To: "Karl Pribram"
From: "Dr. G. Heinz"
Subject: Re: Mathematik des Nervensystems
Cc:
Bcc: Heinz_Gerd_privat
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Lieber Karl,
haben Sie meine letzte Mail nach Walters Neuro-Konferenz erhalten (siehe unten)? Hoffe, Ihnen geht es gut?
Ich glaube, ich bin soweit um über Interferenznetze zu schreiben (Springer wartet schon seit fünf Jahren auf ein Buch). Gern würde ich Ihre Holonomic Brain Theory einarbeiten. Dazu brauche ich aber dringend einen Tip, wo die ursprünglichste Idee (Bild wäre schön) sowie die kompakteste Darstellung zu finden sind.
Viele Grüsse aus Berlin
Gerd Heinz
___________________________
PS: Fand Ihre Biographie unter:
http://en.wikipedia.org/wiki/Karl_H._Pribram
Holonomic model
Main article: Holonomic brain theory
Pribram's holonomic model, developed in collaboration with quantum physicist David Bohm, theorizes that memory/information is stored not in cells, but rather in wave interference patterns. Pribram was drawn to this conclusion by two facts:
* There are visual cortex response functions that correspond to Gabor functions, which in turn are related to hologram image functions.
* Drastic lesions can be made in animal brains which reduce, but do not extinguish memories (training), as demonstrated by Karl Lashley in the 1920s.
To formulate his model, Pribram utilized Fourier analysis, based on the Fourier Theorem, a variation of calculus that transforms complex patterns into component sine waves. Some believe that Pribram's theory also explains how the human brain can store so many memories in the engram in such limited space. Pribram believes the brain operates according to the same mathematical principles as a hologram. Bohm has suggested these wave forms may compose hologram-like organizations.
Technological advances associated with brain wave patterns, such as neuroimaging and transcranial magnetic stimulation (TMS), have provided understanding that was foreshadowed by the insights of Pribram and Bohm. TMS offers the potential for improving diagnostic objectivity and the efficacy of psychiatric interventions. Researchers have made significant advances with TMS brain implants, which focus magnetic pulses on specific brain regions, thereby perhaps altering the neurological wave patterns that Pribram describes.
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I wrote in my last email (9.11.2007):
Dear Karl,
we had many fun! I have to tell you the story. Walter Freeman was so kind to invite me to hold a talk about my 'Mathematics of Nerve System' at 14th Fall Academy, see below.
Starting with timefunctions I showed the waves of timefunctions (simulations), then the integrals of time function waves (called "images") and last the self- and cross interference proportions, that you called "holonomic". Some people were impressed, that the mathematics and physics of holograms is reducable on the level of abstract timefunctions.
I showed Walters wave image of 1982 and presented some laws I found. After my talk I asked Walter in front of the audience: "Can you imagine, that we would have a totally different neuro-science if Walter or Karl would have continued this way?" And to Walter I asked: "Wy did you left this way? Karl Pribram showed the holograms, you showed the waves - for me it seems, you had 1972 an impression, how the things can go?" he laughed up his sleeve and answered "Karl was my chief. He was the inventor. It was Karls intention, that I should work on this things during my dissertation, but my interest was different..." The audience smiled!
So let me please explain my deep respect to your ideas.
Dear Karl, I have a question. For my references to the inventors of "Interference Networks"
Lashley rats holomorphic memory
(McCulloch/Pitts) deadlock of interference with a time discretization
Jeffress first interference circuit
Pribram holography
Freeman first waves
Amari network dynamics
Abeles synfire chains
Konishi audience for Jeffress
Packard first waves on squids
I need the very first paper about the hologram-idea. Can you please send a copy or a PDF of the paper or of the page with the image?
Thanks for your help in advance.
