Computer scientists
use the model of unidirectional brain activity to create
computational strategies based on the simple interpretation of how a
cell decides whether or not to fire its axon. The algorithm uses
multiple, analog, biased inputs to determine a single, digital,
monotone output. Each input is assigned a bias or importance that
changes throughout time as experience refines its overall impact.
This happens through the recursive pruning and expansion of a dynamic
decision-tree's limbs. It is a fractal growth that bends towards the
increasing value of its output. A few important or highly biased
dendrites can fire the axon while it takes many more with a
lower bias to coax emission -- the quantum event.
How the biological
cell determines the bias and firing patterns associated with its
individual network is a mystery. There are about a hundred-billion
neurons and a hundred-trillion connections (more than the stars in
our galaxy). With this much complexity, how is a brain anything but a
big box of noise? Why would a single neuron decide to fire? How does
a sole voice count in a cacophony of others? It seems so random but
functions much like a democratic poll; the brain signals the body to
act when relative networks exhibit the required activity, in other
words, reach the tipping-point; the little guys dance with enough
enthusiasm to raise the roof. Unlike a democracy, not every vote is
counted the same. Like a kleptocracy, an important few can make all
the difference. Stars often steal the show, blowing that roof right
off the walls.
However a cell
determines whether it will fire or not happens inside the cell where
a dense mesh of microtubules holds the architecture of the cell
together. For some time, this was the sole function assigned to the
stuff. Now we know it plays a role in the firing of the axon. This
substance is like the bones of a body except there are many more
microtubules in a cell than bones in a body. This essential component
of the system is linked with neurodegenerative diseases. How these
fibers are aligned and what parts are stable and dynamic are the
subject of intense study. But what do they mean?
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