A Topological Surface Spin Network Brain Model: Theoretical Physics Approach to an Information Processing and Learning System (en Inglés) - Siddhartha Sen

This book presents a way to understand brain functions from its global properties using the methods of theoretical physics. The global form of the brain is captured by a Riemann surface with spin structure. Using such a surface network model, a global way to understand how all brain signals are generated, how and where memories are stored, how memory is recalled, how the brain behaves as a quantum computer, how the internal logic of the brain can be determined and consciousness measured. The results are quantitative. The signals produced are solitons and have explicit analytic representations. This book also shows how EEG waveforms are co-produced whenever any brain signal is generated and is able to correctly predict their frequencies and amplitudes. The memory structure is shown to be an extended helical quantum structure of linked protons and conjectured to be located in the insulating sheaths of nerve fibers. Each memory structure is shown to have a memory specific excitation frequency that overlaps with EEG frequencies. Numerous applications of the approach are included and chapters summarizing neuroscience ideas used and mathematical concepts of algebraic geometry are explained in an intuitive way. Recent observational evidence for the existence of quantum structures in the brain are discussed and von Neumann’s conjecture that the internal logical system of the brain is non-standard is proved.