  The neural networks of the human brain act as very efficient parallel
processing computers co-ordinating memory related responses to a multitude of
input signals from sensory organs. Information storage, update and appropriate
retrieval are controlled at the molecular level by the neuronal cytoskeleton
which serves as the internal communication network within neurons. Information
flow in the highly ordered parallel networks of the filamentous protein
polymers which make up the cytoskeleton may be compared to atmospheric flows
which exhibit long-range spatiotemporal correlations, i.e. long-term memory.
Such long-range spatiotemporal correlations are ubiquitous to real world
dynamical systems and is recently identified as signature of self-organized
criticality or chaos. The signatures of self-organized criticality i.e.
long-range temporal correlations have recently been identified in the
electrical activity of the brain. A recently developed non-deterministic cell
dynamical system model for atmospheric flows predicts the observed long-range
spatiotemporal correlations as intrinsic to quantum-like mechanics governing
flow dynamics. The model visualises large scale circulations to form as the
result of spatial integration of enclosed small scale perturbations with
intrinsic two-way ordered energy flow between the scales. Such a concept maybe
applied for the collection and integration of a multitude of signals at the
cytoskeletal level and manifested in activation of neurons in the macroscale.
The cytoskeleton networks inside neurons may be the elementary units of a
unified dynamic memory circulation network with intrinsic global response to
local stimuli.
