IUBio

Effects of Music

Lee Kent Hempfling lkh at cei.net
Sun Jan 26 07:00:33 EST 1997


rhall at uvi.edu (Richard Hall) enunciated:

<snip my stuff>

>I am still perplexed by the 60-120 hz number for brain computation cycles.
>Is the CORE Technology intelligent processing technique using a fourier
>type of analysis on brain waves?  I do not understand how a preferred
>musical frequency of 60-100 beats per minute (1-1.4 hz) relates to a either
>central processing cycle of 60-120 hz or the Crick-Llinas 33-80 hz
>frequencies.

Wave computation in a mean sum equation. Paper at
http://www.aston.ac.uk/~batong/Neutronics/wave.htm

>While trying to resolve this I have been slowly considering the behavior of
>several sensory and central systems.  The numbers do not seem consistent
>with high frequency through put.

>Granted the auditory system has unusual properties capable of resolving
>frequencies up to 50,000 hz in some bats. If sampling theory dictates 2
>sampling intervals to resolve one event,the poor bat would need a brain
>cycling at 100,000 hz to differentiate frequencies. Human speech employs
>optimal sound frequencies between 200-4,500 hz and we can discriminate up
>to 15,000 hz, but no one argues that bats are more intelligent than humans.

I can see where the confusion is setting in. The discussion of
frequencies should not be considered to be the signal frequency but
rather the clocking frequency.  It is like the sampling rate of your
computer has nothing to do with the configuration of bytes. Yet bytes
are variable.

>Why would higher processing speeds be needed?  Auditory receptor cells lack
>generator potentials and reception is first integrated by spiral (auditory)
>neurons projecting into the cochlear nucleus which maps frequency
>topographically. Integration typically has a longer time course since most
>neuron-neuron inputs are characteristically subthreshold and rely on
>summation to elicit postsynaptic responses.   Since axons cannot sustain ap
>much faster than 300 hz, our inputs must be indexed to frequency rather
>than mimic stimulus frequency. Indeed, human auditory nerves typically max
>out at 100 hz even when representing sound frequencies in excess of 10,000
>hz (Lieberman, 1978.)

Once again, the content (value) of the signal is not the same thing as
the rate in which it is computed.

>Spike trains can have high frequencies.  The absolute refractory periods of
>neurons are typically 3-5 ms thus axons may have action potentials (ap) at
>frequencies of up to 200 or 300 hz.  Still these ap are usually grouped in
>short bursts. Post synaptic responses have longer time courses which can
>further modulate high frequency input. Recordings of thalmocortical
>responses to tactile stimulation show ap bursts that may exceed 60 hz. If
>cortical processing is between 60 and 120 hz, a slight phase shift could
>miss most of that information and create a false signal at a weird
>frequency a process known as aliasing.  I would wager the cortex cycles
>slower than the frequency of inputs and thus avoids aliasing errors by
>integrating inputs over time.  Again the brain indexes reality as a complex
>pattern as might be expected by the massive volume of cerebrum dedicated to
>association cortices.

I like this examination. From a personal observation. Two things: The
component that is the chamber for the processing is not the signal
that is processed. and 2: Time order is right, association is right as
comparison in a mean sum (((P-N)/2)+N) which is a wave interaction
calculation...... clocking frequencies are derivatives of a base. It
is the enhanced clocking (ratio of memory to input in subconscious and
ratio of midterm to short term in conscious level) that makes the
difference. Output of first stage is reactive based on long term
memory. Output of second stage is contemplative based upon the short
term memory and its feedback of wave computation results into itself.

>Graded synaptic transmissions are much more common in the brain cortex than
>spike driven transmission (as you have pointed out several times) and
>graded potentials typically decay within 30-300 ms, again resulting in 3-33
>hz as the maximium rate for discriminated signal transmission.  Beta waves
>fall somewhere in the 13-25 hz range and correlate with an active brain.
>Graded transmission with long duration and lack of refractory periods is
>perfect for rapidly turning high frequency inputs in to proportionate
>release of neurotransmitter.  Since brain waves are based on graded
>potential changes these time constraints appear consistent with a brain
>processing model operating at 30 hz tops.

OK....  brain waves (ABGT) are harmonics. They are harmonics of
functional synchronous clocking frequencies. Even Llinas has pointed
out that the near 40hz he has observed comes from a back to front wave
in the 17k range.  Observing these brain waves is observing many
functions of parallel synchronous activity of clocking frequency. It
is not observing the base frequencies. Decay is indicative of the
space between the pulses.  If you would like I'd be more than pleased
to detail the entire human level protocol. I am restricted only in a
few areas due to patent protection in replicating the process but when
that point would be reached I would indicate the missing operand.

