ingber.eeg.ps.Z in Neuroprose archive

[Lester Ingber]

The paper ingber.eeg.ps.Z has been placed in the Neuroprose archive.
This can be accessed by anonymous FTP on cheops.cis.ohio-state.edu
(128.146.8.62) in the pub/neuroprose directory.

This will laserprint out to 65 pages, so I give the abstract below to
help you decide whether it's worth it.  (I also enclose a referee's
review afterwards to sway you the other way.)  The six figures can
be mailed on request, and I'm willing to make some hardcopies of
the galleys or reprints, when they come, available.  However, since
this project is funded out of my own pocket, I might have to stop
honoring such requests.  The published paper will run 44 pages.

This message may be forwarded to other lists.

Lester Ingber


         ------------------------------------------ 
        |                                          |
        |                                          |
        |                                          |
        |           Prof. Lester Ingber            |
        |          ______________________          |
        |                                          |
        |                                          |
        | P.O. Box 857                703-759-2769 |
        | McLean, VA 22101   ingber at umiacs.umd.edu |
        |                                          |
         ------------------------------------------ 

=======================================================================
Physical Review A, vol. 44 (6) (to be published 15 Sep 91)

       Statistical mechanics of neocortical interactions:
      A scaling paradigm applied to electroencephalography

                          Lester Ingber
  Science Transfer Corporation, P.O. Box 857, McLean, VA 22101
                    (Received 10 April 1991)

     A series of papers has developed a statistical mechanics  of
neocortical  interactions  (SMNI), deriving aggregate behavior of
experimentally  observed  columns  of  neurons  from  statistical
electrical-chemical  properties  of synaptic interactions.  While
not useful to yield insights at the single neuron level, SMNI has
demonstrated  its capability in describing large-scale properties
of short-term memory and electroencephalographic (EEG)  systemat-
ics.   The necessity of including nonlinear and stochastic struc-
tures in this development has been stressed.  In  this  paper,  a
more  stringent test is placed on SMNI: The algebraic and numeri-
cal algorithms previously developed in this and  similar  systems
are brought to bear to fit large sets of EEG and evoked potential
data being collected to investigate  genetic  predispositions  to
alcoholism  and  to  extract  brain  "signatures"  of  short-term
memory.  Using the numerical algorithm  of  Very  Fast  Simulated
Re-Annealing,  it  is  demonstrated that SMNI can indeed fit this
data within experimentally  observed  ranges  of  its  underlying
neuronal-synaptic  parameters,  and use the quantitative modeling
results to examine physical neocortical  mechanisms  to  discrim-
inate  between  high-risk  and  low-risk  populations genetically
predisposed to alcoholism.  Since this first study is  a  control
to  span relatively long time epochs, similar to earlier attempts
to establish such correlations,  this  discrimination  is  incon-
clusive  because  of  other neuronal activity which can mask such
effects.  However, the SMNI model is shown to be consistent  with
EEG  data  during  selective attention tasks and with neocortical
mechanisms describing short-term  memory  (STM)  previously  pub-
lished  using  this  approach.   This paper explicitly identifies
similar nonlinear stochastic mechanisms  of  interaction  at  the
microscopic-neuronal,    mesoscopic-columnar   and   macroscopic-
regional scales of neocortical interactions.  These results  give
strong  quantitative  support  for an accurate intuitive picture,
portraying neocortical interactions as having common algebraic or
physics  mechanisms  that  scale  across  quite disparate spatial
scales and functional or behavioral phenomena,  i.e.,  describing
interactions  among  neurons,  columns  of  neurons, and regional
masses of neurons.

PACS Nos.: 87.10.+e, 05.40.+j, 02.50.+s, 02.70.+d

=======================================================================
Report of Referee        Manuscript No. AD4564

Over the years, I had several occasions to review papers by Lester Ingber.
However, there was never time enough to fully digest and
comprehend all of the details to convince myself that his efforts of
developing a theoretical basis for describing neocortical brain functions
are in fact sound and not just speculative.  This paper dispels all
those reservations and doubts, but unfortunately it is rather lengthy.

This paper, and the research behind it, is pioneering, and it needs to be
published.  The question is whether Physical Review A is the appropriate
journal.

Since the paper reviews and presents in a rather comprehensive fashion
the research by Lester Ingber in the area of modeling neocortical
brain functions, I recommend that it be submitted to Review of
Modern Physics.
=======================================================================



         ------------------------------------------ 
        |                                          |
        |                                          |
        |                                          |
        |           Prof. Lester Ingber            |
        |          ______________________          |
        |                                          |
        |                                          |
        | P.O. Box 857                703-759-2769 |
        | McLean, VA 22101   ingber at umiacs.umd.edu |
        |                                          |
         ------------------------------------------