Does Neuroscience Challenge the Existence of Free Will?

[Ken G]

A recent thread on free will did not meet the criteria of the forum, but perhaps a similar discussion could be generated by borrowing directly from the example in the rules:
"The research of Benjamin Libet suggests that our decisions to act occur before our conscious awareness of them. Isn't this a serious problem for the idea of free will?
http://en.wikipedia.org/wiki/Benjamin_Libet". Specifically, does this imply an either/or battle between determinism and free will?

One might try adopting the approach that the neurological correlates of free will are deterministic (if one does wish to adopt a kind of dualistic picture where all that is physical is deterministic and free will is housed in some extra-physical seat of conscious choice). To summarize, Libet's research, and a host of follow-on studies of various kinds, suggest that when you look at the neural correlates of consciousness, as they have been identified (a tricky business in itself but the only one that neuroscience can access directly), you typically find that the experience of consciousness is a rather slow process, compared to the timescales on which we sometimes have to make (split second) choices that nevertheless are considered "conscious", albeit "snap", decisions. Does this mean that a decision we must make rapidly, say a life-or-death choice about whether to jump into a river to save someone, are not things we can attribute to free will, when a more long-term decision (like who to marry) might be?

That might be an interesting issue, to try to draw the line between what is "conscious" and what is just "instinct", but personally, I would look in a different direction-- I would look critically at the very assumption that physically identifiable processes are deterministic in some "absolutely true" way, such that they could preclude a concept of free will. Instead, determinism is a model, just like all scientific concepts. It was never intended to describe how reality actually is, and it is never used for that.

Instead, the model of determinism is applied to making predictions about outcomes, and in some situations, we know this model leads to good predictions, and in others, it has more limited success. For example, determinism in weather prediction leads to the fairly absurd concept that a butterfly can "change the weather", when a much more natural conclusion is that the butterfly is schooling us in the limitations of deterministic thinking. And in quantum mechanics, that which is deterministic is a process that does not lead to definite predictions, such that the outcomes of experiments are not in fact determined, are are of uknown determinism at best. I feel these should all be taken as a cautionary tale about the fundamental incorrectness of the equation physical = deterministic.

So in this sense, I would agree that there is something fundamental in how we do science that requires the determinstic model, but I disagree that this means we know the universe itself evolves deterministically-- rather, our scientific understanding of the universe involves placing the template of determinism against the universe, so a deterministic universe is what we get-- with all its blind spots. The deterministic approach produces a powerful, but the evidence is, an incomplete, way to think about things, as per the chaos and quantum mechanics examples.

 

[apeiron]

It would be great if people could actually discuss freewill in the light of what is actually known about the neurology of choice making and the focusing of action plans, rather than applying the lens of reductionist physics. All the philosophical conundrums would rapidly vanish.

But if people want to debate in terms of universals, or mathematical constructs, then a good place to start is recognising that determined~random are two extremes of a spectum of constraint. Determined is to be locally constrained in some regard. Random is to be unconstrained in that regard.

There is then a third story - that of complexity. Here you have a systems view, rather than the reductionist's view, where there is a self-organising, equilbrium-seeking, interaction between global constraints and local degrees of freedom.

This is what the standard reductionist dichotomy (of determined vs random) cannot see. By only viewing causality as a local issue, the global or holistic aspects are missed (or treated as merely "emergent", epiphenomenal even).

So the whole freewill debate - which has been run through 1000s of times on PF - is motivated by a "too simple" reductionist view of reality. One that really works for physics, but does not work for neurology or the other sciences of the complex.

And anyone who is actually forced to study the neurology will quickly realize this.

As to focusing on Libet, his evoked potential approach is easily misinterpreted as it tells you so little about what is actually happening in the brain (it just says something happens ahead of the time it becomes reportable - but we knew that from psychology's very first experiments conducted by Wundt on perception/aperception).

As a laugh, here is an example of the current literature where you can see the kind of detail people are having to get into to explain the brain as a system that develops its actions.

How choice modifies preference: neural correlates of choice justification.
Qin J, Kimel S, Kitayama S, Wang X, Yang X, Han S.

Department of Psychology, Peking University, Beijing, People's Republic of China.

