Dynamical Neuroscience: Wiki Article Entry - Input Needed

[rhody]

Interesting discussion pythagorean, atty, and aperion. I have a question regarding the paper, and an observation that leads to a second question at the end. I took the time to read and redline the paper aperion posted in post #76. I would like clarification on page 6, right side, middle of the "Biased competition and attention paragraph":

The most obvious candidates for controlling gain (and implicitly encoding precision) are classical neuromodulators like dopamine and acetylcholine,which provides a nice link to theories of attention and uncertainty75–77

I always thought dopamine and acetycholine were neurotransmitters versus neuromodulators ?

The paper - http://www.fil.ion.ucl.ac.uk/~karl/T...n%20theory.pdf - is a good example here because it tries to unite many models under the one generalised approach. So it weaves in optimal control theory, DST, and other stuff.

I think that whatever theory(s) and model(s) describe how the brain learns, adapts and responds to injury should consider results from experiments done in the past. Specifically, in my posts https://www.physicsforums.com/showpost.php?p=2925375&postcount=25 and https://www.physicsforums.com/showpost.php?p=2971857&postcount=30 from my plasticity thread. Excerpts below, regarding brain maps arranging themselves in topographical order in response to severing nerves and then observing the results experimentally using micro probes after surgery. My point is there is a physical limit in the area of adaptation (thought to be 1 to 2 centimeters, but through experiment observed to be almost one half of an inch !)

Post #25
To make a long story short, a colleague of Merzenich's at Vanderbilt, Jon Kaas, worked with a student, Tim Pons who wondered, was one to two centimeters the limit for plastic change ? I bet some of you can guess where this idea is going, an experiment, right ? But how ? The answer lay in the Silver Springs monkeys, because they alone had spent twelve years without sensory input to their brain maps, Ironically, PETA's interference for all those years had made them increasingly valuable to the scientific community. If any creature had massive cortical reorganization that could be mapped it would be one of them.

All of the monkeys were aging, but two in particular were in very bad heath and close to death. PETA lobbied the NIH to have one, Paul, euthanized. Mortimer Mishkin, head of Neuroscience and chief of the lab of Neuropsychology at NIH, who many years before had inspected Taub's first deafferentation experiment that overturned Nobel Prize winner's Charles Sherrington's reflexological theory. Miskin met with Tim Pons, agreeing that when the monkeys were to be euthanized, a final experiment could be done, one that would hopefully answer Pon's question. This was a brave decision, since Congress was still on record as favoring PETA. For this reason, they left the government out of it and performed it entirely with private funds. The pressure and fear of repercussion was immense. They performed the procedure in four hours, which normally took a whole day to complete. They removed part of the monkey's skull, and inserted 124 electrodes in different spots of the sensory cortex map for the arm, then stroked the deafferentiated arm. As expected, the arm sent no impulses to the electrodes. Then, Pons stroked the monkey's face, knowing that the brain map for the face is right next to the one for the arm. The neurons in the monkey's deafferentiated arm map began to fire, confirming that the facial map had taken over the arm map. As Merzenich had seen in his experiments, when a brain map is unused, the brain can organize itself so another mental function can take over the processing space. Most surprising was the scope of the organization, over a half of an inch ! Holy crap... that to this humble observer is freaking amazing. The monkey was then euthanized. Over the next six months, this experiment was repeated with three more monkeys, with the same results. Taub had proved that reorganization in damaged brains could occur in very large sectors giving hope to those suffering from severe brain injury.

and post #30

Merzenich, Paul, and Goodman wanted to find out when a peripheral nerve is cut, in the process of regeneration, the axons reattach to the wrong nerve. When this happens a person experiences a "false localization" so that touch that should be felt in an index finger is instead felt in the thumb. Up to this time, scientists believed that the signal from the nerve passed to a specific point on a brain map. Merzenich and his team accepted the "Point to Point" model. They set out to document what happened in the brain during the shuffling of nerves. Instead as they laboriously recorded the neuronal brain maps, they discovered that the signals were "topographically arranged" as the brain had unshuffled the signals from the crossed nerves. This insight forever changed Merzenich's life. Second, the topographically arranged maps were forming in slightly different brain areas than had been observed before the nerves were cut.

