of pleasure: Reward in humans and animals. Psychopharmacology, 199, 457–480. https://doi.org/10.1007/s00213-008-1099-6
Berridge, K. C., & Kringelbach, M. L. (2015). Pleasure systems in the brain. Neuron, 86(3), 646–664.
https://doi.org/10.1016/j.neuron.2015.02.018
Friston, K. (2010). The free-energy principle: A unified brain theory?. Nature Reviews Neuroscience, 11(2), 127–138.
https://doi.org/10.1038/nrn2787
Herholz, S. C., & Zatorre, R. J. (2012). Musical training as a framework for brain plasticity: behavior, function, and structure. Neuron, 76(3), 486–502.
https://doi.org/10.1016/j.neuron.2012.10.011
Hille, M., Kühn, S., Kempermann, G., Bonhoeffer, T., & Lindenberger, U. (2024). From animal models to human individuality: Integrative approaches to the study of brain plasticity. Neuron, 112(21), 3522–3541.
https://doi.org/10.1016/j.neuron.2024.10.006
Kolb, B., & Whishaw, I. Q. (1998). Brain plasticity and behavior. Annual Review of Psychology, 49(1), 43–64.
https://doi.org/10.1146/annurev.psych.49.1.43
Lövdén, M., Garzón, B., & Lindenberger, U. (2020). Human skill learning: Expansion, exploration, selection, and refinement. Current Opinion in Behavioral Sciences, 36, 163–168.
https://doi.org/10.1016/j.cobeha.2020.11.002
Masse, N. Y., Yang, G. R., Song, H. F., Wang, X. J., & Freedman, D. J. (2019). Circuit mechanisms for the maintenance and manipulation of information in working memory. Nature Neuroscience, 22(7), 1159–1167.
https://doi.org/10.1038/s41593-019-0414-3
Parr, T., Pezzulo, G., & Friston, K. J. (2022). Active Inference: The Free Energy Principle in Mind, Brain, and Behavior. MIT Press.
Penacchio, O., & Clemente, A. (2024). Meta-learning in active inference. Behavioral and Brain Sciences, 47, e159.
https://doi.org/10.1017/S0140525X24000074
Pinho, A. L., de Manzano, Ö., Fransson, P., Eriksson, H., & Ullén, F. (2014). Connecting to create: Expertise in musical improvisation is associated with increased functional connectivity between premotor and prefrontal areas. Journal of Neuroscience, 34(18), 6156–6163.
https://doi.org/10.1523/JNEUROSCI.4769-13.2014
Zatorre, R. J., Chen, J. L., & Penhune, V. B. (2007). When the brain plays music: auditory–motor interactions in music perception and production. Nature Reviews Neuroscience, 8(7), 547–558.
https://doi.org/10.1038/nrn2152
Researchers
Ph.D. Olivier Penacchio
University of St Andrews, Autonomous University of Barcelona
