Neural correlates of free will


by Ken G
Tags: correlates, free, neural
apeiron
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Mar8-11, 04:15 PM
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Quote Quote by nismaratwork View Post
How each part adds up to a 'willing' brain, or not, is beyond the ability to extrapolate based on imaging to this point.
My feeling is different having studied precisely this question of how the brain "wills" actions. We already know more than most people could ever want to know.

I would just say pick up Luria's The Working Brain, published in 1973, and read chapter nine. The broad outlines were worked out 50 years ago, and the gaps have been filled in by electrophysiology and animal studies much more than neuroimaging. Read Graybiel on the striatum or Passingham on the frontal lobes for example.

The neural correlates of freewill are one of the "easy problems" even if you are a Chalmer-ite by persuasion. But who really reads neuroscience textbooks?
nismaratwork
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Quote Quote by apeiron View Post
My feeling is different having studied precisely this question of how the brain "wills" actions. We already know more than most people could ever want to know.

I would just say pick up Luria's The Working Brain, published in 1973, and read chapter nine. The broad outlines were worked out 50 years ago, and the gaps have been filled in by electrophysiology and animal studies much more than neuroimaging. Read Graybiel on the striatum or Passingham on the frontal lobes for example.

The neural correlates of freewill are one of the "easy problems" even if you are a Chalmer-ite by persuasion. But who really reads neuroscience textbooks?
I guess wherre you see filled gaps, I see them as bridges to ever widening gaps in our knowledge... we know a lot, but not enough to really explore what the mind is. Well... we can explore, but not in what strikes me as a meaningful way.

Oh, and... nerd that I am, I read them... I read and read them, often for fun. So... that's me... that's a serious bias on my part I guess.
apeiron
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Mar8-11, 04:22 PM
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Quote Quote by Ken G View Post
I would say determinism is quite demonstrably an analysis tool, not a description of how things happen...
Yes, determinism like randomness is in the eye of the beholder . It is how the world looks when it is reduced to its simplest alternatives.

The question then is how do we model complexity. It could be that it is just determinism~randomness made more complicated. Or it could be that in creating the simple model, we left out the "something else" - a story about the global constraints - which is what models of complexity require.
nismaratwork
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Quote Quote by apeiron View Post
Yes, determinism like randomness is in the eye of the beholder . It is how the world looks when it is reduced to its simplest alternatives.

The question then is how do we model complexity. It could be that it is just determinism~randomness made more complicated. Or it could be that in creating the simple model, we left out the "something else" - a story about the global constraints - which is what models of complexity require.
See... this I agree with completely.
Lievo
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Mar8-11, 06:50 PM
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Quote Quote by Ken G View Post
we cannot see that what happens is "deterministic"
Sure, but we can construct models that, by definition, are deterministic, and see what happens. That's exactly what I did: I constructed a deterministic model in which the same kind of problem can arise despite it's neither tied to consciousness nor free will. That says nothing about whether consciousness and free will are or are not determinist. That just shows that determinism is not at the root of the problem while interpreting Libet's finding.

That said, I'm not seeing determinism and randomness as just usefull tricks to guide interpretation. To me this has a precise meaning in terms of theory of computability and theory of complexity. I equate determinism with computabilty, and randomness with BPP class of complexity.

Let's begins with the latter: about everyone thinks that P=BPP, meaning that randomness is unlikely to provide any observable change from a more classical universe (that remains to be proven, however). That's exactly the situation with many-worlds versus Copenhagen interpretation: the first is purely deterministic without randomness, the second uses randomness to a large extent, and it does not make any difference in what we expect to see.

The former is more subtile: yes one will never prove that the universe is computable/determinist. However, the reverse (the universe being uncomputable/non deterministic) is IMHO theorically provable (can you compress most arbitray binary strings? If yes congratulation: you have hypercomputing abilities). So the question, to me, is not whether we can prove that the universe is deterministic. The question is: should we think otherwise when otherwise is such an extraordinary claim? To me extraordinary claims are good to Occamise until we find reasons not to.
apeiron
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Mar8-11, 07:07 PM
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Quote Quote by Lievo View Post
I equate determinism with computabilty, and randomness with BPP class of complexity.
But BPP assumes determinism (the global constraints are taken to be eternal, definite rather than indefinite or themselves dynamic). So no surprise that the results are pseudo-random and Ockham's razor would see you wanting to lop off ontic randomness.