Fast forward, as time passed and more and more of Merzenich's experiments convinced him beyond a shadow of doubt in his mind and the mind of close associates who conducted brain mapping experiments with him that the brain of his test subjects changed every few weeks in cases where no major injury would disturb the brain maps. Merzenich's rejection of localization in the adult brain ran into predictable stiff opposition. In Merzenich's words, "Let me tell you what happened when I began to declare that the brain was plastic. I received hostile treatment. I don't know how else to put it. I got people saying things in reviews such as, 'This would be really interesting if it could possibly be true, but it could not be.' It was as if I just made it up." His critics believed his experiments were sloppy and that the effects described in the results were uncertain. (Recall for a moment how precise the micro-mapping location and sensitivity signals were early in this post. Obviously, many of Merzenich's critics did not do an unbiased assessment of his research). Torsten Weisel the Nobel prize winner now admits that localization in adulthood is wrong and has gracefully acknowledged in print that he was wrong, and that Merzenich and his teams work ultimately led him and his colleages to change their minds. Remaining hardcore localization people took notice when a Torsten admitted localization was wrong. His admission led to mainstream acceptance of brain plasticity being accepted in mainstream neurological circles. To summarize, localization existed as a tenant of mainstream belief for almost 70 years until proven wrong by Merzenich and his remarkable experiments.

This brings me to tantalizing and as yet unsolved questions. We know that brain maps arrange themselves in topographical order, meaning that the map is ordered as the body itself is ordered. We now know that topographic order appears because many of our everyday activities involve repeating sequences of movement in a fixed order. Second, brain maps work by grouping together events that happen together. The audio cortex is arranged like the keys of a piano, with low notes on one end and high ones on the other. Form follows function in that sounds come together with each other in rising sequence in nature. But what causes the audio cortex to arrange itself this way. Obviously we can see this from testing the audio cortex, but what underlying principle or laws of physics allow this "natural arrangement" to be possible ? And as if that question were not vexing enough, how about this, as we get better at a new skill or task be it motor or mental, individual neurons under observation became more selective with improvement. For instance, the brain map for the sense of touch has a "receptive field", a segment on the skin's surface that "reports" to it. As the monkeys were trained to feel the object, the receptive fields of individual neurons got smaller, firing when only parts of the fingertip touched the object. Thus, despite the fact that the size of the brain map increases, each neuron in the map became responsible for a smaller part of the skin surface, allowing for finer touch discrimination. Overall the map became "more precise". Again begging a deeper question, what underlying as yet not understood principle makes this possible ? Finally to add a third vexing question to this, as the neurons are trained they became most discriminatory, and faster. In one experiment Merzenich and his team trained monkeys to discriminate sound in shorter and shorter spans of time. The trained neurons fired more quickly in response to the faster sound, processed them in shorter time periods, needed less time between firings. Faster neurons ultimately lead to faster thought, because speed is thought to be a crucial component of intelligence. The faster firing signals got "clearer", meaning they tend to synchronize with one another, leading to a stronger signal, they become team players so to speak. A powerful signal has greater impact on the brain. When we want to remember something, it is crucial that we must hear it clearly. Lasting change only occurs in brain maps when the subjects "pay close, undivided to the task at hand".

Sorry for the long winded reiterating sections of my posts, I needed them to lay out my case. Do you believe that any theory(s), model(s) have to account for the observations with Merzenich's Silver Spring monkeys ? His nerve severing experiments and measuring the movement of the brain maps offer compelling evidence and measurable physical limits. These experiments offer hard data (to my knowledge never repeated since Merzenich's original experiments due to the controversy at performing them).

