Abstract
Despite the mass of empirical data in neuroscience and plenty of interdisciplinary approaches in cognitive science, there are relatively few applicable theories of how the brain as a coherent system functions in terms of energy and entropy processes. Recently, a free energy principle has been portrayed as a possible way towards a unified brain theory. However, its capacity, using free energy and entropy, to unify different perspectives on brain function dynamics is yet to be established. This multidisciplinary study attempts to make sense of the free energy and entropy not only from the perspective of Helmholtz thermodynamic basic principles but also from the information theory framework. Based on the proposed conceptual framework, we constructed (i) four basic brain states (deep sleep, resting, active wakeful and thinking) as dynamic entropy and free energy processes and (ii) stylized a self-organizing mechanism of transitions between the basic brain states during a day period. Adaptive transitions between brain states represent homeostatic rhythms, which produce complex daily brain states dynamics. As a result, the proposed simulation model produces different self-organized circadian dynamics of brain states for different types of chronotypes, which corresponds with the empirical observations.
Highlights
Though the presented here interpretation of free energy and entropy stems mainly from the thermodynamic principles, at the same time we imply that it has a strong relation with the information theory as well, which is crucial to understand the meaning of the thermodynamic free energy and entropy employment for modelling the brain state dynamics
This paper provides a deductive conceptual framework, using universal free energy and entropy terms, that can provide a better understanding of brain states dynamics as self-organized energy and entropy processes
Based on the proposed modelling framework, we presented a pilot simulation model to showcase dynamical transitions between the basic brain states during the day
Summary
Though the presented here interpretation of free energy and entropy stems mainly from the thermodynamic principles, at the same time we imply that it has a strong relation with the information theory as well, which is crucial to understand the meaning of the thermodynamic free energy and entropy employment for modelling the brain state dynamics.Despite the wealth of empirical data in neuroscience, there are relatively few global theories about how the brain works. A recently proposed free energy principle for adaptive systems tries to provide a unified account of action, perception and learning This principle has been portrayed as a unified brain theory, its capacity to unify different perspectives on the brain function has yet to be established (Friston, 2010; Huang, 2008; Dayan, 1998). Hinton realized first that some tough problems can be solved in machine learning by treating a prediction error of neural networks as free energy, and minimizing it (Hinton and Terrence, 1999) His insight was that the constant updating of the brain’s states could be expressed in terms of minimizing free energy. Following this logic, everything that can change in the brain will change to suppress prediction errors, from the firing of neurons to the wiring between them, and from the movements of our eyes to the choices we make in daily life
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