In the short run view, where global constraints by definition look "eternal", this is very valid and useful as a modelling approach. But it does not answer the larger case of the long run view where global contraints may be presumed to vary over time. Even the laws of physics could have evolved.

Real complexity modelling involves allowing the global constraints to develop, to self-organise. It is this intrinsic holistic dynamism that a strictly localised view, based on the standard dichotomy of random vs determined, misses.
Ken G
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Mar8-11, 07:39 PM
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Quote Quote by Lievo View Post
Sure, but we can construct models that, by definition, are deterministic, and see what happens. That's exactly what I did: I constructed a deterministic model in which the same kind of problem can arise despite it's neither tied to consciousness nor free will.
Exactly-- you constructed a model in which the same kind of problem can arise. Does that mean it is what happens in free will? Certainly not, your model does not exhibit free will. That is the Catch-22 in your argument-- you say computers are deterministic, so what they model is deterministic, and then you claim that free will has to be deterministic. But by making a deterministic model, you have not demonstrated free will, and you cannot tell that you have modeled free will. That is my point-- free will may have nothing to do with determinism, neither produced by it nor precluded by it. And none of your models answer that issue. I believe apeiron is making a similar point.

That says nothing about whether consciousness and free will are or are not determinist. That just shows that determinism is not at the root of the problem while interpreting Libet's finding.
All the same, you said that we were talking about a deterministic system when we were talking about the brain. The issue is one of definition-- if by a "deterministic system" one means "a system that we gain limited predictive power by modeling it deterministically", then sure we can say the brain is deterministic. But most people's claims about "deterministic systems" require that the system is deterministic, i.e., it's behaviors are determined in advance, which is a very different claim, and not well substantiated by fact-- any better than fact can substantiate that weather is deterministic. Instead, the most straightforward interpretation of the facts is that it is not-- unless we restrict to the weaker meaning of the term.
I equate determinism with computabilty, and randomness with BPP class of complexity.
Note those are both aspects of models of real systems, not aspects of real systems. The issue here is what evidence you have that your models are successful at modeling free will. What evidence is that?
So the question, to me, is not whether we can prove that the universe is deterministic. The question is: should we think otherwise when otherwise is such an extraordinary claim? To me extraordinary claims are good to Occamise until we find reasons not to.
But it is not an extraordinary claim at all, the more extraordinary claim is that the universe is built to submit to our analysis. More simple is the claim that we tailor our analysis to achieve goals, and the universe is just the universe, and a brain is just a brain. The ultimate irony is when we think that our brains our built to understand how our brains are built.
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Mar8-11, 08:35 PM
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Quote Quote by Ken G View Post
That is the Catch-22 in your argument-- you say computers are deterministic, so what they model is deterministic, and then you claim that free will has to be deterministic.
Are you sure you don't mix-up my argument with those of someone else?

Quote Quote by Ken G View Post
But by making a deterministic model, you have not demonstrated free will, and you cannot tell that you have modeled free will.
Didn't I explicitly said the same things? Again, my analogy says nothing about whether consciousness and free will are or are not determinist. That just shows that none are at the root of the problem while interpreting Libet's finding, because one can explicitly construct the same kind of result while evacuating both free will and determinism.

Quote Quote by Ken G View Post
Note those are both aspects of models of real systems, not aspects of real systems.
I'd say it's mathematical definition. Whatever. What's is important is that from these mathematical definitions we can infer whether this or that properties lead to predictions. If an aspect of the model cannot lead to prediction, then you have the mathematical guarantee that this properties is not important to care about. If it allows some prediction, then you can check reality to decide which kind of model can or cannot describe reality: with or without the property?

