Neural Networks, Brainwaves, And Ionic Structures:
A Biophysical Model For Conscious System Processing
Faculty of Electrical Engineering;
This revolutionary model implies that future computers may
exhibit true consciousness.
Abstract: It is shown that neural networks with embedded brainwaves
cross the gap between the fast parallel unconscious mode of neuroscience and
the slow serial conscious mode of psychology. The electromagnetic (EM) component
of extremely low frequency (ELF) brainwaves appears to enable perfect fitting
with the narrow limits of conscious capacity in normal awake states, and with
the very extended limits in altered states of consciousness; due to the biophysical
relativistic mechanism of a dilated subjective time base. It also enables the
mixing of normally conscious and unconscious contents in altered states, due
to the relativistic Doppler mapping of the EM component of the "objective"
ELF brainwave power spectrum onto the zero-degenerate frequency "subjective" one.
Therefore, the EM component of ELF brainwaves provides an extraordinary
basis for consciousness-like internal displays. As the rather complex, additional
low-dielectric, weakly ionized gaseous neural network is necessary in these
processes, it seems that biological compounds and structures will essentially
determine the further development of brain-like conscious computers and molecular
There is a curious traditional dichotomy between psychologists and neuroscientists. Psychologists work with the slow, serial, and limited capacity component of the nervous system, which is associated with consciousness and voluntary control; while neuroscientists work with the fast, parallel "hardware" of the nervous system, enormous in size and complexity, and unconscious in its detailed functioning.
But what is the meaning of this dichotomy? It seems that such a dichotomy is necessary to provide an "interface" between slow voluntary motoric outputs, and fast, parallel, unconscious brain information processing.
How does a serial, slow, and relatively awkward level of functioning emerge from a system that is enormous in size, relatively fast-acting, efficient, and parallel? That is the key question which has been recently addressed by Baars . He has developed a very detailed cognitive model of consciousness, proposing that the split between psychologists and neuroscientists in looking at the nervous system reflects the global-workspace architecture.
Global-workspace represents a kind of working memory or central information exchange, whose contents can be "broadcast" to the nervous system of distributed modules as a whole, allowing many different specialized modules in the brain to interact, competing or cooperating for access.
It should be pointed out that the purely biochemical mechanisms of the extended reticular-thalamic activating system (ERTAS, serving as a major facilitator of conscious experience; whereas the cortex of the brain is providing the content of conscious experience) in the framework of Baars' cognitive model  cannot be accelerated up to several orders of magnitude while in altered states, and cannot account by itself for the changes in speed of information processing.
A physical mechanism that can account for the extremely dilated subjective time base in altered states is the relativistic one -- if only the "subjective" observer can be associated with an EM component of brainwaves (and evoked potentials) which can move through the brain with relativistic velocities.
Our theoretical model  implies that the electromagnetic (EM) component of that oscillatory brain activity (ongoing (EEG) and evoked potentials (EPs), i.e., brainwaves, can be closely related to global broadcasting associated with consciousness.
However, it is necessary that complete information (both conscious and unconscious) be permanently coded from neural networks into brainwaves; presumably as brainwave spatiotemporal patterns of the brain's ionic structure. This presumed process is a result of the temporal changes and activation of the synaptic interconnections in the neural networks of the brain .
The insufficient change in the biochemical rate of neurotransmitter secretion in altered states can be tested by positron emission tomography, or some other metabolic-sensitive methods. This can demonstrate the insufficiency of purely biochemical methods, and the necessity of adopting the proposed biophysical method in explaining the striking acceleration of conscious information processing in altered states of consciousness in comparison to normal ones.
This model fits perfectly with the restricted capabilities of conscious processing capacity in the normal awake state (when brainwaves are predominantly located in the brain tissue with a relative dielectric permittivity greater than 2); and with the very extended limits in altered states of consciousness (characterized by low-dielectric states with relative dielectric permittivity approximately equal 1). In altered states of consciousness, the relative velocity between the "objective" laboratory reference frame and the "subjective" one is highly relativistic . This effect is due to the biophysical relativistic mechanism of dilatation of the subjective time base.
The biophysical nature of the low-dielectric structure  can be related to a displaced (from the body) part of the ionic system which can conduct ELF brainwave currents inside the conductive channels, with a tendency of deterioration during a period of approximately one hour.
The detection of the low-dielectric ionic structure -- which is partly displaced from the body in altered states of consciousness -- is possible by monitoring local changes in the ionic concentration in the vicinity of the body by using infrared image processing, microwave scattering, electro-photography, positron emission tomography or some other isotope tracer studies.
This model also enables the mixing of normally conscious contents (predominantly corresponding to gamma, beta, and alpha brainwave bands ) and unconscious contents, corresponding to theta and delta bands ) in dream-like altered states  -- and is due to the relativistic Doppler mapping of the EM component of the "objective" ELF brainwave power spectrum onto the zero-degenerate frequency "subjective" one.
So, one can state that there are two levels of information coding in brain-like conscious neural networks: a) spatio-temporal level of information coding (which is the only one available in contemporary artificial neural networks ), and b) information coding at an extremely low frequency level (which also exists in biological neural networks, and is responsible for conscious and unconscious states, according to the model ).
The information encoding from neural networks to brainwaves can be tested on artificial or biological neural networks with embedded ELF electric activity. This testing procedure consists of a network learning some complex stimuli, or a conditioned reflex in the case of living organisms. If this information is simultaneously coded in ELF electric activity, it can be transferred to a neighboring equivalent neural network due to electromagnetic induction coupling. This transfer could demonstrate the possibility for neural network to brainwave encoding, and vice versa.
Our biophysical analysis of the serial conscious psychological mode in normal and altered states of consciousness implies as follows:
1) Brain-like conscious neural networks must have embedded ELF "brainwaves."
2) A complex ionic network (with the possibility of partial displacement from the neural network, and subsequent deterioration) is necessary.
3) As such a non-organic neural network with these types of properties is extremely difficult to fabricate, it seems that biological neural networks are a necessity in the development of brain-like computers.
4) Such brain-like computers offer the possibility of information processing at relativistic speeds.
Our biophysical model essentially determines that the further development of molecular electronics lies in the direction of biological compounds and structures. Such new components can provide an excellent basis for true conscious system processing.
This model also provides the basis for understanding Psi phenomena, as we shall see in the next issue of 21st.
 B.J. Baars, A Cognitive Theory of Consciousness (Cambridge Univ. Press, Cambridge, MA, 1988).
 D. Rakovic, D. Koruga, Z. Martinovic, and G. Stanojevic, On biophysical structure of brain-like biocomputers, in P.I. Lazarev, ed., Molecular Electronics: Materials and Methods (Kluwer, Dordrecht, The Netherlands, 1991).
 E.R. John, Switchboard versus statistical theories of learning and memory, Science 177 (1972), pp.850-864; E.R. John, T. Yang, A.B. Brill, R. Young, and K. Ono, Double-labeled metabolic maps of memory, Science 233 (1986), pp. 1167-1175.
 E. Basar, EEG Brain Dynamics (Elsevier, Amsterdam, 1980), Ch.2.
 D. Foulkes, Theories of dream formation and recent studies of sleep consciousness, Psychol. Bulletin 62 (1964), pp. 236-247.
 In C. Tart, ed., Altered States of Consciousness (Academic, New York, 1972.
 R. Hecht-Nielsen, Neurocomputing (Addison-Wesley, New York, NY, 1990).
Copyright 1995, All Rights Reserved, Dejan Rakovic, Ph.D., and Gordana Vitaliano , MD.
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