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[Christof Koch]

Having carried out detailed biophysical simulation of single neurons at
the single cell level all my professional life with the aim of  trying to
identify and understand the elementary biophysical mechanisms
underlying information processing , I disagree with Steve LeharUs statement (in
reply to JimUs earlier comment):

        This is a curious view in an age  when science has successfully
        probed the  atomic  element   of the brain,    the neuron, sufficiently
        to understand its major mode of operation. . .

We do NOT understand why neurons have dendritic trees and why they come in diffe
rent sizes and shapes, what---if any--- nonlinear operations go
on there, why the membrane at the cell body contains more than a dozen
distinct ionic currents, what nonlinear  functional is being computed bat
the soma, etc. etc.

On the other hand, we have made progress. Thus, modeling the I/O
capabilities of a neuron via linear synaptic interaction plus a nonlinear squash
ing function (e.g. the Hopfield model) at the soma is a more faithful
rendition than the binary McCulloch and Pitts neuron. Adding sigma-pi
capabilities, i.e. allowing for the possibility of synaptic products
(nominals) is a further  improvement.  The recent realization that
the detailed temporal structure of the action potential discharge might
be terrible relevant (e.g. 40 Hz oscillations) to its function a further
improvment in our view of the neuron.  Thus, even if some of todayUs
connectionists model are still crude, they point in the right direction.


Christof
koch at iago.caltech.edu