Do you believe that mathematical model(s) and theory(s) must account for and accommodate the areas observed in Merzenich's experiments ? Personally, I do, and value your opinions. The results beg for a logical and hopefully mathematical explanation for them.

BTW. Merry Christmas to all of you...

Rhody...

 

[atyy]

I agree that a mapping system is still a dynamic system, I guess I just don't see the the mapping equation explicitly and I wouldn't know how to analyze this system, but this is probably due to my ignorance. Thinking about metaheuristics though, I kind of arrived at some kind of intuition about the mapping in a dynamical sense.

In my understanding, dynamical systems are basically Markovian systems. They can be divided according to whether their state space and time are continuous or discrete. When both are continuous, a differential geometric approach is possible.

There are 3 sorts of systems that appear to (but don't really) fall outside these systems:
1) control systems - these receive an input that is the "external stimulus" in biology or "external control" in engineering. In the continuous state space and time, the differential geometric approach can be extended through the use of Lie brackets (the standard example is parallel parking).
2) non-Markovian systems - these arise from Markovian systems in which we do not have explicit knowledge of at least one degree of freedom. In some cases, limited aspects of the full Markovian system can be recovered, eg. in the continuous space and time case, where there is an attractor, Ruelle-Takens embedding recovers the attractor topology. A related problem in Engineering is the minimal (dynamical) realization of a linear filter.
3) stochastic systems - these arise from Markovian systems in which we do not have explicit knowledge of the initial conditions or external stimulus.

The following is not a dynamical systems approach, persay, but are methods generally accepted to be necessary for confining the solution space of a dynamical system.

The following book explains metahueristic approaches (in general, not just biology). I find two approaches particularly interesting: exploration and exploitation. I think designing a good AI would require utilizing both, and additionally, the AI program "knowing" when to switch between exploration and exploitation.

Metaheuristics: From Design to Implementation
El-Ghazali Talbi
ISBN: 978-0-470-27858-1

Genetic/evolutionary algorithms are an example of a heuristic approach that steals ideas from nature, particularly the implementation of a stochastic optimization.

Hmmm, is that the same exploration and exploitation as in http://www.ncbi.nlm.nih.gov/pubmed/20410125 ?

I always thought dopamine and acetycholine were neurotransmitters versus neuromodulators ?

Dopamine and acetylcholine are "non-classical" neurotransmitters and are called neuromodulators, because they act on different time scales from the fast "classical" neurotransmitters.

I think that whatever theory(s) and model(s) describe how the brain learns, adapts and responds to injury should consider results from experiments done in the past. Specifically, in my posts https://www.physicsforums.com/showpost.php?p=2925375&postcount=25 and https://www.physicsforums.com/showpost.php?p=2971857&postcount=30 from my plasticity thread. Excerpts below, regarding brain maps arranging themselves in topographical order in response to severing nerves and then observing the results experimentally using micro probes after surgery. My point is there is a physical limit in the area of adaptation (thought to be 1 to 2 centimeters, but through experiment observed to be almost one half of an inch !)Sorry for the long winded reiterating sections of my posts, I needed them to lay out my case. Do you believe that any theory(s), model(s) have to account for the observations with Merzenich's Silver Spring monkeys ? His nerve severing experiments and measuring the movement of the brain maps offer compelling evidence and measurable physical limits. These experiments offer hard data (to my knowledge never repeated since Merzenich's original experiments due to the controversy at performing them).

Do you believe that mathematical model(s) and theory(s) must account for and accommodate the areas observed in Merzenich's experiments ? Personally, I do, and value your opinions. The results beg for a logical and hopefully mathematical explanation for them.

