The Physical Brain
The brain is a multiscale physical system whose dynamics can be treated by physical means. Neural field theory (NFT) averages over the microscale to obtain field equations for neural activity at scales of millimeters to the whole brain. When analyzed and simulated using standard methods from theoretical and computational physics, with parameters drawn from physiology, NFT predictions reproduce a wide variety of phenomena. These include spectra of activity, impulse responses, nonlinear dynamics, seizures, sleep-wake cycles, and brain structure-function relationships, as measured by a wide variety of techniques such as electroencephalography and MRI. Fitting of NFT to data can be used to infer physiological parameters and to track brain state in real time. Normal brains are found to operate in a near-critical state, which exhibits a rich variety of nonlinear responses, and can be destabilized into seizures via Hopf bifurcations. In the spectral domain, NFT activity eigenmodes give new windows into brain dynamics and function, and prove to be closely related to spherical harmonics, with eigenvalue splitting that reflects brain geometry and coupling between cortical hemispheres. These diverse outcomes demonstrate the power of physically-based analysis to predict and unify multiple phenomena and measurements across scales, and thus to open up new applications and imaging and analysis methods.