Statistical Mechanics
Spontaneous and stimulus-induced coherent states of dynamically balanced neuronal networks (1711.09621v4)
Takashi Hayakawa, Tomoki Fukai
2017-11-27
How the information microscopically processed by individual neurons is integrated and used in organising the macroscopic behaviour of an animal is a central question in neuroscience. Coherence of dynamics over different scales has been suggested as a clue to the mechanisms underlying this integration. Balanced excitation and inhibition amplify microscopic fluctuations to a macroscopic level and may provide a mechanism for generating coherent dynamics over the two scales. Previous theories of brain dynamics, however, have been restricted to cases in which population-averaged activities have been constrained to constant values, that is, to cases with no macroscopic degrees of freedom. In the present study, we investigate balanced neuronal networks with a nonzero number of macroscopic degrees of freedom coupled to microscopic degrees of freedom. In these networks, amplified microscopic fluctuations drive the macroscopic dynamics, while the macroscopic dynamics determine the statistics of the microscopic fluctuations. We develop a novel type of mean-field theory applicable to this class of interscale interactions, for which an analytical approach has previously been unknown. Irregular macroscopic rhythms similar to those observed in the brain emerge spontaneously as a result of such interactions. Microscopic inputs to a small number of neurons effectively entrain the whole network through the amplification mechanism. Neuronal responses become coherent as the magnitude of either the balanced excitation and inhibition or the external inputs is increased. Our mean-field theory successfully predicts the behaviour of the model. Our numerical results further suggest that the coherent dynamics can be used for selective read-out of information. In conclusion, our results show a novel form of neuronal information processing that bridges different scales, and advance our understanding of the brain.
Transient magnetic domain wall AC dynamics by means of MOKE microscopy (1903.03006v1)
Pablo Domenichini, Cintia Quinteros, Mara Granada, Sophie Collin, Jean Marie George, Javier Curiale, Sebastian Bustingorry, Maria Gabriela Capeluto, Gabriela Pasquini
2019-03-07
The domain wall response under constant external magnetic fields reveals a complex behavior where sample disorder plays a key role. Furthermore, the response to alternating magnetic fields has only been explored in limited cases and analyzed in terms of the constant field solution. Here we unveil phenomena in the evolution of magnetic domain walls under the application of alternating magnetic fields within the creep regime, well beyond a small fuctuation limit of the domain wall position. Magnetic field pulses were applied in ultra-thin ferromagnetic films with perpendicular anisotropy, and the resulting domain wall evolution was characterized by polar magneto-optical Kerr effect microscopy. Whereas the DC characterization is well predicted by the elastic interface model, striking unexpected features are observed under the application of alternating square pulses: magneto-optical images show that after a transient number of cycles, domain walls evolve toward strongly distorted shapes concomitantly with a modification of domain area. The morphology of domain walls is characterized with a roughness exponent when possible and contrasted with alternative observables which result to be more suitable for the characterization of this transient evolution. The final stationary convergence as well as the underlying physics is discussed.
Quantum Nash equilibrium in the thermodynamic limit (1806.07343v3)
Shubhayan Sarkar, Colin Benjamin
2018-06-19
The quantum Nash equilibrium in the thermodynamic limit is studied for games like quantum Prisoner's dilemma and the quantum game of chicken. A phase transition is seen in both games as a function of the entanglement in the game. We observe that for maximal entanglement irrespective of the classical payoffs, a majority of players choose Quantum strategy over Defect in the thermodynamic limit.
The stochastic motion of self-thermophoretic Janus particles (1903.02992v1)
Pierre Gaspard, Raymond Kapral
2019-03-07
Langevin equations for the self-thermophoretic dynamics of Janus motors partially coated with an absorbing layer that is heated by a radiation field are presented. The derivation of these equations is based on fluctuating hydrodynamics and radiative heat transfer theory involving stochastic equations for bulk phases and surface processes that are consistent with microscopic reversibility. Expressions for the self-thermophoretic force and torque for arbitrary slip boundary conditions are obtained. The overdamped Langevin equations for the colloid displacement and radiative heat transfer provide expressions for the self-thermophoretic velocity and its reciprocal contribution where an external force can influence the radiative heat transfer. A nonequilibrium fluctuation formula is also derived and shows how the probability density of the Janus particle displacement and radiation energy transfer during the time interval [0,t] are related to the mechanical and thermal affinities that characterize the nonequilibrium system state.
Universal voter model emergence in genetically labeled homeostatic tissues (1903.02985v1)
Hiroki Yamaguchi, Kyogo Kawaguchi
2019-03-07
Recent experiments in adult mammalian tissues have found scaling relations of the voter model in the dynamics of the genetically labeled population of stem cells. Yet, the reason for this seemingly robust appearance of the voter model remains unexplained. Here we show that the voter model kinetics is indeed a generic behavior that arises at macroscale in a linearly stable homeostatic tissue undergoing turnover. Starting from the continuum model of a multicellular system, we show that the dynamics of the labeled cell population converges to the voter model kinetics at large spatio-temporal scale of observation. We present a method to calculate the length scale and time scale of coarse-graining that is required in obtaining the effective voter model dynamics, and apply it to the growth factor competition model and the pairwise mechanical interaction model.
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