I'm not specifically familiar with which papers deal with the Silver Spring monkeys (Edit: Reading Rhody's quote, the Silver Spring Monkeys were not Merzenich's, but Edward Taub's). However, work by Merzenich such as http://www.ncbi.nlm.nih.gov/pubmed/6725633 and http://www.ncbi.nlm.nih.gov/pubmed/9497289 is generally considered to be implemented by some form of Hebbian learning (change in synaptic strength as a function of correlation between pre and post-synaptic activity). The detailed mathematical description of the learning rule is still unknown because several factors that may be important are experimentally poorly described. One factor is whether it is necessary for the presynaptic neuron to spike before the postsynaptic neuron. Second is the influence of neuromodulators such as dopamine and acetylcholine. Third, the detailed circuitry of the system is unknown and apparently complicated, so which synapses the changes occur at is unknown.

Experiments trying to look at these include:
http://www.ncbi.nlm.nih.gov/pubmed/16423693
http://www.ncbi.nlm.nih.gov/pubmed/16929304
http://www.ncbi.nlm.nih.gov/pubmed/18004384

Theoretical work includes (I'm casting very widely, since these mechanisms may occur throughout the cortex)
http://www.ncbi.nlm.nih.gov/pubmed/11684002
http://www.ncbi.nlm.nih.gov/pubmed/17444757
http://www.ncbi.nlm.nih.gov/pubmed/20573887

BTW. Merry Christmas to all of you...

 

[apeiron]

Do you believe that mathematical model(s) and theory(s) must account for and accommodate the areas observed in Merzenich's experiments ? Personally, I do, and value your opinions. The results beg for a logical and hopefully mathematical explanation for them.

I don't find anything surprising in the evidence of cortical plasticity because the brain is "dynamic" - ie: adaptive - over all scales.

It is only surprising if you presume the brain must be constructed bottom-up out of definite hardware components. And given neurons are built out molecular components like microtubles with a half-life of about 10 minutes, this seems a silly presumption indeed.

 

[Pythagorean]

I suppose my definition of dynamical systems has been rather narrow; I have never worked with systems discretized in time, so it is tough for me to identify them. Are stochastic systems in general, always dynamical systems? I thought it was a more general statement about a probabilistic approach and didn't necessarily require time-evolution considerations.

From atyy's abstract (pertaining to the exploration/exploitation discussion):

This circuit generates song variability that underlies vocal experimentation in young birds and modulates song variability depending on the social context in adult birds.

Yes, this sounds like an example of what I was imaging.

 

[atyy]

I suppose my definition of dynamical systems has been rather narrow; I have never worked with systems discretized in time, so it is tough for me to identify them. Are stochastic systems in general, always dynamical systems? I thought it was a more general statement about a probabilistic approach and didn't necessarily require time-evolution considerations.

Yes, you are right. In general only stochastic systems with an infinite number of variables (one for each time) are considered stochastic dynamical systems. However, it is known that low-dimensional chaotic systems have ergodic attractors that give rise to probabilities (usually called measures)

In the context of neurobiology and Poincare-Izhikevich type analyses, you might be interested in Gutkin and Ermentrout's work on how Poisson-like statistics can be generated.

However, very, very long transients can also masquerade as "attractors" and produce behaviour that is ergodic for all practical purposes: http://www.ncbi.nlm.nih.gov/pubmed/19936316.

Yes, this sounds like an example of what I was imaging.

You may find the background to Leblois et al's work interesting. Xie and Seung present an example of a continuous state and time dynamical rule with stochastic input. The mathematical analysis is hard so they make a heuristic replacement with a continuous state and discrete time system (which I think is non-Markovian) and show that that system does gradient ascent on the reward. Their discrete time rule is very close to the reinforcement learning rules studied in artificial intelligence beginning in the late 1980s, and from which "exploration" and "exploitation" concepts developed (reinforcement learning itself was inspired by even older biology). In addition to Leblois et al's work, you can see this feedback into current work in the models of eg. Fiete and Seung (bird song) or Legenstein et al (brain-machine interfaces). In short: http://chaos.aip.org/resource/1/chaoeh/v21/i3/p037101_s1?view=fulltext&bypassSSO=1 (ok, I admit Crutchfield can be a bit over the top )

 

[atyy]

http://chaos.aip.org/resource/1/chaoeh/v21/i3/p037101_s1?view=fulltext&bypassSSO=1

I put a wrong link there, it should be http://chaos.aip.org/resource/1/chaoeh/v20/i3/p037101_s1?bypassSSO=1.