Gerd
_______________________________________________________
14th Herbstakademie
THEORY IN COGNITIVE NEUROSCIENCE
November 4th - 7th, 2007 in Wildbad Kreuth, Bavaria, Germany organized by Harald Atmanspacher and Wolfgang Tschacher Submission and registration see conference website: http://www.upd.unibe.ch/research/symposien/HA14.html Submissions directly to: herbstakademie2007@igpp.de
ABSTRACT
Heinz, Gerd, GFaI Berlin
heinz@gfai.de, www.gfai.de/~heinz
“Nerve velocity calculated by cross interference distance”
Signals in nerve systems can be seen as pulse-like time-functions, flowing slowly through different stages of information processing. We will call them discrete waves on wires that flow in inhomogeneous nets of wires, so called “Interference Networks” (IN). Excitement locations (interference integrals) are coupled to places, were many wave maxima interfere.
Different researchers found different views on such nets between holography and experimental sciences. Lloyd A. Jeffress and Mark Konishi detected a symmetry relation, Karl Pribram analysed them to be holomorphic, Walter Freeman analysed wave packets and Andrew Packard observed waves on animals.
The author found IN to be “image-like”. Basic properties of IN were investigated with very simple, nearly homogeneous configurations. Data addressing in IN needs the self-interference condition, like in optical images, projections can only occur under certain circumstances at defined places, the locations of self-interference.
If subsequent pulses flow with specific velocity, the pulse-pause corresponds to a geometric distance, the geometric wave length. If many pulses flow through different nerves and re-combine, a specific pattern shows the so called cross-interference distance: Around a self-interference figure subsequent pulses form a cross-interference pattern, which has a distance to the self-interference figures. To take IN for data addressing, only the space of self-interference can be used.
But the average distance between self- and cross interference pattern is reasoned by the average pause between the waves! We call it cross-interference distance R
(1) R = vT/2
with average nerve velocity v and puls distance (pause) T = 1/f, fire frequency is f.
(Eqn. (1) of http://www.gfai.de/~heinz/historic/pressinf/bilder_d.htm)
If we change now the view, we can ask for the velocity for a cross interference distance of two meter for a long Swiss Guardian.
(2) v = 2 R/T = 2 fR
Dependent of the maximum firing rate and geometrical configurations we get values for v between 10 and 120 m/s.
Example: R = 2 m; f = 30 Hz
v = 2 fR = 2* 30 Hz * 2 m = 120 m/s
The value corresponds to the velocity measurable in myelin-isolated nerves.
Fazit:
It seems, peripheral nerve system can be seen to be interferencial networks.
______________________________
Dear Karl,
thank you very much for your letter.
Your remarks:
>The major problem I see is that the primate brain is not a homogeneous medium
I introduced the homogeneous cases for demonstrations. Otherwise it is hard to teach IN.
The term "Interference Network" suggests the oppposite: it is a signal network with delays, strongly inhomogeneous.
But you can not find a way to understand basic properties.
Best regards - Viele Gruesse
Gerd
At 10:05 07.08.2007 -0400, you wrote:
>Dear Gerd: Thank you for your very interesting ms. The major problem
>I see is that the primate brain is not a homogeneous medium within
>which your interference patterns could spread. Any ideas as to how to
>overcome this problem? Did I miss something? Best, Karl
>
>
>On 8/6/07, Dr. G. Heinz wrote:
>>
>>
>>
>> Dear Karl,
>>
>> only for demonstration per coincidence I calculated the puls-velocity of a
>> two-meter sized nerve system over the cross-interference distance
>> (Fremdinterferenzradius R). Doing this, I got 120 m/s.
>>
>> The idea is comparable simple: If it is an interference system that has to
>> address all possible locations separately, the cross interference radius
>> obtains a specific velocity.
>>
>> See
>> http://www.gfai.de/~heinz/historic/pressinf/bilder_d.htm#radius
>>
>> Hope, you can share my joy?
>> Afterwards I renamed the page to 'Die Mathematik des Nervensystems'.
>> (I'm sorry, I was so happy!)
>>
>> If you like, I can give some lectures...
>>
>>
>> Viele Gruesse
>> Gerd
>>
>>
>>
>> Mit freundlichen Gruessen / Best regards / Meilleures salutations
>> Gerd Heinz
>>
>>
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