Perceptions and actions, thoughts and memories result from coordinated activity in hundreds or even thousands of neurons in the brain. It is an old dream of the physics community to provide a statistical mechanics description for these and other emergent phenomena of life. These aspirations appear in a new light because of developments in our ability to measure the electrical activity of the brain, sampling thousands of individual neurons simultaneously over hours or days. The progress that has been made in bringing theory and experiment together is reviewed, with a focus on maximum entropy methods and a phenomenological renormalization group. These approaches have uncovered new, quantitatively reproducible collective behaviors in networks of real neurons and provide examples of rich parameter-free predictions that agree in detail with experiments.

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• Classical statistical mechanics
• Neural information
• Shannon entropy
• Biological networks
• Biological neural networks
• Ising model
• Renormalization group