Abstract
When making a difficult choice, people often justify the choice by increasing their liking for the chosen object and decreasing their liking for the rejected object. To uncover the neural signatures of choice justification, we used functional magnetic resonance imaging to monitor neural activity when subjects rated their preference for chosen and rejected musical CDs before and after they made their choices. We observed that the trial-by-trial attitude change (i.e., increase of preference for chosen items and decrease of preference for rejected items) was predicted by post-choice activity in the ventral medial prefrontal cortex (MPFC), right temporal-parietal junction, anterior insula, and bilateral cerebellum. Furthermore, individual difference in choice justification (i.e., increased preference for chosen items minus decreased preference for rejected items) was predicted by post-choice neural activity in the dorsal MPFC, left lateral prefrontal cortex, and right precentral cortex positively. In addition, interdependent self-construal was correlated with decreased activity in the ventral MPFC in the post-choice than pre-choice sessions. These findings suggest that both negative arousal/regulation and self-reflection are associated with choice justification. This provides evidence for the self-threat theory of choice justification.

 

[Ken G]

I agree with your points about the limitations of the determined vs. random dichotomy. Often a debate on free will seems focused on that dichotomy, as if either was directly relevant (it's not even obvious which one provides more room for free will-- determinism is usually seen as anathema to free will, which then implies randomness somehow supports it, but of course we would always hold a person more responsible for a decision that emerged from the constraints of their persona more so than something they did at random). I'm sypathetic to the claim that free will and conscious choice may require a different analysis than reductionism.

 

[apeiron]

I'm sypathetic to the claim that free will and conscious choice may require a different analysis than reductionism.

Well let's see if there are any takers for a non-reductionist discussion for a change .

 

[Q_Goest]

Hi Ken,

Instead, the model of determinism is applied to making predictions about outcomes, and in some situations, we know this model leads to good predictions, and in others, it has more limited success. For example, determinism in weather prediction leads to the fairly absurd concept that a butterfly can "change the weather", when a much more natural conclusion is that the butterfly is schooling us in the limitations of deterministic thinking.

I think what you're trying to suggest is that chaotic systems might not be fully deterministic, but that's not true. They are.

Chaos theory is a field of study in applied mathematics, with applications in several disciplines including physics, economics, biology, and philosophy. Chaos theory studies the behavior of dynamical systems that are highly sensitive to initial conditions; an effect which is popularly referred to as the butterfly effect. Small differences in initial conditions (such as those due to rounding errors in numerical computation) yield widely diverging outcomes for chaotic systems, rendering long-term prediction impossible in general.[1] This happens even though these systems are deterministic, meaning that their future behavior is fully determined by their initial conditions, with no random elements involved.[2] In other words, the deterministic nature of these systems does not make them predictable.[3][4] This behavior is known as deterministic chaos, or simply chaos.

Ref: http://en.wikipedia.org/wiki/Chaos_theory
Baranger wrote a decent paper covering the various concepts of chaos and complexity called "Chaos, Complexity, and Entropy, A physics talk for non-physicists" that you might be interested in. About the "butterfly effect" or more appropriately, "sensitivity to initial conditions" he states:

A system who's configuration is capable of changing with time is known as a "dynamical system". A dynamical system consists of some "variables" and some "equations of motion" or "dynamical equations". The variables are any things which can vary with time. They can be multiple or single, continuous or discrete. They must be chosen in such a way that complete knowledge of all the variables determines uniquely the "state" of the system at one time. In other words, two similar systems with the same values of all the variables are in identical configurations now, and will evolve identically.

Ref: http://www.necsi.edu/projects/baranger/cce.pdf

So regardless of whether or not a system can be called chaotic, complex, nonlinear or whatever, at least given classical mechanical models, those systems evolve deterministically over time. A computer system for example, such as the one sitting on your desk, is utterly deterministic. Even random number generators in these machines are not random, but only pseudo-random, using 'environmental' cues to create seemingly random outputs. If classical mechanics governs mental 'decisions' then 'free will' (or perhaps more appropriately, "mental causation" which is the concept that phenomenal mental states have an influence over physical states) is false. There is no "downward causation" in the sense that locally efficient causes can be subordinated by global physical states.

