Statistical physics-inspired approaches to modelling living systems

Understanding life through physics concepts and principles has been a persistent challenge along the years. Whether or not physics can be successfully extended to explaining phenomena involving living systems or human consciousness remains a fundamental question. In this respect, thermodynamics, statistical physics, and quantum mechanics seem to provide a useful, general framework.

Other questions I am very interested in include the origin of asymmetry in biological distributions, the possible existence of general statistical regularities, the basis of collective behaviours, and models of lifespan in humans. It has been neither fully understood how important processes at the root of evolution, such as, mutation, natural selection and inheritance are combined to give rise to the present layout of the species. Or the case of human decision at short times, is it expected to follow statistical rules?

I am very enthusiastic about establishing connections between the answers to the above questions and artificial intelligence algorithms.

Some recent publications

More on my Publons

Human Reaction Times: Linking Individual and Collective Behaviour Through Physics Modeling
Juan Carlos Castro-Palacio, Pedro Fernández-de-Córdoba, J. M. Isidro, Sarira Sahu, and Esperanza Navarro-Pardo, Symmetry 2021, 13(3), 451.
https://www.mdpi.com/2073-8994/13/3/451

Based on the recent evidence of correlations between the reaction time series to visual stimuli produced by different individuals within a group, we propose a Physics-inspired model to represent the reaction time data of a coetaneous group of individuals. In doing so, a Maxwell–Boltzmann-like distribution appeared, the same distribution as for the velocities of the molecules in an Ideal Gas model. We describe step by step the methodology we use to go from the individual reaction times to the distribution of the individuals response within the coetaneous group. In practical terms, by means of this model we also provide a simple entropy-based methodology
for the classification of the individuals within the collective they belong to with no need for an external reference which can be applicable in diverse areas of social sciences.

Machinery Failure Approach and Spectral Analysis to Study the Reaction Time Dynamics over Consecutive Visual Stimuli: An Entropy-Based Model
Miguel E. Iglesias-Martínez, Moisés Hernaiz-Guijarro, Juan Carlos Castro-Palacio, Pedro Fernández-de-Córdoba, J. M. Isidro and Esperanza Navarro-Pardo, Mathematics 2020, 8(11), 1979.
https://www.mdpi.com/2227-7390/8/11/1979

The reaction times of individuals over consecutive visual stimuli have been studied using an entropy-based model and a failure machinery approach. The used tools include the fast Fourier transform and a spectral entropy analysis. The results indicate that the reaction times produced by the independently responding individuals to visual stimuli appear to be correlated. The spectral analysis and the entropy of the spectrum yield that there are features of similarity in the response times of each participant and among them. Furthermore, the analysis of the mistakes made by the participants during the reaction time experiments concluded that they follow a behavior which is consistent with the MTBF (Mean Time Between Failures) model,
widely used in industry for the predictive diagnosis of electrical machines and equipment.