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The NEURONS and NEURAL SYSTEM: a 21St CENTURY PARADIGM

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The NEURONS and NEURAL SYSTEM: a 21St CENTURY PARADIGM The NEURONS and NEURAL SYSTEM: a 21st CENTURY PARADIGM This material is excerpted from the full β-version of the text. The final printed version will be more concise due to further editing and economical constraints. A Table of Contents and an index are located at the end of this paper. A few citations have yet to be defined and are indicated by “xxx.” James T. Fulton Neural Concepts [email protected] August 1, 2016 Copyright 2011 James T. Fulton 2 Neurons & the Nervous System [xxx consider connexon, connexons instead of conexus, conexuses ] 2 The Functional Configuration of the Basic Neuron 1 Notice: The Coursera organization has recently begun offering free courses claimed to be at the college level. The course entitled “Computational Neuroscience” by two little known instructors, Adrienne Fairhall, Rajesh P. N. Rao2, from the University of Washington is based on the literature repeating endlessly the state of the art in the cytology of the cell and neurons from the first half of the 20th Century–specifically prior to the dawn of semiconductor physics, the discovery of the transistor, and the more recent discovery of the biological transistor. The latter is now in commercial use in organic light emitting device screens in cellphones and even television monitors. The existence of the biological transistor, a three-terminal device, totally deprecates the two terminal device, based on the Hodgkin-Huxley conceptual explanation of their totally empirical experiments, that is the basis of the course. The following material is in no way compatible with that new telecourse (May 2013). No further discussion of the telecourse except to point out that it remains possible to obtain a PhD in computational neuroscience without having demonstrated any detailed knowledge of how the neuron actually works. 2.1 Introduction It is a remarkable fact that the extensive neuroscience literature contains virtually no information describing the relationship between the input signal(s) applied to a neuron and the resulting output signal. This chapter will focus on this input-output relationship. It is also a fact that the neuroscience literature contains virtually no information concerning the cytological structure internal to a neuron. This chapter will address this subject, but a more extensive discussion of the morphology of the neuron will be presented in Chapter 5. It is also a fact that the neuroscience community has long accepted the concept of simple heavy inorganic ions (sodium, potassium and chlorine ions) moving freely through the liquid-crystalline bilayer cell wall of a neuron in the total absence of data showing this to be possible and considerable data showing such passage is not possible. The neuron has evolved to satisfy a wide variety of applications within the neural system as suggested by the block diagrams of Chapter 1 (Sections 1.1.2, 1.1.4 and 1.2.7). As noted elsewhere in this work, Hodgkin & Huxley were involved in exploratory research and were grasping for explanations as to what they observed. Their background, and that of the scientific community was relatively crude in the 1930's and 1940's. While they were unable to demonstrate that any ions passed through their axolemma, they assumed that ions did because of the difference in relative concentration of ions on the two sides of their axolemma. This assumption and their assertion of an “Independence Principle” to explain their assumption has 1Released: August 1, 2016 2https://www.coursera.org (The only current course is on Computational Neuroscience) The Neuron 2- 3 proven unsupportable in modern science. Unfortunately, the Don’s of the natal biochemical community of the 1960's, also relying on their limited scientific base, ordained that Hodgkin & Huxley were right and furthermore, the operation of the neural system was fundamentally based on chemical reactions. Their position has been very difficult to overcome because of its repeated assertion by their protégée in introductory textbooks. This situation has continued to the present day where Purves et al3. dedicate their unit 1 (particularly chapters 2 through 4) to regurgitating the Hodgkin & Huxley hypotheses, including their adoption of the euphemism relating the discharging of the axoplasm potential to an inrush of sodium ions (rather than a discharging of the axoplasm by electrons exiting the space via the internal amplifier) and the recharging of the axoplasm by an outrush of potassium ions (rather than the inrush of electrons from the glutamate/GABA power source) in the absence of any data to this day showing the axolemma is permeable to these heavy ions. The fact that ions of these heavy ions do not exist alone when in solution has also escaped the attention of these protégée (Section 8.5.4.4). That section also shows the coordinate complex of the sodium ion and water is significantly larger in diameter (9 Angstrom) than the putative internal diameter of the pores in the axolemma typically proposed in the literature (about 2 Angstrom). The hypothesis