The takeaway from all that is generally that mental causation, including free will, is epiphenomenal. A paper quoted by https://www.physicsforums.com/showthread.php?t=471841&page=3" (Farkus, "Mental Causation in a Physical Brain") for example, suggests:

I will defend and discuss the following claims: ... (4) the physical world is causally closed, rendering the mental causation epiphenomenal, ...
[and concludes with]
Since mental properties are claimed to lack causal power, mental causation is in conventional philosophical sense to be treated as a convenient metaphor and it can only refer to the top-down effects in the brain. It is also argued that the lack of causal power does not diminish the ontological importance of mental properties ...

In this case, "top-down effects" should not be confused with "downward causation". Not sure why apeiron suggests mental causation isn’t epiphenomenal since he’s quoted this paper as being the “systems approach”. Perhaps he can help explain what that really means. Regardless, it would seem that if our expectation of the brain is that of a chaotic, complex system that operates as we understand it today (ie: through the classical interaction of neurons) then the brain is deterministic as would be "free will".

 

[apeiron]

So regardless of whether or not a system can be called chaotic, complex, nonlinear or whatever, at least given classical mechanical models, those systems evolve deterministically over time.

Conflating complexity and complication is precisely where reductionists get it wrong.

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.

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.

In this case, "top-down effects" should not be confused with "downward causation". Not sure why apeiron suggests mental causation isn’t epiphenomenal since he’s quoted this paper as being the “systems approach”.

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.

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.

So if you say "mental state" and I say "non-holonomic constraint", or even "top-down effects", only one of us is speaking the language of systems science. The other is stuck with the epiphenomenalism that is "solved" only by ontological dualism.

 

[JoeDawg]

A recent thread on free will did not meet the criteria of the forum, but perhaps a similar discussion could be generated by borrowing directly from the example in the rules:
"The research of Benjamin Libet suggests that our decisions to act occur before our conscious awareness of them. Isn't this a serious problem for the idea of free will?

No. All it really tells us, is that the decision making process is distinct from the self-reflective process. It actually makes sense that the latter would require more processing. Compare how much more difficult it is to learn to drive a car... than it is to drive one after you have learned. In the former case, you have to 'be aware' of everything you are doing. In the latter, your decisions seem 'more unconscious', even though a truly unconscious driver would be in a lot of trouble. The real problem is that the conscious/unconscious dichotomy is overly simplistic. We're only scratching the surface of what consciousness actually is, so this is not surprising.

 

[octelcogopod]

I agree with Joe about the conscious/unconscious dichotomy. I think there is a problem of what awareness and sensory stimuli (qualia) is, but I also think there is a whole lot of confusion as to what a conscious action is, how humans make a choice, and just what it means to be able to think but not able to control ones brain directly in any way. It's very hard to define what choice is, how one makes a choice, and what control is in terms of the influence a conscious mind might have on physical brain states.

I do think on some fundamental level that if everything is determined that the mind doesn't really have any true choice, but the problem then becomes the question of what other choices would we have that would truly be free? The mind is by definition limited to the choices it can see, and those choices are limited by the physical opportunities presented, no matter how free the mental mind might be.

 

[nismaratwork]

Exploring free will from the perspective of modern neurology is a bit like trying to divine character traits via Phrenology... "scratching the surface" is generous IMO.

 

[Lievo]

I would look critically at the very assumption that physically identifiable processes are deterministic in some "absolutely true" way, such that they could preclude a concept of free will.

Suppose an single-vote election design to elect one of two candidates. Let's modify slightly the usual rules so that a randomly chosen schedule determine when each voter will have access to the polling station. Suppose also that there is 10⁸ voters. Finally suppose two hidden observers who have prior access to either the first 10⁵ ballots or the next 10⁵ ones.

In this example free will is what makes each voter decide on way or the other, consciousness is the public outcome publicised after the end of the pool, and everything in between is purely deterministic.

Because of the law of large numbers, there is no doubt that the hidden observers will be able to predict the outcome of the election, despite they look at only 0.1% of the individual ballots. Is it to say that the decision is taken by only 0.1% of the individuals? Of course not: the two observers does not even look at the same ballots, but both can predict the outcome.

What Libet showed is that one can predict the outcome of a decision before the decision becomes consciouss.* The shortcome is not with determinism. The short come is to equate decision with the ability to predict the decision.
*for the sake of clarity I lay aside the usual issues about this claim

 

[nismaratwork]

In other words, true uncertainty vs. measurement problems?

