Approximating the Effect of Consciousness on Stochastic Brain Structures

Abstract

There is a large amount of evidence in the Parapsychology literature that indicates thatconsciousness is not an emergent property of neuronal interactions and can exist andfunction independently of a brain. Here we examine mathematical methods that canbe used to derive dynamic equations for the mind-matter interactions occurring in thebrain that these observations imply the existence of. We use the moments method toapproximate the effect that consciousness has on stochastic binary decision-makingneural networks , which we model using biologically realistic Wilson-Cowan equations(Deco et al., 2007). We show that small changes in the variance of the randomness (onthe order of 0.1 Hz2) consumed by the neural networks can bias the networks to selectone binary decision value over the other. Using observations about the interconnectednessof relatively isolated groups of neurons, we argue that biases of the size predictedby the approximation would be sufficient to allow a brain-independent consciousnessto exert significant control over the brain. The results that we present here are relevantto any theory positing that rote computations carried out by neurons are not the solecontributor to consciousness.