>The human preference for ritual music with a 1.4 hz beat over something
>"faster" may reflect something besides tuning curves of cochlear neurons or
>the cycles the brain flops information per second. I still like the
>correlation with heart rate, which incidently is influenced by brainstem
>activity just as is arousal of the sleepy brain.

Ah..... You make a very good point. It IS correlated. From the same
base as a derivative. So it would, pump blood, synchronously with many
other functions.  But it still only pumps blood. ;-)

>My point is that 60-120 hz seems to be a high estimate of central
>processing clocks based on the properties of individual synapses and fairly
>complex isolated neural preparations regardless of input frequency. The
>massively parallel solution that has evolved in vertebrates may tolerate or
>thrive at much slower sampling rates, eg. 1-30 hz.  Actually, slower
>sampling rates would make massively parallel darn near essential.

The rate of ratio enhancement in the levels determines the intellect.
In cute and cuddly creatures that rate is far less than human
subconscious ratios. The CREC scale points this out in an attempt to
make the playing field even. You can find it at the company site.

>Why then are the Crick-Llinas 33-80hz frequencies considered central to
>information processing?  From my arm chair, the CORE Technology intelligent
>processing technique seems simply empirical.

Of course it does. You have to keep in mind (no pun intended) that
until something becomes relational to something already in memory it
appears foreign. The more the new knowledge is different from the
established knowledge base of the observer the more foreign it will
appear and the harder it will be to assimulate it. The nice thing
about that though is that human memory is far more in control over
input than our cute and cuddly relatives. The draw back to that is
humans have a tendency to be consumed by our ability to be many steps
ahead of input. 

A discussion regarding consciousness for just a moment: There are two
forms of it in varying degrees. Other Awareness and Self Awareness. In
a rather horrible research paper published in DISCOVERY magazine a
couple of months ago (I forget the authors) study of chimps lead them
to make the conclusion backwards. It is just like most other things we
observe. And we always (well... almost always) ignore the perspective.

When I look at you, I see the image you would see in a mirror. So my
perspective on you would be (to you) backwards. Or in the case of
scientific observation... upside down. The problem with this is that
when we write and speculate and theorize about things we observe, we
do so from our perspective and not from the perspective of what we are
observing. 

This is what I called ''Observational Illusion" in a paper a couple of
years ago. "The Great Wall Of Neuroscience (Hempfling, 1995, blatant
self promotion)".  We can perhaps best illustrate this point by
considering a conversation between two people. 

When person A says something trying to make an explanation of what he
or she did to person B , person A relates the story from their
perspective. BUT... person B hears the story (observes it) from their
perspective.  Without clarification from person A , person B might
very well not have gotten the story but rather their impression of the
story. Do that enough and the original story is lost.

It is the same with politicians running for office: Congressman
Smith-Jones runs for office saying he will cut taxes. Cutting taxes is
upper most import to his constituents. And they elect him. When he
gets in office he forgets to cut taxes (it is not as high a priority
as it is to his constituents). The people cry ... foul! But that was
not the point. Perspective was different. The congressman's point was
to get elected. The people's point was to cut taxes. When a political
candidate has the same perspective as the people the other politicians
can not see it and call him or her an extremist.  The perspective is
not the same.

When evaluating scientific observations, we need to consider the
perspective of what we have observed MORE than the perspective of our
conclusions of what we observed. Doing this; we have the potential to
understand the things we observe and not just the way the things
appear to us.

Many scientists make the mistake of looking at a biological event and
trying to make it fit their perspective of computation. Which today is
digital. There are dichotomies as (Lofting 1996) put it so well.
Correlational Opposites as (Blue 1996) put it so well. But the most
important aspect is the binding of the oppositions. What comes from
the interaction of two opposing things (variable degree opposition,
equality cancels) is a blend of them both. It is then a new thing. 

In the brain the computational process is the blending of two things.
Two wavelets. The result is a new wavelet that is the mean sum of them
both. It is a smaller value than the sum of the two. So unless it is
supported (repetition, practice etc.) it will fade. That means
memories of things that happened many years ago are not the actual
reading of that memory but rather the reading of the memories of that
memory. There is no such thing as a repressed memory. There IS
non-supported memory.  

>Incidently, I have been exploring your web sight at my accustomed
>processing rate of 1 hz ;-).

Good. That means you will run out of things to read before I get
finshed with the next paper. "Light-Young's Double Slit and
Uncertainty"

Thanks, Richard,  for the very good letter.

Lee
Lee Kent Hempfling...................|lkh at cei.net
chairman, ceo........................|http://www.aston.ac.uk/~batong/Neutronics/
Neutronics Technologies Corporation..|West Midlands, UK; Arkansas, USA.




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