The Darwinian concept of natural selection was conceived within a set of Newtonian background assumptions about systems dynamics. Mendelian genetics at first did not sit well with the gradualist assumptions of the Darwinian theory. Eventually, however, Mendelism and Darwinism were fused by reformulating natural selection in statistical terms. This reflected a shift to a more probabilistic set of background assumptions based upon Boltzmannian systems dynamics. Recent developments in molecular genetics and paleontology have put pressure on Darwinism once again. Current work (...) on self-organizing systems may provide a stimulus not only for increased problem solving within the Darwinian tradition, especially with respect to origins of life, developmental genetics, phylogenetic pattern, and energy-flow ecology, but for deeper understanding of the very phenomenon of natural selection itself. Since self-organizational phenomena depend deeply on stochastic processes, self-organizational systems dynamics advance the probability revolution. In our view, natural selection is an emergent phenomenon of physical and chemical selection. These developments suggest that natural selection may be grounded in physical law more deeply than is allowed by advocates of the autonomy of biology, while still making it possible to deny, with autonomists, that evolutionary explanations can be modeled in terms of a deductive relationship between laws and cases. We explore the relationship between, chance, self-organization, and selection as sources of order in biological systems in order to make these points. (shrink)

Theoretical considerations related to neurological post-COVID complications have become a serious issue in the COVID pandemic. We propose 3 theoretical hypotheses related to neurological post-COVID complications. First, pathophysiological processes responsible for long-term neurological complications caused by COVID-19 might have 2 phases: Phase of acute Sars-CoV-2 infection linked with the pathogenesis responsible for the onset of COVID-19-related neurological complications and the phase of post-acute Sars-CoV-2 infection linked with the pathogenesis responsible for long-lasting persistence of post-COVID neurological problems and/or exacerbation of another (...) neurological pathologies. Second, post-COVID symptoms can be described and investigated from the perspective of dynamical system theory exploiting its fundamental concepts such as system parameters, attractors and criticality. Thirdly, neurofeedback may represent a promising therapy for neurological post-COVID complications. Based on the current knowledge related to neurofeedback and what is already known about neurological complications linked to acute COVID-19 and post-acute COVID-19 conditions, we propose that neurofeedback modalities, such as functional magnetic resonance-based neurofeedback, quantitative EEG-based neurofeedback, Othmer’s method of rewarding individual optimal EEG frequency and heart rate variability-based biofeedback, represent a potential therapy for improvement of post-COVID symptoms. (shrink)

This paper defends an internalist perspective of selection based on the hypothesis that considers living evolutionary units as Maxwell's demons (MD) or Zurek's Information Gathering and Using Systems (IGUS). Individuals are considered as IGUS that extract work by means of measuring and recording processes. Interactions or measurements convert uncertainty about the environment (Shannon's information, H) into internalized information in the form of a compressed record (Chaitin's algorithmic complexity, K). The requirements of the model and the limitations inherent to its formalization (...) are discussed. This approach offers an alternative view to the causes of evolutionary variations which goes beyond the classical Lamarckian-Darwinian controversy. I argue that random variations only apply near-to-equilibrium at the time organisms have attained structural closure, and that a speed up of mutation rates that facilitates the production of directed variations occurs far-from-equilibrium due to organisms' openness to the surrounding conditions. However, real organisms are located somewhere between the above two cases and thus, operate at an intermediate stage where there is a maximum efficiency of H/K conversion. In consequence, IGUS keep their autonomy and evolving capacity by compromising between external circumstances and inner constraints. This compromise is made possible by closure regulation. Likewise, this model explains why nature has favored the selection of agents capable of selectively recording a partial description of their environment. (shrink)