Quote Quote by Ken G View Post
The issue here is what evidence you have that your models are successful at modeling free will. What evidence is that?
From the mathematical definition of randomness, an informed guess is that either randomness isn't at the root of free will, or free will can account for nothing. From the mathematical definition of computability, you can infer that either free will is determinist or it allows hypercomputing. So if one find evidence for hypercomputing that'd be evidence against determinism. Notice hypercomputing doesn't mean unpredictability. It means extraordinary abilities. See Penrose for one who defends this line of though, and especially defends that mathematicians have superpowers.

Quote Quote by Ken G View Post
the more extraordinary claim is that the universe is built to submit to our analysis.
Some would disagree.
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nismaratwork
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Science is a method, it's no guarantee that the universe is comprehensible.
Q_Goest
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Hi Ken G,
Quote Quote by Ken G View Post
There is an important difference between a "chaotic system", which is something physical, and chaos theory, which is mathematics. Of course chaos theory is deterministic, the issue is whether or not the physical system is deterministic.
I understand what you're getting at, but chaotic systems are clearly defined as deterministic in the literature as I've quoted above. Yes, they are mathematically deterministic. Are they physically deterministic? When looking at the 'weather' or any other fluid system for that matter, we use statistical mechanics to define the fluid's momentum, density, internal energy, etc... at any point and at any time, and to the degree those values are accurate, the model will make accurate predictions. The fact that a fluid's momentum is made up of an aggregate of molecules and those molecules are being lumped together means that we can never be perfectly accurate. But does that really matter? Does it really matter that after an extended period of time, even our most accurate measurement of the macro states won't provide sufficient detail to define the micro states and thus the sensitivity to initial conditions might again cause a deviation from our model? I suppose one could also argue that given sufficient information about the micro states of molecules in the fluid, one could debatably predict the system with even higher accuracy, though I won't go that far. So are you suggesting that physical determinism isn't possible because we can't know the micro states, or are you suggesting that there might be some kind strong emergence and thus a form of downward causation that subordinates local physical laws? Or are you suggesting such systems aren't deterministic for some other reason?
apeiron
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Mar8-11, 09:00 PM
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Quote Quote by Q_Goest View Post
So are you suggesting that physical determinism isn't possible because we can't know the micro states, or are you suggesting that there might be some kind strong emergence and thus a form of downward causation that subordinates local physical laws? Or are you suggesting such systems aren't deterministic for some other reason?
Have you found time to read this great paper yet?

http://arxiv.org/abs/0906.3507

You will see that Franks makes the argument that it does not matter whether the microscale is ontically random or ontically deterministic because it is the global constraints (the information preserved at the global scale and which acts top-down) which explains the patterns of nature.

We already knew this of course. You can generate fractals either by deterministic iterative equations or suitable stochastic processes. It looks the same in the end as what matters is the information represented as the global constraints.

But Franks makes this explicit. There is a top-down view which is not reducible to the bottom up. The whole is more than the sum of its parts (whether they be random or determined). And this is true even for simple systems (like those with a gaussian, or even simpler(!) powerlaw, statistics). It is of course obviously true for complex systems like life and mind.
Q_Goest
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Hi apeiron,
Quote Quote by apeiron View Post
Chaos is merely an example of the complicated. The global constraints are simple and unchanging (holonomic).

Complexity by contrast involves non-holonomic constraints (as argued by Howard Pattee for example). Top-down causality is qualitatively different when we shift from the holonomic to the non-holonomic case.
I’m not familiar with “holonomic” so I did a search:

"A physical system is defined in terms of a number of degrees of freedom which are represented as variables in the equations of motion. Once the initial conditions are specified for a given time, the equations of motion give a deterministic procedure for finding the state of the systems at any other time. Since there is no room for alternatives in this description, there is apparently no room for hereditary processes. . . The only useful description of memory or heredity in a physical system requires introducing the possibility of alternative pathways or trajectories for the system, along with a 'genetic' mechanism for causing the system to follow one or another of these possible alternatives depending on the state of the genetic mechanism. This implies that the genetic mechanism must be capable of describing or representing all of the alternative pathways even though only one pathway is actually followed in time. In other words, there must be more degrees of freedom available for the description of the total system than for following its actual motion. . . Such constraints are called non-holonomic."

