Free energy and inference in living systems.

Organisms are non-equilibrium, stationary systems self-organized via spontaneous symmetry breaking and undergoing metabolic cycles with broken detailed balance in the environment. The thermodynamic free-energy (FE) principle describes an organism's homeostasis as the regulation of biochemical work constrained by the physical FE cost. By contrast, recent research in neuroscience and theoretical biology explains a higher organism's homeostasis and allostasis as Bayesian inference facilitated by the informational FE. As an integrated approach to living systems, this study presents an FE minimization theory overarching the essential features of both the thermodynamic and neuroscientific FE principles. Our results reveal that the perception and action of animals result from active inference entailed by FE minimization in the brain, and the brain operates as a Schrödinger's machine conducting the neural mechanics of minimizing sensory uncertainty. A parsimonious model suggests that the Bayesian brain develops the optimal trajectories in neural manifolds and induces a dynamic bifurcation between neural attractors in the process of active inference.

Bayesian mechanics of perceptual inference and motor control in the brain.

The free energy principle (FEP) in the neurosciences stipulates that all viable agents induce and minimize informational free energy in the brain to fit their environmental niche. In this study, we continue our effort to make the FEP a more physically principled formalism by implementing free energy minimization based on the principle of least action. We build a Bayesian mechanics (BM) by casting the formulation reported in the earlier publication (Kim in Neural Comput 30:2616-2659, 2018, https://doi.org/10.1162/neco_a_01115 ) to considering active inference beyond passive perception. The BM is a neural implementation of variational Bayes under the FEP in continuous time. The resulting BM is provided as an effective Hamilton's equation of motion and subject to the control signal arising from the brain's prediction errors at the proprioceptive level. To demonstrate the utility of our approach, we adopt a simple agent-based model and present a concrete numerical illustration of the brain performing recognition dynamics by integrating BM in neural phase space. Furthermore, we recapitulate the major theoretical architectures in the FEP by comparing our approach with the common state-space formulations.

Classical and quantum dissipative dynamics in Josephson junctions: An Arnold problem, bifurcation, and capture into resonance.

We theoretically study the phase dynamics in Josephson junctions, which maps onto the oscillatory motion of a pointlike particle in the washboard potential. Under appropriate driving and damping conditions, the Josephson phase undergoes intriguing bistable dynamics near a saddle point in the quasienergy landscape. The bifurcation mechanism plays a critical role in superconducting quantum circuits with relevance to nondemolition measurements such as high-fidelity readout of qubit states. We address the question "what is the probability of capture into either basin of attraction?" and answer it concerning both classical and quantum dynamics. Consequently, we derive the Arnold probability and numerically analyze its implementation of the controlled dynamical switching between two steady states under the various nonequilibrium conditions.

Recognition Dynamics in the Brain under the Free Energy Principle.

We formulate the computational processes of perception in the framework of the principle of least action by postulating the theoretical action as a time integral of the variational free energy in the neurosciences. The free energy principle is accordingly rephrased, on autopoetic grounds, as follows: all viable organisms attempt to minimize their sensory uncertainty about an unpredictable environment over a temporal horizon. By taking the variation of informational action, we derive neural recognition dynamics (RD), which by construction reduces to the Bayesian filtering of external states from noisy sensory inputs. Consequently, we effectively cast the gradient-descent scheme of minimizing the free energy into Hamiltonian mechanics by addressing only the positions and momenta of the organisms' representations of the causal environment. To demonstrate the utility of our theory, we show how the RD may be implemented in a neuronally based biophysical model at a single-cell level and subsequently in a coarse-grained, hierarchical architecture of the brain. We also present numerical solutions to the RD for a model brain and analyze the perceptual trajectories around attractors in neural state space.

Praseodymium Cuprate Thin Film Cathodes for Intermediate Temperature Solid Oxide Fuel Cells: Roles of Doping, Orientation, and Crystal Structure.

Highly textured thin films of undoped, Ce-doped, and Sr-doped Pr2CuO4 were synthesized on single crystal YSZ substrates using pulsed laser deposition to investigate their area-specific resistance (ASR) as cathodes in solid-oxide fuel cells (SOFCs). The effects of T' and T* crystal structures, donor and acceptor doping, and a-axis and c-axis orientation on ASR were systematically studied using electrochemical impedance spectroscopy on half cells. The addition of both Ce and Sr dopants resulted in improvements in ASR in c-axis oriented films, as did the T* crystal structure with the a-axis orientation. Pr1.6Sr0.4CuO4 is identified as a potential cathode material with nearly an order of magnitude faster oxygen reduction reaction kinetics at 600 °C compared to thin films of the commonly studied cathode material La0.6Sr0.4Co0.8Fe0.2O3-δ. Orientation control of the cuprate films on YSZ was achieved using seed layers, and the anisotropy in the ASR was found to be less than an order of magnitude. The rare-earth doped cuprate was found to be a versatile system for study of relationships between bulk properties and the oxygen reduction reaction, critical for improving SOFC performance.

A nationwide seroprevalence of total antibody to hepatitis A virus from 2005 to 2009: age and area-adjusted prevalence rates.

BACKGROUND/AIMS: Recent outbreak of hepatitis A in Korea is clearly related to the epidemiological shift of hepatitis A virus (HAV). However, nationwide seroprevalence data have been limited. This study estimated the nationwide, age- and area-adjusted anti-HAV prevalence from 2005 to 2009. METHODS: Retrospective analysis of the results of total anti-HAV test in 25,140 cases which were requested by 1,699 medical institutions throughout the nation to Seoul Clinical Laboratory from Jan. 1 2005 to Dec. 31 2009 was performed. The estimated seroprevalence was adjusted by area and age of the standard population based on the 2005 Census data from Korea National Statistical Office. RESULTS: The area-adjusted anti-HAV prevalence in the children younger than 10 years were 33.4% in 2005 and 69.9% in 2009. The most susceptible age groups to HAV infection during the last 5 years were teenagers and the young adults in their age of twenties. The area-adjusted seroprevalence in 2009 were 11.9% in the age group of 20-29 years, 23.4% in the age group of 10-19 years, 48.4% in the age group of 30-39 years. The population in 40-49 years showed geographically different seroprevalence with the lowest rate in Seoul (80%). CONCLUSIONS: The most susceptible age group to HAV infection is 10-29 years, while the young children less than 10 years showed about 70% seropositivity. The changing seroepidemiology should be monitored continuously for the proper vaccination and patient care.

Local entropy in quasi-one-dimensional heat transport.

We study the nonequilibrium entropy of the heat transport problem by performing molecular dynamics simulations of a quasi-one-dimensional gas of hard disks in the steady state. The entropy density, flux, and production rate, associated with the entropy balance of the system, are obtained from the numerically measured velocity distributions, based on the kinetic theory analysis of the Boltzmann entropy. We obtain an equilibriumlike Clausius relation from the computer experiments which, in turn, fulfills the generalized Gibbs relation for spatially inhomogeneous states.

Localization of phonon polaritons in disordered polar media.

The localization of the hybrid modes of phonons and photons in polar matter is investigated in the presence of random scatterers theoretically. We employ the self-consistent generalized Born-Huang approach to derive effective equations describing the phonon-polariton fields. Based on these equations, the density of states and various localization properties are exploited in two-dimensional systems both analytically and numerically within the framework of the Anderson model with a non-Hermitian effective Hamiltonian. Consequently, it is shown that the disorder effect brings some intriguing features which include the appearance of the localized states in the polariton bottleneck in the energy spectrum and the collapse of the energy gap. In addition, an analysis is given of the polariton level-spacing distribution.