 

[Pythagorean]

I've actually alway considered computational a subset of dynamical; but I'm not sure about language difference and semantics a lot because everyone in 'complexity' has the same language for different things.

 

[Pythagorean]

(General post following, not based on prior discussion persay, just spirit of thread.)

So, there are seven known bifurcations in dynamical systems. The last one discovered was discovered in the 1990's and it has probably the fanciest name of all the bifurcations, "Blue Sky Cotastrophe".

http://www.scholarpedia.org/article/Blue-sky_catastrophe

So far, I have only seen it used in applications for biological systems; I wonder if it could be a defining feature of life in the spirit of the book Towards a Mathematical Theory of Complex Biological Systems which gives 10 defining characteristics of life to be quantified by mathematics.

 

[atyy]

I've actually alway considered computational a subset of dynamical; but I'm not sure about language difference and semantics a lot because everyone in 'complexity' has the same language for different things.

Let me ask one more question about semantics - these are meaningless - but they are fun!

Do you consider any system of ordinary differential equations a dynamical system, or does the evolution parameter have to represent time?

For example, in the renormalization group, which represents a type of emergence, there are ordinary differential equations. The existence of fixed points of the flow is a typical question (Hollowood, first figure - it will warm your geometric heart). However the evolution parameter is not time, but resolution scale. Would you consider that a dynamical system?

Funnily, in the AdS/CFT correspondence of string theory there seems to be a sort of holographic emergence in which the renormalization group resolution scale becomes a spatial dimension (McGreevy, Fig 1).

So, there are seven known bifurcations in dynamical systems. The last one discovered was discovered in the 1990's and it has probably the fanciest name of all the bifurcations, "Blue Sky Cotastrophe".

http://www.scholarpedia.org/article/Blue-sky_catastrophe

That is very interesting indeed. Is it a sort of intermittency?

A quick google indicates that it is not (Thompson & Stewart, p264). It seems that there's hysteresis in blue sky, but not in intermittency (Medio and Gallo, p171).

 

[Pythagorean]

Do you consider any system of ordinary differential equations a dynamical system, or does the evolution parameter have to represent time?

I've always considered it (possibly incorrectly) a dynamical system as long as the dynamics aren't stagnant. I.e. if the physical solution is steady state or periodic, then it is a system that does not evolve or "go anywhere". If the solutions of the system are chaotic (asymptotic), it is necessarily a dynamical system by this definition.

Of course there's stable chaos and transient chaos, too. Stable chaos isn't real chaos... it doesn't have exponentially diverging perturbations, but it doesn't appear to be steady-state or periodic either so I'd give it the benefit of the doubt. Transient chaotic systems spend a long time in a dynamical state. Long enough to give rise to interesting spatiotemporal structures, during which the short-time lyapunov exponent is positive... so I would call them dynamical systems too.

 

[rhody]

I thought this was interesting and worth sharing. TED: Antonio Damasio: The quest to understand consciousness. Here is a nice view of real axional connections in the brain and the directionality of their pathways. His talk is geared toward "what" the brain does as he best understands it. The how the brain does it is what the three of you have been discussing here. I thought it is useful to put into context.

http://img833.imageshack.us/img833/2078/connectionsinthebrain.jpg

http://img859.imageshack.us/img859/4840/axionalconnections.jpg

Backing up a bit to my post and the responses:

Thanks for your explanation of dopamine and acetycholine, atty, now I understand, and for the links.