 

[apeiron]

Exploring free will from the perspective of modern neurology is a bit like trying to divine character traits via Phrenology... "scratching the surface" is generous IMO.

How so when the previous two posters raised a crucial distinction between attentional control and automatic or habitual behaviour. And you can go straight to your neurology textbooks to learn in intricate detail about the way the brain handles the two so that it no longer seems a mystery.

 

[nismaratwork]

How so when the previous two posters raised a crucial distinction between attentional control and automatic or habitual behaviour. And you can go straight to your neurology textbooks to learn in intricate detail about the way the brain handles the two so that it no longer seems a mystery.

I find it mysterious because those distinctions don't always hold, and we know from observation that greater complexity exists... it's just an approximation of those intricacies. I'd add, for all the mapping that's done, the interactive and adaptable nature of the brain continues to stymie, and when you touch on consciousness and tne mind... yech.

I love neurology, but it has limits in terms of what is being looked for or screened during imaging, and the tendency to hyperfocus on one system.

Hell, we could probably debate all day about what constitutes the Limbic system... it's too messy for my tastes.

 

[apeiron]

I find it mysterious because those distinctions don't always hold, and we know from observation that greater complexity exists...

What are you thinking of here? Broadly I believe the attention~habit dichotomy holds up pretty well.

The striatum can "emit" learned behaviours in a habitual fashion in time frame of 120 to 250ms, the cortex can "evolve" novel states of response in 300 to 700ms. The distinction in terms of architecture, time frames, and processing logic looks robust.

Though I would agree there is a third level of responding probably in the reflexive - responses evolved over genetic timescales, such as all the brainstem and spinal level stuff (with time frames of 30 to 100 ms). And mostly very resistant to any learning, or top-down higher brain constraints.

The limbic brain is a pretty useless construct when it comes to the brain's architecture I agree. I prefer understanding the "emotional" aspects of the brain in terms of orienting responses.

But the thread is about the "willing centre" of the brain . And that becomes a bit of a laugh in the literature. Ohh, we can see the anterior cingulate light up, the nucleus accumbens, the insular cortex, the DPFC. When actually the whole brain is the willing organ - and divides according to grades of willing from the reflexive, to the habitual, to the "conscious" or attentive.

And all these grades are consciously reportable (if we learn to attend to them), but not so easily consciously controlled (because reflexes and habits are not meant to be attentively controlled by definition - that is just a mistaken cultural belief fostered by the socially constructed notion of freewill).

 

[nismaratwork]

What are you thinking of here? Broadly I believe the attention~habit dichotomy holds up pretty well.

The striatum can "emit" learned behaviours in a habitual fashion in time frame of 120 to 250ms, the cortex can "evolve" novel states of response in 300 to 700ms. The distinction in terms of architecture, time frames, and processing logic looks robust.

Though I would agree there is a third level of responding probably in the reflexive - responses evolved over genetic timescales, such as all the brainstem and spinal level stuff (with time frames of 30 to 100 ms). And mostly very resistant to any learning, or top-down higher brain constraints.

The limbic brain is a pretty useless construct when it comes to the brain's architecture I agree. I prefer understanding the "emotional" aspects of the brain in terms of orienting responses.

But the thread is about the "willing centre" of the brain . And that becomes a bit of a laugh in the literature. Ohh, we can see the anterior cingulate light up, the nucleus accumbens, the insular cortex, the DPFC. When actually the whole brain is the willing organ - and divides according to grades of willing from the reflexive, to the habitual, to the "conscious" or attentive.

And all these grades are consciously reportable (if we learn to attend to them), but not so easily consciously controlled (because reflexes and habits are not meant to be attentively controlled by definition - that is just a mistaken cultural belief fostered by the socially constructed notion of freewill).

Certainly that is the prevailing view, but I suspect that as you say, the combined action of numerous systems gives rise to the possibility of will, conscious or otherwise. When and how a behavior is initiated is a part of the answer, but it leaves major gaps that I don't think reflex alone can fill. PTSD is an example of "learned" reflexive behavior IMO, and yet it only begins to make sense once filtered through many of the regions you mentioned earlier.

