  The fundamental, powerful process of computation in the brain has been widely
misunderstood. The paper [1] associates the general failure to build
intelligent thinking machines with current reductionist principles of temporal
coding and advocates for a change in paradigm regarding the brain analogy.
Since fragments of information are stored in proteins which can shift between
several structures to perform their function, the biological substrate is
actively involved in physical computation. The intrinsic nonlinear dynamics of
action potentials and synaptic activities maintain physical interactions within
and between neurons in the brain. During these events the required information
is exchanged between molecular structures (proteins) which store fragments of
information and the generated electric flux which carries and integrates
information in the brain. The entire process of physical interaction explains
how the brain actively creates or experiences meaning. This process of
interaction during an action potential generation can be simply seen as the
moment when the neuron solves a many-body problem. A neuroelectrodynamic theory
shows that the neuron solves equations rather than exclusively computes
functions. With the main focus on temporal patterns, the spike timing dogma
(STD) has neglected important forms of computation which do occur inside
neurons. In addition, artificial neural models have missed the most important
part since the real super-computing power of the brain has its origins in
computations that occur within neurons.
