ULTIMATE COMPUTING - Quantum Consciousness Studies

64 From Brain to Cytoskeleton
spontaneous releases of individual vesicles causing a background rate of
miniature end plate potentials which are below the threshold for depolarization of
the postsynaptic cell.
Specific binding of neurotransmitter molecules to post synaptic receptors
changes the membrane permeability to specific ions which produce localized
receptor potentials which are either excitatory or inhibitory. The post synaptic
membrane “integrates” the local receptor potentials spatially and temporally such
that when a “threshold” is exceeded, signals propagate in the post synaptic
dendrite, cell body, or axon.
Whether the response is excitatory or inhibitory depends on the species of ion
channel carrying the synaptic current. For example, in the neuromuscular
junction, acetylcholine increases post synaptic permeability to sodium and
potassium, leading to an excitatory, depolarizing action potential. Post synaptic
acetycholine activated channels open for one to two milliseconds and allow a net
entry of about 2 x 10 4 ions. Other synaptic channels stay open for tens of
milliseconds and pass 10 5 ions or more. Still other post synaptic receptors couple
directly to cytoskeletal changes and do not involve ionic conductance at all. At
inhibitory synapses, GABA may increase permeability to chloride ion, driving the
membrane potential away from threshold: Inhibition may also occur presynaptically
in which case release of excitatory neurotransmitter is prevented. By
combining multiple inputs, synapses “compute” to determine their output.
Nerve cells influence each other by either excitation, producing impulses in
another cell, or by inhibition, tending to prevent impulses from arising in an
adjacent cell. Lateral inhibition also occurs; activity in a group of active axons
inhibits firing in nearby fibers—an apparent sharpening or focusing mechanism.
A neuron receives many excitatory and inhibitory inputs from other cells
(convergence) and in turn supplies many others (divergence). The process
whereby neurons combine together all of their incoming signals is known as
integration. Thus each cell must integrate a multitude of synaptic inputs (up to
200,000 synapses per neuron) to determine its own output. Additional levels of
processing at dendritic branch points, dendritic spines, active nodes between
myelin sheaths, and changes in synaptic efficacy illustrate the complexity at the
level of individual neurons. Rather than a simple switch, each neuron is more like
a computer. The intraneuronal cytoskeleton is the nervous system within the
nervous system.
4.3 Representation of Information
The central enigma in brain science is how information is represented within
nervous systems. Understanding mechanisms of the vast capacities for storage,
retrieval, and processing of information within the brain would be of enormous
benefit not only to neuroscience, but to workers in computer science, particularly
artificial intelligence (AI). Indeed, vast strides have been made in AI by utilizing
“good guesses” about brain information processing and, conversely,
understanding of brain functions and capabilities is being advanced by AI related
theory including neural nets and parallel connectionism.
The underlying assumption about brain function and the comparative basis for
AI considers parallel networks of connected units in which neurons and their
synaptic connections are the fundamental substrates. However individual neurons
perform a significant amount of analog processing both at the level of dendrites
and within their cytoskeleton. For example, modification of synaptic transmission
threshold, the cornerstone of neural net learning models, is regulated by the
cytoskeleton and its cytoplasmic connections. Viewing neurons as fundamental