The old understanding

Recently, experimental and theoretical neurophysiology have diverged; this is the fundamental reason the brain’s elementary operations are not understood. Philosophically, the ’old understanding’ describes observations in terms of mathematical formulas and attempts to provide a physical background for them. If it fails, it uses hypothesised lipid or other biophysical effects or supposed other mechanisms, including even quantum mechanical ones. Anything (even potential quantum effects in the brain) but understanding concepts of science. No matter that those mechanisms contradict conservation laws and first principles, since ’the ordinary laws of science cannot describe living matter’.

Experimental research uncovers new facts and additional details. At the same time, instead of realizing and admitting that some initial hypotheses were incorrect, theory creates more ad hoc hypothesis and generates new (experimentally untested) theories. Given that biology claims that laws of nature are not valid for living matter, those newly created (and self-contradicting) theories have only a slight relation to nature. Bad examples include that

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  experimentalists measure the ion current’s speed in the range of m/s, but theory uses equations that assume a million times higher speed

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  experimental research has shown that the Axon Initial Segment (AIS) concentrates the majority of ion channels; however, theory suggests that all ion channels are distributed throughout the membrane

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  the current producing the Action Potential (AP) travels through AIS (that is, the resistor represented by the AIS is connected in series to the neuronal condenser); theory insists that the resistor represented by the AIS is connected in parallel to the neuronal condenser

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  the parallel $RC$ circuit cannot produce the experimentally observed neuronal behavior, another ad hoc assumption was introduced: a $K^{+}$ current flows against the $N{a}^{+}$ current in the opposite direction, with a precisely coordinated (although unexplained) temporal behavior of ion channels, despite experimental evidence

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  the ions have ‘mobility’, but do not need a driving force, and the electric field does not influence their movement

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  a ‘leakage current’ must flow, even in the resting state, despite the metabolic efficiency of biology; again, despite experimental evidence

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  the leakage current consists of ’leakage ions’, which move independently of the strong potential across the membrane

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  the current has the magic feature that it can both emit and absorb heat; this is the only discipline where a dissipative process is reversible.

Anything is possible, given that the laws of nature cannot describe life (or, maybe, life scientists do not know those laws).

The miserable fact is that several aspects of the ”old understanding” are wrong. Among others

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  The charge carriers are ions (with a mass nearly 100,000 times bigger and a propagation speed a million times slower than that of electrons). The Coulomb forces between ions are neglected, which excludes understanding that the current comprises ions and that the current transmission mechanism is drastically different.

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  The biological matter’s current conduction mechanism differs from the one in metals (leading to assuming the conduction speed of free electrons in ionic solutions for ions; the laws of electricity created for light and fast electrons are not valid in the same form for heavy and slow ions a wrong interpretation of conductance; wrong discussion of the electric operation of cells based on false analogies with classic electric circuits)

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  In the slow ion currents, the electric repulsion, along with the biological ’construction’ (constraints, and components with limited capacity), leads to ’skin’ effects that fundamentally alter the physical behavior. The ions create a thin ($<1nm$ thick) ion-rich layer in the electrolyte near the membrane. These skins are responsible for conducting phenomena rather than protein-based mechanical changes. Classical theory handles the membrane-separated segments (bulk electrolyte) as homogeneous (misses the layer where the dynamic processes of operating the neuron happen)

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  Ions have charge and mass; changing one of them changes the other

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  The repelling of the slow charged particles naturally causes mechanical and other changes; the signals propagate in the absence of external electrical voltage (concentration gradient and mechanical pressure)

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  The slow ion currents and the finite sizes are responsible for the timing relations of the cells

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  neurons’ potential changes are the result of electrochemical (electrodiffusional) processes instead of net electrical ones

Physiology introduced the extremely harmful concept of equivalent electrical circuit, see Fig. 3.17 that excludes understanding that

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  The ions in electrolites move under the simultanous effect of dual electrical/thermodynamic forces. Bioelectrical (thermodynamic) processes generate control voltages in biology, and they change continuously, i.e., it obscures the need to consider the cooperation and interference between electrical and thermodynamic disciplines; furthermore, it excludes understanding the associated mechanical, optical, and other changes.

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  The voltage is location- and time-dependent during AP creation;

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  The clamping methods introduce a feedback that contributes an electron current (converted to ion current) to the native ion current; the assumed ‘conduction change’ mechanisms contradict the first principles of charge and mass conservation.