In more common terminology, this type of constraint is a structure that we say controls a dynamics. To control a dynamical systems implies that there are control variables that are separate from the dynamical system variables, yet they must be described in conjunction with the dynamical variables. These control variables must provide additional degrees of freedom or flexibility for the system dynamics. At the same time, typical control systems do not remove degrees of freedom from the dynamical system, although they alter the rates or ranges of system variables. Many artificial machines depend on such control constraints in the form of linkages, escapements, switches and governors. In living systems the enzymes and other allosteric macromolecules perform such control functions. The characteristic property of all these non-holonomic structures is that they cannot be usefully separated from the dynamical system they control. They are essentially nonlinear in the sense that neither the dynamics nor the control constraints can be treated separately.
It sounds like Pattee wants simply wants these macromolecules and genetics to have a stronger causal role in evolution but I'm not sure exactly what he's getting at. Perhaps you could start a new thread regarding Pattee and his contributions to philosophy and science.

Baranger's paper shows he has an intuitive grasp of this, but has not actually studied the subject from a theoretical biology standpoint. So this part of his presentation lack precision.
Sure, Baranger's paper is pretty basic, but it clearly makes the point that chaotic systems are deterministic given precise initial conditions, which is relevant to the OP. I think it’s important also to separate out chaotic systems that are classical (and separable) in a functional sense, such as Benard cells, from systems that are functionally dependant on quantum scale interactions. Our present day paradigm for neuron interactions is that they are not dependent on quantum scale interactions, so it seems to me one needs to address the issue of how one is to model these “non-holomonic” properties (classical or quantum mechanical influences) and whether or not such a separation should make any difference.

I don't follow you here. Perhaps "effects" does seem a too-loose way of talking about global constraints (holonomic or otherwise), but it seems acceptable enough in context. And indeed, it would be exactly the right term if you wanted to draw attention to the crucial systems fact that the top-down action is having an "effect" on the local scale. Because this is the whole point. Top-down constraints do result in something at the local atomistic scale. That is, it creates what is there via its constraint of local degrees of freedom.
This is a good example of what confuses me about everything you say about this "systems approach". Are you suggesting these "top-down constraints" are somehow influencing and subordinating local causation? That is, are you suggesting that causes found on the local level (such as individual neuron interactions) are somehow being influenced by the top down constraints such that the neurons are influenced not only by local interactions, but also by some kind of overall, global configuration? Or are you merely referring to how boundary conditions act as local causal actions at some 'control surface' such as we use in multi-physics approaches that use FEA to model physical phenomena in engineering and the sciences? Note that FEA and similar approaches are simplified versions of the underlying philosophy surrounding the more conventional “systems approach”, that nonlinear differential control volumes must be in dynamic equilibrium over time. It’s this dynamic equilibrium between local causes that might somehow be misconstrued as there being some kind of genuine downward causation which of course, isn’t a mainstream concept. Being an engineer, I’d readily accept that boundary conditions act on any given system, but the underlying philosophy of how those boundary conditions act on any classically defined, separable system, does not allow for nonlocal causation and thus does not allow for downward causation in any real sense of the term.

And likewise, I don't get your crack about epiphenomenal mental states. Farkus argues that the epiphenomal part of it all is that philosophers end up talking about something that does not in fact exist separate from the system.
After rereading his paper, I’d say that he does in fact try to separate mental states (phenomenal states) from the underlying physical states as you say, but that mental states are epiphenomenal isn’t an unusual position for computationalists. Frank Jackson for example (Epiphenomenal Qualia) is a much cited paper that contends exactly that. So I’d say Farkus is in line with many philosophers on this account. He's suggesting mental states ARE physical states, and it is the mental properties that are "causally irrelevant" and an epiphenomenon (using his words) which I’d say is not unusual in the philosophical community. Not that there aren’t logical problems with that approach. He states for example:
The intra-level causation in the brain is argued to simultaneously operate at various levels. At the lowest level (that we consider), a neuron (causally) affects the behavior of another neuron it projects [connects] to. At a somewhat higher spatial level, (activation of a) voxel A in certain brain area affects a voxel B in another brain area, …
That says to me, he accepts that neurons only interact locally with others but we can also examine interactions at higher levels, those that are defined by large groups of neurons.

