Brain Influences Itself with Its Own Electric Field

[apeiron]

Now I understand how you came to this opinion. I won't defend Ramanchandran's view here, and can understand the upset part.

Thanks for accepting my point. A rare occurence on PF for some reason . In fact mirror neurons were being hyped all over the place in the late 90s. Ramachadran is a milder example (and I would excuse him somewhat because he just gets over-enthusastic).

For the human specificity, or for self-awarness as we were discussing earlier? You may state that idea for an understanding of the human specificity, but if you want to explain self-awarness using Vygotskean approach, you'll have to pretend that self-awarness is specific to humans. It was maybe possible to think that at Vygotsky time, but not now. That's why I said earlier that all Vygostkean's views regarding self-awarness are simply outdated. Of course, if there is a hidden jewel that can escape this critic, I'll be glad to hear it. But no, I won't trust your word up to consider my homework is to search for something that has all reasons not to exit in the first place.

What evidence are you thinking of for self-awareness in animals? What is this new data?

If you are talking about Gallup, or machievellian monkeys, or other stuff, I'm well familiar with it. There is nothing yet that contradicts a social constructionist or symbolic interactionist understanding of exactly how human minds are different from that of even other intelligent social mammals.

 

[rhody]

Liveo, Aperion, Pythagorean,

From this link: http://www.howstuffworks.com/framed...gazine.com/2007/aug/unsolved-brain-mysteries"

It is likely that mental information is stored not in single cells but in populations of cells and patterns of their activity. However, it is currently not clear how to know which neurons belong to a particular group; worse still, current technologies (like sticking fine electrodes directly into the brain) are not well suited to measuring several thousand neurons at once. Nor is it simple to monitor the connections of even one neuron: A typical neuron in the cortex receives input from some 10,000 other neurons.

Although traveling bursts of voltage can carry signals across the brain quickly, those electrical spikes may not be the only—or even the main—way that information is carried in nervous systems. *Forward-looking studies are examining other possible information couriers: glial cells (poorly understood brain cells that are 10 times as common as neurons), other kinds of signaling mechanisms between cells (such as newly discovered gases and peptides), and the biochemical cascades that take place inside cells.

and

http://www.howstuffworks.com/framed...gazine.com/2007/aug/unsolved-brain-mysteries"

The mechanisms underlying consciousness could reside at any of a variety of physical levels: molecular, cellular, circuit, pathway, or some organizational level not yet described. The mechanisms might also be a product of interactions between these levels. One compelling but still speculative notion is that the massive feedback circuitry of the brain is essential to the production of consciousness.

In the near term, scientists are working to identify the areas of the brain that correlate with consciousness. Then comes the next step: understanding why they correlate. This is the so-called hard problem of neuroscience, and it lies at the outer limit of what material explanations will say about the experience of being human.

Rhody...

 

[atyy]

Just a quick note for to help the OP's literature search - a technical term for electric field effects of the type mentioned is "ephaptic" - I learned this from Gordon Shepherd's book "The Synpatic Organization of the Brain".

 

[atyy]

That's the hypothesis I think is intuitive and falsifiable enough to justify investgating.

I still don't understand the difference between transient chaos and stable chaos quite yet though, still absorbing the paper.

But to me, it seems like realistically, most systems we consider chaotic will eventually die out (heat death). If you take time to infinity for the lyaounov exponent, wouldn't this inevitably result in a negative lyaounov exponent? So already it seems that FTLE (finite time lyap constant) are more applicable to me.

For "strange attractor" chaos, the largest lyapunov exponent is negative when you are "on" the attractor. In transient and stable chaos the lyapunov exponent is negative "on" the attractor, but the transient behavior appears very complicated. Transient and stable chaos are distinguished by positive and negative lyapunov exponents on the transients.

http://arxiv.org/abs/cond-mat/0401038
http://arxiv.org/abs/cond-mat/0603154
http://www.frontiersin.org/Computational_Neuroscience/10.3389/neuro.10.013.2009/abstract

 

[Lievo]

Thanks for accepting my point. A rare occurence on PF for some reason .

