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Objective. Modelling is an important way to study the working mechanism ofbrain. While the characterization and understanding of brain are stillinadequate. This study tried to build a model of brain from the perspective ofthermodynamics at system level, which brought a new thinking to brainmodelling.  Approach. Regarding brain regions as systems, voxels as particles, andintensity of signals as energy of particles, the thermodynamic model of brainwas built based on canonical ensemble theory. Two pairs of activated regionsand two pairs of inactivated brain regions were selected for comparison in thisstudy, and the analysis on thermodynamic properties based on the model proposedwere performed. In addition, the thermodynamic properties were also extractedas input features for the detection of Alzheimer's disease.  Main results. The experiment results verified the assumption that the brainalso follows the thermodynamic laws. It demonstrated the feasibility andrationality of brain thermodynamic modelling method proposed, indicating thatthermodynamic parameters could be applied to describe the state of neuralsystem. Meanwhile, the brain thermodynamic model achieved much better accuracyin detection of Alzheimer's disease, suggesting the potential application ofthermodynamic model in auxiliary diagnosis.  Significance. (1) Instead of applying some thermodynamic parameters toanalyze neural system, a brain model at system level was proposed fromperspective of thermodynamics for the first time in this study. (2) The studydiscovered that the neural system also follows the laws of thermodynamics,which leads to increased internal energy, increased free energy and decreasedentropy when system is activated. (3) The detection of neural disease wasdemonstrated to be benefit from thermodynamic model, implying the immensepotential of thermodynamics in auxiliary diagnosis.

Modelling brain based on canonical ensemble with functional MRI: A thermodynamic exploration on neural system