Dopamine and acetylcholine are "non-classical" neurotransmitters and are called neuromodulators, because they act on different time scales from the fast "classical" neurotransmitters.

aperion, you said.

It is only surprising if you presume the brain must be constructed bottom-up out of definite hardware components. And given neurons are built out molecular components like microtubles with a half-life of about 10 minutes, this seems a silly presumption indeed.

You mention a time component of a half life of about ten minutes for microtubules, and I was referring to a distance of about one half of an inch of change observed in the experiment of the nerves on a monkey's deafferentiated arm. What does the half life of a microtubule have to do with the distances, up to one half of an inch in the measurement of activity in an up to that time unused brain region ?

See excerpt of https://www.physicsforums.com/showpost.php?p=2925375&postcount=25 below:

They performed the procedure in four hours, which normally took a whole day to complete. They removed part of the monkey's skull, and inserted 124 electrodes in different spots of the sensory cortex map for the arm, then stroked the deafferentiated arm. As expected, the arm sent no impulses to the electrodes. Then, Pons stroked the monkey's face, knowing that the brain map for the face is right next to the one for the arm. The neurons in the monkey's deafferentiated arm map began to fire, confirming that the facial map had taken over the arm map. As Merzenich had seen in his experiments, when a brain map is unused, the brain can organize itself so another mental function can take over the processing space. Most surprising was the scope of the organization, over a half of an inch ! Holy crap... that to this humble observer is freaking amazing. The monkey was then euthanized. Over the next six months, this experiment was repeated with three more monkeys, with the same results. Taub had proved that reorganization in damaged brains could occur in very large sectors giving hope to those suffering from severe brain injury.

Rhody...

 

[apeiron]

You mention a time component of a half life of about ten minutes for microtubules, and I was referring to a distance of about one half of an inch of change observed in the experiment of the nerves on a monkey's deafferentiated arm. What does the half life of a microtubule have to do with the distances, up to one half of an inch in the measurement of activity in an up to that time unused brain region ?

You are framing this as a "problem of plasticity", whereas I am pointing out the contrary issue - the difficulty in creating organisational stabiliity. If all the parts are fluid, how do you ever get anything to stand still?

So the puzzle from a biological point of view is stasis rather than flux. How come the cortical maps don't just change all the time and it takes fairly radical surgery, growth and relearning to make a significant change in them?

In fact from memory, the likely story in the case of this particular experiment is that the wider neural connections (from finger to facial maps) already existed. They just would have been very weak. So nothing new would have to grow over that half-inch in fact. There would just have to be upregulation of dendrites and synapses, which happens in hours.

 

[rhody]

So the puzzle from a biological point of view is stasis rather than flux. How come the cortical maps don't just change all the time and it takes fairly radical surgery, growth and relearning to make a significant change in them?

Fast forward the link to the TED talk for 12:00 and listen to what Antonio Damasio has to say about this, at 14:00 minutes discusses how the structures, he calls them modules in the diagram "create brain maps that are exquisitely topographic, and exquisitely interconnected in a recursive pattern." He also goes onto what brain areas give rise to "the self" (14:20 - 14:50). Give it a look and see what you think. I understand that you, atty and pythagorean are trying to cover all the bases. A noble but difficult endeavor. It takes persistence, going down false paths, even failure at times to discover the truth about what happens inside of our noggins.

Rhody...

 

[atyy]

As apeiron points out the brain plastic is both good and bad. The plastic brain is what allows sound localization in some animals to remain accurate even though their heads change as they age. It allows us to learn new things and recover from brain injury. However, severe tinnitus due to brain plasticity is "maladaptive". So the brain should have some means of regulating its plasticity according to age, as it does by the critical period; and according to behavioural necessity, which involve rhody's neuromodulators. Zhou et al summarize this in their introduction of this paper (free!).