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  The communication network has a heavily time-dependent operation

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  The neuronal signal processing and computation work with temporal arguments and results

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  In the neuronal oscillator, a wrong oscillator type is in use; the vital component AIS, discovered a half century ago and understood two decades ago, is not yet integrated into the theory of neuronal operation (leading to the ad-hoc introduction of a non-existent rectifying current)

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  A potential controlled mechanism, instead of a fake protein mechanism, forwards the charge carriers; disabled understanding why the neuron remains stable and how its power supply works

Biology has a statical view. It neglects that the underlying laws of classical physics developed for an infinite, homogeneous, structureless medium, where the interactions have the same speed, are applied to finite, inhomogeneous, structured living matter, where the interactions have enormously different speeds; furthermore, that the phenomena happen on the boundary of the continuous and particle views. The static view does not need (furthermore, does not enable the finding of) the laws of motion (in the sense of laws of Newton, Schrödinger, Hamilton)

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  It relies on biophysics, which applies the existing (’ordinary’) laws of classical physics inadequately. Classical physics derived its laws for ’another construction’; that is, biological matter also needs different approximations, laws and mathematical formalism. Consequently, what followed was wrong, including the computational principles, just because of the wrong model.

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  Experimentally, clamping and patching (using feedback) introduce foreign currents into the cell, stop its native operation, and enable deriving conclusions from that artificial, statical operating mode for the native, dynamical operating mode.

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  Theoretically, statical states are assumed, and the experienced dynamicity (processes) is accounted for as perturbation.

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  The voltage gradient, instead of currents, controls the neuronal oscillator’s operation, which is known from the well-established theory of electricity but neglected in physiology.

Similar is the case with neuronal computing and communication [28].

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  Biology applies von Neumann’s principles of computing [3], although von Neumann said that applying the idea to biology was ‘unsound’.

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  It refers to Shannon’s communication theory [32], although Shannon explicitly protested [33] against doing so.

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  It attempts to compare the so-called ‘spiking neural networks’, different mathematical learning algorithms, and even the functionality of artificial intelligence, without being aware that they have only the name in common with their biological counterparts [16].

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  The opposite direction faces also similar issues: borrowing only one aspect of biological computing cannot make an approach successful [11], neither in building supercomputers nor in biomorph architectures, large neural networks, brain simulation, or artificial intelligence systems.

Current physiology is based on some tragic misunderstandings (due to the lack of physical knowledge)

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  The static worldview, inherited from anatomy and confirmed by the incorrect interpretation of clamping, resulted in treating neuronal operation as perturbations to a static state, without considering causality. The case is similar to the incorrect hypothesis in physics that the orbits of the planets “must be” perfect circles; therefore, the observed deviations “must be” due to perturbations. Assuming perturbations hides the need for laws of motion in both cases. Relying on incorrect hypotheses excluded the introduction of the correct laws of motion (and, in general, understanding that there are laws underlying the observations). It required working out an elaborate system of perturbations (the work of generations of scientists using a wrong hypothesis).

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  The disciplinary approach (combined with overestimating the wrong hypothesis about protein mechanisms) protein!mechanism obscures the fact that the resting potential originates from combined electrical/thermodynamic effects; among others, that the reason for the transient voltage increase is a drastic concentration increase, and that during an AP, drastic transient concentration changes produce the observed voltage changes. The exact mechanism is responsible for the axonal signal transfer (instead of a magic action of cooperating lipids).

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  A spectacular example of the schizophrenic perspective in physiology is [34], which, theoretically, starts from the Hodgkin-Huxley model. Experimentally, they measure that there is no time delay between $K^{+}$ and $N{a}^{+}$ current; the same subthreshold and suprathreshold voltage gradients generate an AP with the same way but different magnitude (the AP is generated without exceeding some threshold, because a gradient of any size generates such a voltage on the AIS; and the current $K+$ itself also shows symptomes of hyperpolarization); the leakage current has the same (negligible) magnitude in resting and transient states (showing that two different ‘leakage’ mechanisms are present in the two states; furthermore, this current cannot be responsible for the membrane’s resting potential); they work with ‘ion counting’ but do not attempt to find out the identity of the ’leakage’ ions; the leakage ions are neither $K^{+}$ nor $N{a}^{+}$, nor do they generate Nernst voltage. Theoretically, they assume that the neuron “pumps 3 $N{a}^{+}$ ions out of the cell and two potassium ions in”; experimentally, they show in their Fig. 6 that the ratio changes between 0.01 and 7.5

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  The non-scientific approach, which posits that science’s first principles do not apply to life, excludes attempts to introduce physical explanations for processes in living matter and opens pathways for creating an alternative worldview where science creates nature instead of merely describing it.