Modelling Microtubules in the Brain as n-qudit Quantum Hopfield Network and Beyond

TL;DR

This paper extends a quantum neural network model based on microtubules in the brain from qubits to n-qudits, aiming to enhance the mathematical abstraction in modeling consciousness.

Contribution

The work introduces an n-qudit quantum Hopfield network model inspired by microtubules, advancing the quantum modeling of consciousness beyond previous qubit-based approaches.

Findings

Extended the quantum neural network model to n-qudits

Demonstrated potential for higher abstraction in consciousness modeling

Built on prior simplified tubulin dimer models

Abstract

The scientific approach to understand the nature of consciousness revolves around the study of human brain. Neurobiological studies that compare the nervous system of different species have accorded highest place to the humans on account of various factors that include a highly developed cortical area comprising of approximately 100 billion neurons, that are intrinsically connected to form a highly complex network. Quantum theories of consciousness are based on mathematical abstraction and Penrose-Hameroff Orch-OR Theory is one of the most promising ones. Inspired by Penrose-Hameroff Orch-OR Theory, Behrman et. al. (Behrman, 2006) have simulated a quantum Hopfield neural network with the structure of a microtubule. They have used an extremely simplified model of the tubulin dimers with each dimer represented simply as a qubit, a single quantum two-state system. The extension of this model to n-dimensional quantum states, or n-qudits presented in this work holds considerable promise for even higher mathematical abstraction in modelling consciousness systems.