In short, I'm not arguing for free-will... I'm saying that the whole mess is sufficiently complex that we can't pick it apart yet with scientific tools. This is a time when philosophy, psychology, and biology (in the form of neurology) have to find some kind of uneasy balance. How each part adds up to a 'willing' brain, or not, is beyond the ability to extrapolate based on imaging to this point.

 

[Ken G]

I think what you're trying to suggest is that chaotic systems might not be fully deterministic, but that's not true. They are.

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. How would you show that the chaotic system is deterministic? You cannot, you can only show that the chaotic analysis leads to useful results-- that's no surprise, holding the template of determinism to physical systems has led to many successes, none of which show that the physical system is actually deterministic. Indeed, as I argued above, there is considerable evidence that the physical system is not actually deterministic, and imagining that it is gives us that butterflies change weather. They do not-- instead, weather is fundamentally statistical, and no butterfly changes the statistical tendencies of the outcomes. Determinism is simply a limited concept.

So regardless of whether or not a system can be called chaotic, complex, nonlinear or whatever, at least given classical mechanical models, those systems evolve deterministically over time. A computer system for example, such as the one sitting on your desk, is utterly deterministic.

The computer is built to be deterministic. The weather is not.

Regardless, it would seem that if our expectation of the brain is that of a chaotic, complex system that operates as we understand it today (ie: through the classical interaction of neurons) then the brain is deterministic as would be "free will".

Again, there is no evidence that classical chaotic systems are deterministic, that's just plain not true. How would you show that a chaotic system, a physical system not a theory describing it to some degree of usefulness, is deterministic?

 

[Ken G]

No. All it really tells us, is that the decision making process is distinct from the self-reflective process. It actually makes sense that the latter would require more processing. Compare how much more difficult it is to learn to drive a car... than it is to drive one after you have learned. In the former case, you have to 'be aware' of everything you are doing. In the latter, your decisions seem 'more unconscious', even though a truly unconscious driver would be in a lot of trouble. The real problem is that the conscious/unconscious dichotomy is overly simplistic. We're only scratching the surface of what consciousness actually is, so this is not surprising.

I agree with what you have said here. That's why I tend to see the whole issue of free will as orthogonal to the issue of deterministic vs. random-- the latter are templates we use in reductionists analyses, the former may involve phenomena we are quite far from having much of a handle on.

 

[Ken G]

In this example free will is what makes each voter decide on way or the other, consciousness is the public outcome publicised after the end of the pool, and everything in between is purely deterministic.

I can see where you are coming from on the first two issues, but the basis for the final claim just depends on what one thinks determinism really means. I would say determinism is quite demonstrably an analysis tool, not a description of how things happen (and you might be saying something similar, but then we cannot see that what happens is "deterministic", we can only say what happens admits to useful analysis via determinism). Indeed, when we attempt to use determinism as a literal description of how things happen, it invariably breaks down at some point along the way. Even when we say we are sure an apple will fall when we drop it, we are speaking in terms of probabilities-- it is highly probably the apple will fall, but we don't know that something else could happen we did not expect, like a bomb might go off that blows the apple upward instead. Probability is always an assessment of what you don't know as well as what you do, and determinism is an analysis tool that is intentionally blind to this fact.

Randomness is also an analysis tool-- my point is merely that being able to predict an outcome with high success is an example of the usefulness of the concept of determinism, not an example of a deterministic process. If you decide what movie you will see today, and I know you quite well, I might be able to write in an envelope what you will choose, based on my knowledge of you. That means I can determine your choice with high success rate-- it does not mean you are not exercising free will. The issue of determinism is nothing but predictability, and is quite orthogonal to issues of free will.

What Libet showed is that one can predict the outcome of a decision before the decision becomes consciouss.* The shortcome is not with determinism. The short come is to equate decision with the ability to predict the decision.

Here I would agree with you.

 

[apeiron]

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]

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]

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]

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]

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]

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]

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.

 

[Lievo]

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?

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.

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?

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.

the more extraordinary claim is that the universe is built to submit to our analysis.

Some would http://xkcd.com/54/"

 

[nismaratwork]

Science is a method, it's no guarantee that the universe is comprehensible.

 

[Q_Goest]

Hi Ken G,

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]

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]

Hi apeiron,

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 into 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]

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]

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]

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]

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]

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).