ULTIMATE COMPUTING - Quantum Consciousness Studies

Brain/Mind/Computer 45
transmitting presynaptic information to other neurons by graded potentials at
dendrodendritic synapses, a process called “whispering together” (Adey, 1977).
The extent and significance of “electrotonic” current pathways among dendritic
membrane glycoproteins, membrane patches and dendritic spines are unknown
but could also be important. The net summation of dendritic potentials in cerebral
cortex is recorded at the scalp as electroencephalography (EEG). On the axonal or
output side the parent fibers do not necessarily excite all daughters at each
branching point, and branch points of some axons contain regions where high
frequency filtering, alternate firing and other forms of information processing can
occur (Scott, 1977). Branch point conductance may be influenced by small
changes in local geometry and electrical coupling, thus providing intraneural
regulation of neural transmission. Composition of membranes, spatial distribution
of glycoproteins, ion channels, myelin gaps (“nodes of Ranvier”) and clustering
of receptors have also been viewed as information coding. All potential neural
information processing modes (synaptic plasticity, axon and dendrite
morphology, membrane protein distribution) depend on the dynamic cytoskeletal
functions of axoplasmic transport and’ trophism (Chapter 5).
The neuron’s complexity may indeed be more like a computer than a single
gate. But what are the gates What is the indivisible substrate of neuronal
function Where is the neuron’s neuron How does an amoeba or paramecium
perform complex tasks without benefit of a synapse, neuron, or brain Relatively
recently, with perfection of electron microscopic fixation, immunofluorescence
and other techniques, the interior of living cells has been revealed. It has been
shown to possess complex, highly parallel interconnected networks of
cytoskeletal protein lattices which connect to and regulate membranes and all
other cellular components. The structure of these protein polymers, their dynamic
activities and the lack of a clear alternative understanding of cognition have led to
theoretical consideration of dynamic cytoskeletal activities as functional
information processing modes such as cellular automata and holograms.
This cytoskeletal view, developed in detail later in this book, is consistent
with many of the earlier schools of understanding consciousness. From the
cytoskeletal perspective, consciousness is a property of protoplasm (specifically
related to cytoskeletal proteins) but the vertebrate variety of consciousness is a
nonlinear collective effect-an emergent evolution-of that which exists in simple
organisms. An early nonlinear jump in the evolution of consciousness may have
occurred with the introduction of cytoskeletal centrioles and microtubules, and the
concomitant transformation of prokaryotic cells to eukaryotic cells about one
billion years ago (Chapter 3). Perhaps, as cytoskeletal networks and higher
organizational levels such as neural networks reached sufficient complexity in the
brains of mammals, collective properties emerged nonlinearly due to
cooperativity, resonance, phase transitions, and coherent phenomena allowing for
automata, holography, or some other mechanism of information processing.
Neural network theory, parallelism, connectionism, and the AI approach to
consciousness have provided enlightenment regarding the brain/mind. Many of
these approaches may be applied to the cytoskeleton, a fractal subdimension of
neural networks (Figures 2.3 and 2.4). Levels of neural network connections such
as the reticular activating system or hippocampal circuits may depend on
intracellular cytoskeletal dynamics for their regulation. For example, learning in
neural net theories is based on Donald Hebb’s (1949) suggestion that circuits of
connected neurons develop more conductive synapses which facilitate activation
of that circuit. Firing along given patterns following a specific stimulus is thought
to represent a specific concept, thought, or memory-information. Learning is then
thought to occur by reinforcement or strengthening of synaptic connections, or