When one sees change in the brain, the synapse that changed is not necessarily near by. To provide a naive example, if one neuron connects to ten, and each of those connect to another ten, then a change in one synapse at the first layer would change the 100 neurons in the last layer, without additional synapses changing. Apeiron mentions that the inputs were probably already there but weak, so that not much neurite lengthening would be needed, just more anatomically local changes. The experimental papers I linked to in post #92 (abstracts only, unfortunately) try to look at weak inputs using intracellular recording. Work that shows that some of the changes are non-local enough to be visible by light microscopy includes Antonini et al and Xu et al.

I remember an interview of Alfred Brendel about trying to learning new fingerings for a piece of music, and how in a moment of stress one reverts to the old fingerings. Most have probably had similar experiences. Zheng and Knudsen did an interesting study that shows the old maps are still there in some sense. Vogels et al's new modelling study, which I hope has enough continuous time evolution for Pythagorean to consider dynamical:) "can accommodate synaptic memories with activity patterns that become indiscernible from the background state but can be reactivated by external stimuli." The background state is a state that is experimentally probabilistically described, and theoretically thought to represent chaos, stable chaos, or transient chaos (Pythagorean, did I get your attention ).

He also goes onto what brain areas give rise to "the self" (14:20 - 14:50).

rhody, thanks for that terrific link. Damasio's talk is wonderfully argued as usual! I'd be interested to know what you think of Holland and Goodman's proposal. What is common to Damasio's and Holland and Goodman's proposals is that there is a part of the brain that makes a model of itself and its interaction with the environment. Probably the difference is that Holland and Goodman's internal models are inspired by work on motor control, and I had myself similarly guessed that the cerebellum is the seat of consciousness. In contrast, Damasio proposes brainstem areas, focussing in particular on the midbrain periaquaductal gray. Most curiously, Wikipedia's article on the PAG explicitly addresses its role in consciousness, and links to comments by Patricia Churchland (about 20 minutes in).

 

[apeiron]

Fast forward the link to the TED talk for 12:00 and listen to what Antonio Damasio has to say about this, at 14:00 minutes discusses how the structures, he calls them modules in the diagram "create brain maps that are exquisitely topographic, and exquisitely interconnected in a recursive pattern." He also goes onto what brain areas give rise to "the self" (14:20 - 14:50). Give it a look and see what you think. I understand that you, atty and pythagorean are trying to cover all the bases. A noble but difficult endeavor. It takes persistence, going down false paths, even failure at times to discover the truth about what happens inside of our noggins.

Rhody...

I don't really get the point you are trying to make. The brainstem has very little developmental plasticity, the cortex a tremendous amount.

And there are no surprises in Damasio's talk - except where he says the optic nerve apparently exits throught the foveal pit.

 

[rhody]

And there are no surprises in Damasio's talk - except where he says the optic nerve apparently exits throught the foveal pit.

You are a stickler for the smallest slip or detail, aperion, I imagine Damasio would not like to work for you.

Rhody...

 

[Pythagorean]

chaos, stable chaos, or transient chaos[/B] (Pythagorean, did I get your attention ).

The interesting thing I read in the abstract of that paper, just in general (ignoring for a moment the brain and "focusing" on the whole universe) is that irregularity can arise from a system that is not either chaotic or stochastic. (you had me at "free!").

 

[rhody]

I'd be interested to know what you think of Holland and Goodman's proposal.

Thanks atty, concerning the topic of "self", I scanned sections of Holland's and Goodman's proposal. I think this section pretty much sums it up, my interpretation, from page 14. In 1999, Damasio proposed a neurologically based theory of consciousness, summarized by Churchland in 2002 in a paper examining self-representation in nervous systems:

...that the self/nonself distinction, originally designed to support coherencing, it ultimately responsible for consciousness. Simply put, a brain whose wiring enables it to distinguish between inner-world and outer-world representations and to build a metarepresentational model of the relation between out and and inner entities is a brain enjoying some degree of consciousness.

Essentially that the self-representation's relations to representation of things in the world lead's to consciousness.

