Tensor network theory

Tensor network theory is a theory of brain function (particularly that of the cerebellum) that provides a mathematical model of the transformation of sensory space-time coordinates into motor coordinates and vice versa by cerebellar neuronal networks. The theory was developed by Andras Pellionisz and Rodolfo Llinas in the 1980s as a geometrization of brain function (especially of the central nervous system) using tensors.

The mid-20th century saw a concerted movement to quantify and provide geometric models for various fields of science, including biology and physics. The geometrization of biology began in the 1950s in an effort to reduce concepts and principles of biology down into concepts of geometry similar to what was done in physics in the decades before. In fact, much of the geometrization that took place in the field of biology took its cues from the geometrization of contemporary physics. One major achievement in general relativity was the geometrization of gravitation. This allowed the trajectories of objects to be modeled as geodesic curves (or optimal paths) in a Riemannian space manifold. During the 1980s, the field of theoretical physics also witnessed an outburst of geometrization activity in parallel with the development of the Unified Field Theory, the Theory of Everything, and the similar Grand Unified Theory, all of which attempted to explain connections between known physical phenomena.

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