Thermodynamic properties and Hilbert space of the human brain

Abstract

Any macrosystem consists of many microparticles. According to statistical physics, the macroproperties of a system are realized as the statistical average of the corresponding microproperties. In our study, a model based on ensemble theory from statistical physics is proposed. Specifically, the functional connectivity (FC) patterns confirmed by Leading Eigenvector Dynamics Analysis (LEiDA) are taken as the microstates of a system, and static functional connectivity (SFC) is seen as the macrostate. When SFC can be written as the linear combination of these FC patterns, it is realized that these FC patterns are valid microstates for which the statistical results of relevant behaviors can describe the corresponding properties of SFC. In this case, the thermodynamic functions in ensemble theory are expressed in terms of these microstates. We apply the model to study the biological effect of ketamine on the brain and prove by maximum work principle that compared to that in the control group, the capability of work done by the brain that has been injected with ketamine declines significantly. Moreover, the quantum mechanical operator of the brain is further studied, and a Hilbert space spanned by the eigenvectors of the operator is obtained. The confirmation of the mechanical operator and Hilbert space opens great possibilities of using quantum mechanics to study brain systems, which would herald a new era in relevant neuroscience studies.