Ed Witten - examining an aspect of String Theory. He isn't convinced that consciousness can ever be solved by physics.
It was interesting pulling up a blog post by chemist Ash Jogelekar where he quoted physicist Edward Witten as writing:
"I think consciousness will remain a mystery. Yes, that's what I tend to believe. I tend to think that the workings of the conscious brain will be elucidated to a large extent. Biologists and perhaps physicists will understand much better how the brain works. But why something that we call consciousness goes with those workings, I think that will remain mysterious. I have a much easier time imagining how we understand the Big Bang than I have imagining how we can understand consciousness...
Understanding the function of the brain is a very exciting problem in which probably there will be a lot of progress during the next few decades. That's not out of reach. But I think there probably will remain a level of mystery regarding why the brain is functioning in the ways that we can see it, why it creates consciousness or whatever you want to call it. How it functions in the way a conscious human being functions will become clear. But what it is we are experiencing when we are experiencing consciousness, I see as remaining a mystery...
Perhaps it won't remain a mystery if there is a modification in the laws of physics as they apply to the brain. I think that's very unlikely. I am skeptical that it's going to be a part of physics."
This may be so, but I don't believe the problem is as insuperable as he and many other physicists believe. But it will require patience and getting our theories tested properly in terms of what could be considered an environment conducive to human consciousness. Jogelekar himself adds:
"what Witten is saying here is in some sense quite simple: even if we understand the how of consciousness, we still won't understand the why. This kind of ignorance of whys is not limited to consciousness, however"
Which is true! I have no idea WHY solar flares and coronal mass ejections are often linked together and erupt where they do but I have a detailed idea of how they do. In science this is the most one can really aspire to: answering the 'how' as opposed to the 'why'.
In the case of consciousness it would seem that a logical starting point is the physical scale of the synaptic cleft. The scale is on the order of 200-300 nm and hence subject to the Heisenberg Uncertainty Principle. Once so subject, then it embodies the laws of quantum mechanics. Wave forms, as opposed to simple classical trajectories of particles (e.g. electrons) are enabled, because uncertainty principle limitations applied to calcium ion (Ca++) capture near synapses shows they (calcium ions) must be represented by a probability wave function. (Cf. Henry Stapp, Mind, Matter And Quantum Mechanics, Springer-Verlag, 1983).
Consider the 4D wave function U(X,Y,Z, t) . Then brain dynamics and function at a time t is contingent upon the neuron and its connections to synapses at the same time t. We therefore want networks that invoke the above function and Pauli spin operators as effective gates.
Application of the Heisenberg Uncertainty Principle to Ca+2 ions (at body temperature) discloses the associated wave packet dimension increases to many times the size of the ion itself. Thus we can represent the ion uptake superposition as a separate contributor to the aggregate (sub-complex) or neuronal assembly:
U (A1....A n) + U (Ca+2) n
It was physicist David Bohm who first pointed out ('Quantum Theory', p. 169), a very precise analogy of quantum processes to thought. In particular, the quantum "wave packet collapse" (e.g. to a single eigenstate, from a superposition of eigenstates) is exactly analogous to the phenomenon of trying to pinpoint what one is thinking about at the instant t he is doing such thinking. More often than not, when one does this, as Bohm notes - "uncontrollable and unpredictable changes" are introduced into the thought process or train of thought.
Often, people are heard to say: "Sorry, I've lost my train of thought".
What they really mean is the thought coherence they had enjoyed has since been obliterated, so that they have to commence the thought process anew. The coherent state has "collapsed" into a single state which they now no longer recognize. In this way, as Bohm pointed out, the "instantaneous state of a thought" can be compared to the instantaneous position of a particle (say associated with a de Broglie wave or "B-wave" in a brain neuron). Similarly, the general direction of change of a thought is analogous to the general direction of change in time for the particle's momentum (or by extension, its phase function).
Now, let's get into more details.
From the foregoing remarks (on thought), Bohm - in another work ('Wholeness and the Implicate Order', 1980) could also regard meditation as a possible "channel" by which the individual mind can access the Dirac Ether. I have dealt with similar conjectures before, in terms of the 'quantum potential".
In general, the quantum potential defined by Bohm (ibid.) is:
VQ= { - ħ2/ 2m} [Ñ R]2 / R
Where ħ is the Planck constant of action h divided by 2π , m is the mass, and R a phase amplitude. The quantum potential computed for a pair of Gaussian slits is shown below (cf. Bohm, D. and Hiley, B.J.: Foundations of Physics, Vol. 12, No. 10, p. 1001):
Now assume the total set of one's thoughts contains waves of frequencies ranging from f' (highest) to f, then the empirical quantum potential ( V'Q) can be expressed:
V'Q = h(f' - f),
where h is Planck's constant.
