ULTIMATE COMPUTING - Quantum Consciousness Studies

26 Toward Ultimate Computing
“spider-web” of motionless curves (the “Chladni” nodal lines). Originally
observed by sprinkling sand on a vibrating plate, these patterns more recently
have been observed by laser interferometry. The pattern is the “macron” and
depends upon intrinsic dimensions and elasticity of the medium, and extrinsic
frequency and amplitude of the driving force. The plate is a two dimensional
example, however a simple rubber ball may be visualized with stable vibrational
modes characterized by symmetric distortions of shape separated by motionless
nodal surfaces. Another macron example is a round dish filled with a thin layer of
isotropic liquid. If the bottom of the dish is heated, the liquid will soon begin to
simmer; careful observation reveals nodal lines and packed hexagons called
Benard cells within which the liquid convects toroidally. This Benard
phenomenon, also seen as wind induced patterns in the sands of the Sahara and
other deserts, is also considered by Abraham as a macron. These macrons or
stable modes also depend on intrinsic controls such as shape, compressibility and
viscosity, and external controls such as frequency and amplitude of the driving
force.
Other forms of macrons described by Abraham include smoke rings,
opalescences like abalone shell, and the aurora borealis or Northern Lights.
Turning to the brain, Abraham conjectures: “a thought is a macron of the brain
bioplasma.” He proposes that spatial patterns of EEG are electrical macrons at
dendritic surfaces or that macrons occur within nerve cells. He suggests that
repetitive reinforcement of specific macrons “hardens” them into a structural form
in a learning mechanism. Abraham’s macrons may be compared to standing
waves, reaction diffusion systems, and holograms which can all manifest 3
dimensional analog patterns of interactive information suitable to the
cytoskeleton. Another “digital” system of interactive patterns in dynamic lattices
is the “cellular automaton.”
1.5.4 Cellular Automata
Complex behavior resulting from collective activities of simple subunits
occurs in “cellular automata.” Von Neumann’s (1966) original cellular automaton
consisted of a large number of identical “cells” connected in a uniform pattern.
The term “cell” was chosen by Von Neumann and others as the indivisible
subunit in “cellular automata” based on biological “cells” as indivisible subunits
of life. Much like atoms once indivisible, are now recognized to be composed of
electrons, protons, neutrons, quarks, etc., it is now apparent that biological cells
are complex entities whose actions depend on collective functions of intracellular
structures including the cytoskeleton. Nevertheless, “cellular” in cellular
automaton jargon means an indivisible grain, a discrete subunit with a finite
number of states. The essential features of cellular automata are 1) at a given time,
each cell is in one of a number of states. 2) The cells are organized according to a
fixed geometry. 3) Each cell communicates only with other cells in its
neighborhood; the size and shape of the neighborhood are the same for all cells.
Depending on geometry, the number of neighbors may be 4 (rectangular), 6
(hexagonal), 8 (rectangular with corners) or more neighbors per subunit or cell. 4)
There is a universal clock. Each cell may change to a new state at each tick of the
clock depending on its present state, and the present states of its neighbors. The
rules for changing state are called the transition rules of the cellular automata. At
each clock tick (or “generation”) the behavior of each cell depends only on the
states of its neighbors and its own state. In cellular automaton, simple neighbor
rules can lead to complex, dynamic patterns.
Cellular automaton may be considered similar to lattice models such as a two
dimensional Ising generator. Based on magnetic spin states of components within