I like efficient, pithy language to describe human consciousness, and the concept of "self". Whether or not this theory lives up to testable/repeatable experiment(s) is another matter. I for one would like to see a "test for consciousness" and "test for self" created. It may not be possible, because it challenges my notion of what is possible, and that cannot be a bad thing.

P.S. I am listening to Patricia Churchland's talk now...

Rhody...

 

[rhody]

atty,

Thanks for The Science Network link, circa 2009. Churchland's talk was interesting as was the follow on speaker's. A whole new sandbox of characters to consider, I loved the hosts comment's at one point during question and answer, "Another addition to our mound of bafflement's". Pretty much sums up my thoughts. I did learn one thing, the thought process into what attributes that collectively contribute to what we recognize as "consciousness" is farther outside of the box by these researcher's than I ever imagined.

Example, a certain species of fly sleeps, and has been shown to twitch it's lower legs during sleep. The implication here is that REM sleep is necessary for consciousness and that this species of fly shares that with human's. Suggesting that REM sleep and insect leg twitching are somehow related. I would say that is outside the box, wouldn't you ?

Rhody...

 

[atyy]

rhody, my own view is that consciousness is essentially solved - I'll buy the Damasio, and Holland and Goodman approach. Maybe high tc superconductivity is more mysterious.

I would like to know how I am a strange loop fits in though. It seems closely related, but I am not sure whether inifinity is needed - perhaps as some sort of limit, analogous to phase transitions in which the thermodynamic limit exists in theory, but not exactly in real life - or the reflections in a pair of mirrors where true infinity is spoilt by atomic structure.

 

[Pythagorean]

A Good Grounding paper:

The Complex Systems Approach: Rhetoric or Revolution
Chris Eliasmith
Department of Philosophy, University of Waterloo
Received 4 February 2011; accepted 14 February 2011

http://onlinelibrary.wiley.com/doi/10.1111/j.1756-8765.2011.01169.x/pdf

rhody, my own view is that consciousness is essentially solved - I'll buy the Damasio, and Holland and Goodman approach.

Would you mind posting some references and your own summary of the solution? Due next Friday. : )

 

[rhody]

Would you mind posting some references and your own summary of the solution? Due next Friday. : )

Cute Pythagorean, I like it.

Rhody...

 

[PPagan]

Hello All,
I am a newbie here--happened to be passing through and got interested. Apologies in advance if this is not the right venue for this question, but I was struck by the claim that the problem of consciousness is solved. Do you distinguish between the question of how self-representation is achieved by the brain, and the question of how actual conscious experience ("qualia", if you like) arises out of brain function?
Thanks

 

[atyy]

Good lord, do people have no sense of humour?

 

[Pythagorean]

Good lord, do people have no sense of humour?

You mean that watery fluid in the eye between the lens and the cornea?

 

[Pythagorean]

I don't really have a sense for it, but I memorized the humorism table

 

[PPagan]

OK extremely embarrassed...

 

[Pythagorean]

"Is There Chaos in the Brain?", parts I and II:

http://www.ncbi.nlm.nih.gov/pubmed/11558325

http://www.ncbi.nlm.nih.gov/pubmed/14694754

 

[Pythagorean]

Currently, the top featured paper this month for Nature Neuroscience is:

Bump attractor dynamics in prefrontal cortex explains behavioral precision in spatial working memory
http://www.nature.com/neuro/journal/v17/n3/full/nn.3645.html

 

[AgentSmith]

Consciousness

atty,

Example, a certain species of fly sleeps, and has been shown to twitch it's lower legs during sleep. The implication here is that REM sleep is necessary for consciousness and that this species of fly shares that with human's. Suggesting that REM sleep and insect leg twitching are somehow related. I would say that is outside the box, wouldn't you ?

Rhody...

The implication makes at least two, perhaps three assumptions. Further, the use of the word consciousness in this discussion as if there was only one kind and of one degree is unwarranted.