that the permeability of the axolemma is a variable is also unsupported by any physical chemistry. Such variation in permeability is not required in the context, and hypotheses, of this work, except in the fact that modified neurolemma can form an ideal electrolytic diode. Such a semiconductor diode exhibits a deterministic and well characterized variable impedance to electrons. Steriade, et. al. have addressed the difficulty of interpreting neuronal oscillations in brain functions without any understanding of the underlying mechanisms4. Their position is that the problem is the lack of a formal mathematical base for these mechanisms. However, mathematics does not provide a base for a mechanism, it provides a framework. A base is more fundamental and relies upon physics, electronics and chemistry. The oscillatory mechanisms associated with neurons are based on the active element within them, the Activa. The oscillatory performance of neurons is identical to those associated with man-made electronic circuits. The mathematical interpretation of both type of devices is well documented in the electronics literature. This will be demonstrated in this chapter. Their suggestion that a set of differential equations based on phase plane analysis can describe the oscillations of a neuron is correct. However, their supposition that the phase plane used is derivable from an autocatalytic (chemical) mechanism where the end product further activates the enzyme creating it appears unproven5. The resulting hypotheses, involving contorted chemistry, are not needed when the basic physics of the situation are examines as in this and the preceding chapter. This work takes exception to the claim of Steriade, et. al. that “In fact, chemically mediated oscillations, especially as it relates to the gK(Ca) is a most important component of the intrinsic electrical properties of neurons.” After providing a rationale for the autocatalytic hypothesis, they conclude “In addition, other ionic conductances are present that endow these neurons with a more complicated set of oscillatory properties.” This is the classical solution of solving a problem based on an inadequate understanding of the fundamentals. The investigator merely introduces more variables into the equations until a sufficient degree of flexibility is available to meet any requirement. Rather than introducing additional ions flowing with and counter to the local electric field, there is a need to re-examine the original chemically- based hypothesis. 3Purves, D. Augustine, G. Fitzpatrick, D. et al. (2004) Neuroscience, 3rd Ed. Sunderland, MA: Sinauer Associates. 4Steriade, M. Jones, E. & Llinas, R. (1990) Thalamic oscillations and signaling. NY: John Wiley, pp 132-133 5Goldbeter, A. & Moran, F. (1988) Dynamics of a biochemical system with multiple oscillatory domains as a clue for multiple modes of neuronal oscillations Eur Biophys Jour vol 15(5), pp 277-287 4 Neurons & the Nervous System 2.1.1 The fundamental neuron of biology The Neuron 2- 5 Figure 2.1.1-1 shows the basic schematic of a neuron that will be discussed in this chapter. The expression of the neuron in this figure is significantly modified from one by Shepherd in Byrne & Roberts (1997, page 91). This electrolytic configuration supports a fundamental difference from the historical two-terminal neuron of Hodgkin and Huxleys. The neuron and the biological transistor (the Activa) within it are three-terminal electrolytic devices. These elements are developed in detail in Section 2.2 & 2.3. The small numbers shown in this figure were not addressed in the original work except to tie that part of the neuron to simple waveforms that Shepherd related to operation of the stage 3 signal projection neuron. These waveforms were not sufficiently precise to be included here. The location of the Activa is shown by dashed lines in this annotated figure and is included in the region frequently described as the hillock in stage 3A neurons. Figure 2.1.1-1The generic schema of a biological neuron. Left; the generic neuron biased for analog operation. Right; same generic neuron with an extended (multi-segment axon and biased for pulse (action potential) generation. The individual axon segments of pulse generating neurons are myelinated to reduce signal attenuation between Nodes of Ranvier.. The combination of the dendritic and poditic trees is frequently described as a “bi-stratified dendritic tree.” Red elements, examples of axons of antidromic neurons. Blue; neuritic structures of orthodromic neurons. C; signal transmission by conduction in these regions. P; signal transmission by propagation along the myelinated axon segments. See text. Compare to Byrne & Roberts, 2004 & 2009. The same neuron can be operated in two distinct modes through electrolytic biasing. In both cases, all of the signals applied to the dendritic boutons are summed and the net sum is applied 6 Neurons & the Nervous System to the noninverting input terminal of the three-terminal internal Activa. Similarly, all of the signals applied to the poditic boutons are summed and the net sum signal is is applied to the negative (signal inverting) input terminal of the three-terminal Activa.
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