Bioinspired robotics and theoretical neuroscience

During the last decade, different experiments using inverse statistical mechanics have explored general properties of the neural and behavioural aspects of different biological organisms. Some of the results of these experiments show that many biological and cognitive systems do not operate deep into one or other regime of activity. Instead, they exploit critical surfaces poised at transitions in their parameter space. The pervasiveness of criticality in natural systems suggests that there may be general principles inducing this behaviour.

This research line aims to deepen in the understanding of critical phenomena and other statistical properties of embodied organisms, using statistical models and information theoretical tools. As well, we work in exploiting this knowledge for the design of bio-inspired agents exploiting the statistical mechanics of real-life organisms for displaying adaptive behaviour based on general mechanisms instead of ad hoc designs.

Publications

Aguilera, M & Di Paolo, EA (2019). Integrated information in the thermodynamic limit. Neural Networks, Volume 114, pp 136-146. doi:10.1016/j.neunet.2019.03.001

Aguilera, M & Bedia, MG (2018). Adaptation to criticality through organizational invariance in embodied agents. Scientific Reports  8, Article number: 7723 (2018). doi:10.1038/s41598-018-25925-4

Aguilera, M & Bedia, MG (2018). Exploring Criticality as a Generic Adaptive Mechanism. Frontiers in Neurorobotics 12: 55. doi:10.3389/fnbot.2018.00055

Aguilera, M, Alquézar, C & Bedia, MG (2018). Agency and Integrated Information in a Minimal Sensorimotor Model. The 2018 Conference on Artificial Life: A Hybrid of the European Conference on Artificial Life (ECAL) and the International Conference on the Synthesis and Simulation of Living Systems (ALIFE) 2018: 396-403

Aguilera, M & Bedia MG (2017). Criticality as It Could Be: organizational invariance as self-organized criticality in embodied agents. In Knibbe et al. (Eds.) Proceedings of the 14th European Conference on Artificial Life 2017.