ULTIMATE COMPUTING - Quantum Consciousness Studies

34 Brain/Mind/Computer
computers. These neural net models, to be discussed later in this book, are based
on relatively simple assumptions regarding interneuronal synapses as switches
between neurons. Dynamic patterns of neural net activity can simulate systems
capable of learning, independent recognition, different “mental” states, and with
some imagination, rudimentary consciousness. The general architecture of
parallel computers is similar to neurons within the brain, and can take advantage
of simultaneous processing with lateral resolution of conflicting concepts. Despite
these apparent similarities, the brain’s complexity and the dynamic vastness of
human consciousness remain unassailable by current technology. The mind
remains enigmatic to brain and computer.
Figure 2.1: The Brain/Mind/Computer metaphorical triangle. Is the cytoskeleton
the key to understanding
Brain, mind, and computer are mutually metaphorical; each is related to the
other in ways that are not clearly understood. This impasse, the
“brain/mind/computer triangle,” is based on an incorrect assumption. The
irreducible substrate of information processing within the brain has been assumed
to be the notoriously slow interneuronal synapse. Consequently, synapses have
been compared to simple switches, and the brain has been compared to a
computer composed of a collection of synaptic switches. Because each neuron
within the brain has up to several hundred thousand synapses, it must “integrate”
information from among these synapses to regulate its output. Neurons utilize a
variety of analog functions including dendritic morphology, slow wave membrane
properties, and cytoskeletal activities which determine their responses within
neural networks, and which alter synaptic efficacy as apparent mechanisms of
learning. Thus each of the billions of neurons in the brain is a computer.
Similarly, single cell organisms which have no synapses and are independent
agents perform complex tasks involving rudimentary decision making, behavior,