There are some areas in his paper I’m not too sure about. Take for example:
In medium causation, the higher level entity emerges through a realization of one amongst several possible states on the lower level (their interactions) whereas the previous states of the higher level constrain conditions for the coming higher-level sates.
If he’s suggesting that this “higher level” is not determined by the interactions of the lower level (their interactions) in a deterministic way based only on the local interactions of neurons, then that sounds like strong downward causation which is clearly false. Certainly, there are people who would contend that something like that would be required for “free will” or any theory of mental causation. But I’m not sure that’s really what he wants.

In another questionable section he states:
I think that examples of inter-level causation can be found in the social domain as well. Imagine an audience, having just watched the enjoyable performance. Initially, independent claps are eventually converted into a synchronized applause, which is an example of bottom-up causation. And reversely, imagine yourself entering a classroom submerged into a dense atmosphere that can be “sensed in the air.” You are likely to become immediately affected by this global social state. I suggest that top-down causation can also be viewed as an intra-level causation where many parts simultaneously affect another single part (which differs from sequential, uncoordinated peer-to-peer interactions in the intra-level case).
In the part emphasized, I’d say he’s trying to suggest that a person is somehow “immediately” and “simultaneously” affected by a “global state” on entering this classroom which I picture as being a zone of influence of some sort per Farkus. Were the same person to enter the same room and was blind and deaf, would these same “global states” immediately and simultaneously also affect that person? Sounds like Farkus wants his readers to believe that also, but that sounds too much like magic to me.

I suspect that the punchline to all this is that the proposal these folks are after is that higher order levels influence the future higher order levels by influencing lower order levels. That of course is strong downward causation. I don't see any room for a 'medium' causation that somehow doesn't allow a higher level to influence a lower level but still allows higher levels to have some kind of influence. The higher level is made up of lower level constituents, so if there's no change in the lower level constituents caused by the higher level, there's no change.

I think this is a good lead in to strong emergence and strong downward causation which, in one way or another, is necessary for mental causation and free will. The question really is, can the higher physical levels somehow subordinate the local interactions of neurons? And if so, how?
Ken G
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Mar8-11, 10:32 PM
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Quote Quote by Lievo View Post
Are you sure you don't mix-up my argument with those of someone else?
I did conflate your argument with Q_Goest, my apologies.
Didn't I explicitly said the same things? Again, my analogy says nothing about whether consciousness and free will are or are not determinist. That just shows that none are at the root of the problem while interpreting Libet's finding, because one can explicitly construct the same kind of result while evacuating both free will and determinism.
Yes, and I agree with you-- Libet's finding really doesn't say much about free will at all, it says something about how we come under the conscious impression of having free will. That might be something quite a bit different from free will, just as the conscious impression of getting burned by a stove is quite a bit different from the process of burning. I should not have taken issue with your comments, I think we are largely in agreement.
What's is important is that from these mathematical definitions we can infer whether this or that properties lead to predictions. If an aspect of the model cannot lead to prediction, then you have the mathematical guarantee that this properties is not important to care about. If it allows some prediction, then you can check reality to decide which kind of model can or cannot describe reality: with or without the property?
Yes, I agree, the purpose of the mathematics is to empower the predictions, not to identify the actual process. In fact, I would say the express purpose of a mathematical model is to replace the actual process with something that fits inside our heads. For some reason, this replacement often gets misconstrued as a complete description, missing the point that the whole purpose was not to provide a complete description.
From the mathematical definition of randomness, an informed guess is that either randomness isn't at the root of free will, or free will can account for nothing. From the mathematical definition of computability, you can infer that either free will is determinist or it allows hypercomputing
No, this is the point, no mathematical definition can tell you something about free will other than whether or not the mathematical definition is a useful replacement for free will. It certainly can't tell you if free will is determinist, unless one adopts the weak meaning that anything that is usefully replaced by a determinist model is what we mean by "deterministic" when applied to a real thing.

