Article
Quantum-like Behavior without Quantum Physics II: A Quantum-like Model of Neural Network Dynamics
Journal of Biological Physics
(2018)
Abstract
In earlier work, we laid out the foundation for explaining the quantum-like behavior of neural systems in the basic kinematic case of clusters of neuron-like units. Here we extend this approach to networks and begin developing a dynamical theory for them. Our approach provides a novel mathematical foundation for neural dynamics and computation which abstracts away from lower-level biophysical details in favor of information-processing features of neural activity. The theory makes predictions concerning such pathologies as schizophrenia, dementias, and epilepsy, for which some evidence has accrued. It also suggests a model of memory retrieval mechanisms. As further proof of principle, we analyze certain energy-like eigenstates of the 13 three-neuron motif classes according to our theory and argue that their quantum-like superpositional nature has a bearing on their observed structural integrity.
Keywords
- Memory,
- Quasispin models,
- Networks,
- Neurons,
- Interneurons
Disciplines
Publication Date
2018
DOI
10.1007/s10867-018-9504-9
Citation Information
Gualtiero Piccinini and Stephen A. Selesnik. "Quantum-like Behavior without Quantum Physics II: A Quantum-like Model of Neural Network Dynamics" Journal of Biological Physics Vol. 44 Iss. 4 (2018) p. 501 - 538 Available at: http://works.bepress.com/gualtiero-piccinini/37/