Thus, V'Q has units of energy as the other potential functions in physics, e.g. gravitational and electrostatic. On average, the greater the number of possible states, the greater the difference (f' - f) and the greater the empirical quantum potential.
In a real human brain, of course, we have a "many-particle" field (especially since we're looking at neuronal complexes) so that the quantum potential must be taken over a sum such that:
VQ= { - ħ2/ 2m} å i [Ñ Ri]2 / R
The velocity of an individual B-wave is expressed by:
v(B)= Ñ S/ m
Where m is the mass of the particle associated with the B-wave, and S is a phase function obtained by using:
U = R exp( iS/ħ)
A neuron in sub-complex 'A' either fires or not. The 'firing' and 'not firing' can be designated as two different quantum states identified by the numbers 1 and 2. When we combine them together in a vector sum diagram, we obtain the superposition.
Y (n ( A] = Y (n1 ( A1] + Y (n1 ( A2)]
where the wave function (left side) applies to the collective of neurons in 'A', and takes into account all the calcium wavepackets that factored into the process. What if one has 1,000 neurons, each to be described by the states 1 and 2? In principle, one can obtain the vector sum as shown in the above equation for all of the neuronal sub-complex A, and combine it with all the other vector sums for the sub-complexes B, C, D and E in an optimized path. The resulting aggregate vector sum represents the superposition of all subsidiary wave states and possibilities in a single probability density function. Configure the action of Pauli spin gates as well, and radical emergence is allowed, of the type that could even account for the effects reported by Robert Jahn (from his students) on computer random number generators.
VQ= { - ħ2/ 2m} [Ñ R]2 / R
Where ħ is the Planck constant of action h divided by 2π , m is the mass, and R a phase amplitude. The quantum potential computed for a pair of Gaussian slits is shown below (cf. Bohm, D. and Hiley, B.J.: Foundations of Physics, Vol. 12, No. 10, p. 1001):
Now assume the total set of one's thoughts contains waves of frequencies ranging from f' (highest) to f, then the empirical quantum potential ( V'Q) can be expressed:
V'Q = h(f' - f),
where h is Planck's constant.
Thus, V'Q has units of energy as the other potential functions in physics, e.g. gravitational and electrostatic. On average, the greater the number of possible states, the greater the difference (f' - f) and the greater the empirical quantum potential.
In a real human brain, of course, we have a "many-particle" field (especially since we're looking at neuronal complexes) so that the quantum potential must be taken over a sum such that:
VQ= { - ħ2/ 2m} å i [Ñ Ri]2 / R
The velocity of an individual B-wave is expressed by:
v(B)= Ñ S/ m
Where m is the mass of the particle associated with the B-wave, and S is a phase function obtained by using:
U = R exp( iS/ħ)
A neuron in sub-complex 'A' either fires or not. The 'firing' and 'not firing' can be designated as two different quantum states identified by the numbers 1 and 2. When we combine them together in a vector sum diagram, we obtain the superposition.
Y (n ( A] = Y (n1 ( A1] + Y (n1 ( A2)]
where the wave function (left side) applies to the collective of neurons in 'A', and takes into account all the calcium wavepackets that factored into the process. What if one has 1,000 neurons, each to be described by the states 1 and 2? In principle, one can obtain the vector sum as shown in the above equation for all of the neuronal sub-complex A, and combine it with all the other vector sums for the sub-complexes B, C, D and E in an optimized path. The resulting aggregate vector sum represents the superposition of all subsidiary wave states and possibilities in a single probability density function. Configure the action of Pauli spin gates as well, and radical emergence is allowed, of the type that could even account for the effects reported by Robert Jahn (from his students) on computer random number generators.
The Pauli spin matrix-operator σ x = (0,1¦1,0) where the left pair is a matrix 'top' and each right pair a matrix 'bottom' - since they are usually written in a rectangular array form.
Similarly, the other Pauli gates would be defined by: σ y = (0,-i¦i, 0)and σ z = (1, 0¦0, -1), where i denotes the square root of (-1). Incorporation of such Pauli (quantum) gates meets a primary application requirement for feed forward networks, in describing synapse function. (See e.g. Yaneer Bar-Yam, 'Dynamics of Complex Systems', Addison-Wesley, pp. 298-99.)
The advantage is consciousness is elevated out of the strict machine-like model of an ordinary computer to one that can explain more features of the human experience.
This post is intended to show just how complex the integration of consciousness into an existing, accepted theory of physics can be. Empirically, I don't believe anyone can move forward on this topic until the Pauli spin gates' actions are actually tested via neural networks in the brain. When or how this can happen given our current technology is anyone's guess - but it will likely require actual quantum computers. A first marker may well be the extent to which quantum entanglement might emerge for discrete quantum systems.
See also:
http://brane-space.blogspot.com/2010/07/numerical-testing-of-mlp-network.html
See also:
http://brane-space.blogspot.com/2010/07/numerical-testing-of-mlp-network.html
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