So if one find evidence for hypercomputing that'd be evidence against determinism. Notice hypercomputing doesn't mean unpredictability. It means extraordinary abilities. See Penrose for one who defends this line of though, and especially defends that mathematicians have superpowers.
An interesting tack, but all too easy to say, "according to the mathematician." An artist might say that artists have superpowers. My point here is only that there is no need to find evidence against determinism, the responsibility lies squarely on those who claim that determinism has something to do with free will, either for or against, to demonstrate that property.
Ken G
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Mar8-11, 10:42 PM
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Quote Quote by Q_Goest View Post
I understand what you're getting at, but chaotic systems are clearly defined as deterministic in the literature as I've quoted above.
But you see the error there right away, the word "defined" is inconsistent with the word "system." We don't define systems, we notice them. What we define are mathematical models of systems, but a model is never a system. If the literature is being lazy on this point, then it is really missing something important, perhaps along the lines of what apeiron is saying it is missing.

Yes, they are mathematically deterministic.
No, systems are not mathematically deterministic, because systems are not mathematics.
Are they physically deterministic?
That's the issue.
When looking at the 'weather' or any other fluid system for that matter, we use statistical mechanics to define the fluid's momentum, density, internal energy, etc... at any point and at any time, and to the degree those values are accurate, the model will make accurate predictions. The fact that a fluid's momentum is made up of an aggregate of molecules and those molecules are being lumped together means that we can never be perfectly accurate. But does that really matter?
That's indeed the question. Or the follow-on question, does it matter to whom, and in what way? I would say it all depends on the goals. I think those who make models sometimes seem to forget that they are making models for a reason, they have a goal, and that goal is never to describe completely that which they model, for a complete description is not a model at all, it is only the system itself.

So are you suggesting that physical determinism isn't possible because we can't know the micro states, or are you suggesting that there might be some kind strong emergence and thus a form of downward causation that subordinates local physical laws? Or are you suggesting such systems aren't deterministic for some other reason?
I'm suggesting that determinism is itself a construct, a mathematical idea, not necessarily applicable to real systems except that it makes a useful template to hold up to them-- just as all mathematical models of reality are useful templates. That's easy to state, but the issue in regard to free will is that we don't yet know what elements of free will we are even trying to model, so we cannot say whether or not determinism is a useful template to hold up to free will. We already have examples, in weather and in quantum mechanics, where determinism is not always a useful template, though it does have some applicability and some tendency to break down.
Pythagorean
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Mar8-11, 11:04 PM
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Q_Goest,

"Not quantum" doesn't mean classical. Nonlinear dynamics and complex systems are modern physics; in my undergrad curriculum they are taught in the two-semester modern physics course, after quantum and relativity.

They do make use of classical physics (moreso than QM does, for instance) but they are not constrained by classical physics, especially because they allow for dissipative (and stochastic) processes.

Dissipiative processes in thermodynamics are irreversible. Moving through a conservative force, like gravity, your can completely recover your ground... in the real world we have friction: a dissipative process from which heat and entropy flow.

This all becomes very important in turbulence models, where heat dissipation and entropy are rampant among correlated deterministic behavior (and change the deterministic behavior that is chaotic, so it's hard to predict how small, random changes from heat dissipation can manifest large consequences)

On stochastic non-holonomic systems
N. K. Moshchuk and I. N. Sinitsyn
Journal of Applied Mathematics and Mechanics
Volume 54, Issue 2, 1990, Pages 174-182

CUMULANTS OF STOCHASTIC RESPONSE FOR A CLASS OF
SPECIAL NONHOLONOMIC SYSTEMS
Shang Mei and Zhang Yi
Chinese Physics
Vol 10 No 1, January 2001
nismaratwork
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Quote Quote by Pythagorean View Post
Q_Goest,

"Not quantum" doesn't mean classical. Nonlinear dynamics and complex systems are modern physics; in my undergrad curriculum they are taught in the two-semester modern physics course, after quantum and relativity.

They do make use of classical physics (moreso than QM does, for instance) but they are not constrained by classical physics, especially because they allow for dissipative (and stochastic) processes.

