Quantum-like behavior without quantum physics II. A quantum-like model of neural network dynamics.

J Biol Phys

Department of Philosophy, Associate Director, Center for Neurodynamics, University of Missouri - St. Louis, St. Louis, Missouri, 63121, USA.

Published: December 2018

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.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6208592PMC
http://dx.doi.org/10.1007/s10867-018-9504-9DOI Listing

Publication Analysis

Top Keywords

quantum-like behavior
8
quantum-like
4
behavior quantum
4
quantum physics
4
physics quantum-like
4
quantum-like model
4
neural
4
model neural
4
neural network
4
network dynamics
4

Similar Publications

Quantum-inspired neural network with hierarchical entanglement embedding for matching.

Neural Netw

February 2025

School of Information Technology, Halmstad University, Halmstad, Sweden. Electronic address:

Quantum-inspired neural networks (QNNs) have shown potential in capturing various non-classical phenomena in language understanding, e.g., the emgerent meaning of concept combinations, and represent a leap beyond conventional models in cognitive science.

View Article and Find Full Text PDF

Our brains sense the future through a new quantum-like implicit learning mechanism.

Brain Res Bull

October 2024

Department of Quantitative Methods and Statistics, Comillas Pontifical University, established by the Holy See, Vatican City State. Electronic address:

Background: Imagine if our brains could unconsciously predict future events. This study explores this concept, presenting evidence for an inherent 'foreseeing' ability, termed anomalous cognition (AC). We introduce a new experimentally verifiable approach to explain anomalous information anticipation (AIA), a type of AC, based on an innovative, quantum-like model of implicit learning, grounded in Nonlocal Plasticity Theory (NPT).

View Article and Find Full Text PDF

Polyhydroxyalkanoates (PHAs) could be used to make sustainable, biodegradable plastics. However, the precise and accurate mechanistic modeling of PHA biosynthesis, especially medium-chain-length PHA (mcl-PHA), for yield improvement remains a challenge to biology. PHA biosynthesis is typically triggered by nitrogen limitation and tends to peak at an optimal carbon-to-nitrogen (C/N) ratio.

View Article and Find Full Text PDF

Infinite-memory classical wave-particle entities, attractor-driven active particles, and the diffusionless Lorenz equations.

Chaos

January 2024

School of Computer and Mathematical Sciences, University of Adelaide, Adelaide, South Australia 5005, Australia.

A classical wave-particle entity (WPE) can materialize as a millimeter-sized droplet walking horizontally on the free surface of a vertically vibrating liquid bath. This WPE comprises a particle (droplet) that shapes its environment by locally exciting decaying standing waves, which, in turn, guides the particle motion. At high amplitude of bath vibrations, the particle-generated waves decay very slowly in time and the particle motion is influenced by the history of waves along its trajectory.

View Article and Find Full Text PDF

Adaptive Dynamics Simulation of Interference Phenomenon for Physical and Biological Systems.

Entropy (Basel)

October 2023

Department of Biological Science and Technology, Tokyo University of Science, 6-3-1 Niijuku, Katsushika-ku, Tokyo 125-8585, Japan.

Article Synopsis
  • Biological systems exhibit quantum-like behaviors, particularly evident in lactose-glucose metabolism, which creates interference patterns akin to those found in the two-slit experiment with photons.
  • The adaptive dynamics approach is proposed as a bridge between biological and quantum physical phenomena, suggesting that it could help clarify quantum foundations.
  • The paper introduces a numerical simulation algorithm that models a billiard ball-like particle passing through two slits, successfully replicating interference patterns observed in quantum physics experiments.
View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!