Dissipiative processes in thermodynamics are irreversible (that is one of the physical meanings of non-holonomic). Moving through a conservative force, like gravity, your can completely recover your ground... except for in the real world we have friction: a dissipative process.

This all becomes very important in turbulence models, where heat dissipation and entropy are rampant among correlated deterministic behavior (and change the deterministic behavior that is chaotic, so it's hard to predict how small, random changes from heat dissipation can manifest large consequences)

On stochastic non-holonomic systems
N. K. Moshchuk and I. N. Sinitsyn
Journal of Applied Mathematics and Mechanics
Volume 54, Issue 2, 1990, Pages 174-182

CUMULANTS OF STOCHASTIC RESPONSE FOR A CLASS OF
SPECIAL NONHOLONOMIC SYSTEMS
Shang Mei and Zhang Yi
Chinese Physics
Vol 10 No 1, January 2001
Nonlinar dynamics includes nonlinear optics, right? (just clarifying for me here, not a leading question.)
Ken G
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Mar8-11, 11:26 PM
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My point about nonlinear dynamics in general is that it starts with a kind of fiction, which is that the system has "a state." Mathematically, if we have nonlinear dynamics, and start at a state, we have deterministic evolution that obeys sensitivity to initial conditions. However, if we don't actually have a state, but instead a collection of states, involving some uncertainty, then our initial uncertainty grows with time. Mathematically, we would still call that deterministic, because we have a bundle of deterministic trajectories that fan out and cover most or all of the accessible phase space. But physically, if we have an initial uncertainty that grows, we cannot call that deterministic evolution, because we cannot determine the outcome. Hence, if we cannot assert that the reality begins in "a state", we cannot say that its future is determined either. Rather, we see determinism for what it is-- a gray scale of varying degree of predictability, not an absolute state of how things evolve.

The Catch-22 of chaotic systems is we cannot demonstrate that the system does begin in a state other than a state of uncertainty, nothing else is actually demonstrable. It is purely a kind of misplaced faith in a mathematical model that tells us a macroscopic system actually has a state. Even quantum mechanically, a macro system is treated as a mixed state, which is of course not distinguishable from an uncertain state (and here I do not refer to the Heisenberg uncertainty of pure states, but the garden variety uncertainty of mixed states).
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Mar9-11, 12:57 AM
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Quote Quote by Q_Goest View Post
I’m not familiar with “holonomic” so I did a search:

It sounds like Pattee wants simply wants these macromolecules and genetics to have a stronger causal role in evolution but I'm not sure exactly what he's getting at. Perhaps you could start a new thread regarding Pattee and his contributions to philosophy and science.
Given that Pattee is an excellent cite for the systems view, this is certainly the right place to mention him .

What he is talking about here is the symbol grounding issue - how non-holonomic constraints can actually arise in the natural world. Genetic information has to make itself separate from what it controls to be able to stand as a level of top-down control.

Sure, Baranger's paper is pretty basic, but it clearly makes the point that chaotic systems are deterministic given precise initial conditions, which is relevant to the OP.
That was hardly the thrust of the paper. And the more correct statement is that chaotic systems (such as the weather) can be modelled using the mathematical tools of deterministic chaos. This is different from the claim that the weather, or any other system is deterministically chaotic in the ontic sense.

So sure, the models behave a certain way - unfold mechanistically from their initial conditions. And it certainly resembles the observables of real world systems like the weather. But we also know that the models depend on unrealistic assumptions (such as a real world ability to measure initial conditions with complete accuracy).

From a philosophical view, you just can't jump from "looks like" to "is". Especially when you know there are ways that "it isn't".

I think it’s important also to separate out chaotic systems that are classical (and separable) in a functional sense, such as Benard cells, from systems that are functionally dependant on quantum scale interactions. Our present day paradigm for neuron interactions is that they are dependent on quantum scale interactions, so it seems to me one needs to address the issue of how one is to model these “non-holomonic” properties (classical or quantum mechanical influences) and whether or not such a separation should make any difference.
Pardon me? Did you just suggest that a QM basis to neural function was mainstream?

This is a good example of what confuses me about everything you say about this "systems approach". Are you suggesting these "top-down constraints" are somehow influencing and subordinating local causation? That is, are you suggesting that causes found on the local level (such as individual neuron interactions) are somehow being influenced by the top down constraints such that the neurons are influenced not only by local interactions, but also by some kind of overall, global configuration?
What I've said is that global constraints act top-down to restrict local degrees of freedom. So that in a strong sense does create what is there are the local scale. Of course the logic is interactive. It is a systems approach. So the now focused degrees of freedom that remain must in turn construct the global scale (that is making them).

This is how brains work. A neuron has many degrees of freedom. A particular neuron (in a baby's brain, or other unconstrained state) will fire to just about anything. But when a global state of attention prevails, the firing of that neuron becomes highly constrained. It becomes vigorous only in response to much more specific inputs. This is a very basic fact of electrophysiology studies.

So it is not just a theory, it is an observed fact. And yes, this is not the way machines work in general.

After rereading his paper, I’d say that he does in fact try to separate mental states (phenomenal states) from the underlying physical states as you say, but that mental states are epiphenomenal isn’t an unusual position for computationalists. Frank Jackson for example (Epiphenomenal Qualia) is a much cited paper that contends exactly that. So I’d say Farkus is in line with many philosophers on this account. He's suggesting mental states ARE physical states, and it is the mental properties that are "causally irrelevant" and an epiphenomenon (using his words) which I’d say is not unusual in the philosophical community.
I'm not holding up the Farkus paper as a shining example of the systems view. As I made plain, it was just what I happened to be reading that day and my remark was here is another reinventing the wheel.

But I think you are also reading your own beliefs into the words here.

Not that there aren’t logical problems with that approach. He states for example:

That says to me, he accepts that neurons only interact locally with others but we can also examine interactions at higher levels, those that are defined by large groups of neurons.
I don't see the issue. This is the standard view of hierarchy theory. Except you introduced the word only here to suggest Farkus meant that there are not also the local~global interactions that make the brain a system.

There are some areas in his paper I’m not too sure about. Take for example:

If he’s suggesting that this “higher level” is not determined by the interactions of the lower level (their interactions) in a deterministic way based only on the local interactions of neurons, then that sounds like strong downward causation which is clearly false. Certainly, there are people who would contend that something like that would be required for “free will” or any theory of mental causation. But I’m not sure that’s really what he wants.
What he says is that you have two things going on. The higher level has a long-run memory which causes what we might call its persistent state. Then it is also responding to the input coming from below, so its state is also "caused" by that.

If you dig out Stephen Grossberg's neural net papers, or Friston's more recent Bayseian brain papers, you will get a much more elegant view. Yet one with the same essential logic.

In another questionable section he states:

In the part emphasized, I’d say he’s trying to suggest that a person is somehow “immediately” and “simultaneously” affected by a “global state” on entering this classroom which I picture as being a zone of influence of some sort per Farkus. Were the same person to enter the same room and was blind and deaf, would these same “global states” immediately and simultaneously also affect that person? Sounds like Farkus wants his readers to believe that also, but that sounds too much like magic to me.
Surely he is just using an analogy and not suggesting that psi is involved . Why would his explicit claim that a person "senses" the atmosphere be read instead as a claim that a person who could not sense (being blind and deaf) would still sense?

All he is saying is that there is an ambient emotional state in the classroom - a generally shared state averaged across a connected set of people. Any newcomer then will respond to this globally constraining atmosphere.

I think this is a good lead in to strong emergence and strong downward causation which, in one way or another, is necessary for mental causation and free will. The question really is, can the higher physical levels somehow subordinate the local interactions of neurons? And if so, how?
Excellent. But there are so many thousands of papers on the neuroscience of top-down attentional effects on neural receptive fields that it is hard to know where to start.

Here is a pop account with some useful illustrations.
http://www.sciencedaily.com/releases...0325132326.htm

Here is a rather general review.
http://pbs.jhu.edu/bin/q/f/Yantis-CDPS-2008.pdf


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