Yeah, I'm quite new but I also noticed this 'feature' :zzz:

In fact mirror neurons were being hyped all over the place in the late 90s. Ramachadran is a milder example (and I would excuse him somewhat because he just gets over-enthusastic).

A milder example? Just for fun, I'd be curious if you can cite the extreme ones

If you are talking about Gallup, or machievellian monkeys, or other stuff, I'm well familiar with it.

Do you accept the idea that many mammals, and probably all, share self-awarness?

There is nothing yet that contradicts a social constructionist or symbolic interactionist understanding of exactly how human minds are different from that of even other intelligent social mammals.

Again this lacks specificity and, more important, is beside my point. My point was that mirror neurons may be the first hint we have to understand (and construct) self-awarness, a trait common to many animals but absent from our computing software. You can't explain this using an approach that focused on what human can do, because this is not specific to humans.

 

[Lievo]

Liveo, Aperion, Pythagorean

What was the question?

Just a quick note for to help the OP's literature search - a technical term for electric field effects of the type mentioned is "ephaptic" - I learned this from Gordon Shepherd's book "The Synpatic Organization of the Brain".

Ephatic commonly refers to what happens between close axons, especially when myelin is absent or damaged. I'm not sure it is a good idea to use the same term for effects of electrical currents in grey matter.

 

[apeiron]

Do you accept the idea that many mammals, and probably all, share self-awarness?

All animals are aware, but there is no evidence that even chimps are self-aware in a strong human sense of internalising socially-evolved norms of behaviour and self-regulation.

So chimps can extrospect, but they are not introspective - able to have thoughts about their thoughts.

If you feel differently, again what is your evidence?

Again this lacks specificity and, more important, is beside my point. My point was that mirror neurons may be the first hint we have to understand (and construct) self-awarness, a trait common to many animals but absent from our computing software. You can't explain this using an approach that focused on what human can do, because this is not specific to humans.

You say self-awareness is a trait common to many animals. But on what evidence?

And mirror neurons are evidence for the modelling/mental shadowing of the actions of others. So they would underwrite an awareness of others perhaps. But why then necessarily an awareness of self?

 

[Pythagorean]

So chimps can extrospect, but they are not introspective - able to have thoughts about their thoughts.

If you feel differently, again what is your evidence?

What's the evidence for chimps not being introspective?

 

[Lievo]

What's the evidence for chimps not being introspective?

Hard to tell, of course. However, we have some evidences that Chimps cannot make reflexive sentences. For example they can say 'I want this apple. The apple is in the box.', but they won't say 'I want the apple that is in the box'. This lack of reflexive sentence may be taken as an indication that they have limited access to metacognition (I think that I'm thinking), and metacognition is what aperion was referring to.

...and again, metacognition is beside my point. My point is about self-awareness, a basic feature that many if not all mammals share, but none of our 'artificial intelligence'. Apperion, I don't know if that's because my point is unclear, but I would be interested if you could start addressing it.

 

[apeiron]

...and again, metacognition is beside my point. My point is about self-awareness, a basic feature that many if not all mammals share, but none of our 'artificial intelligence'. Apperion, I don't know if that's because my point is unclear, but I would be interested if you could start addressing it.

I can't imagine why you would think most mammals share self-awareness. So I asled you what evidence you put forward for this unorthodox view. Or how are you defining self-awareness here?

If you just mean all mammals have a self-image in the sense of a sense of emboddiment, then of course I agree. But this is not an introspective sense of self, a socially regulated sense of self.

 

[rhody]

Just picked up a just released copy of: "http://www.scientificamerican.com/article.cfm?id=mind-reviews-the-tell-tale-brain" ", by... guess who, V.S Ramachandran of course, and he addresses the subject of Mirror Neuron's in his own unique way.

From the link:

Take mirror neurons, nerve cells that are activated when we perform an action or when we observe someone else performing an action. These neurons appear to help animals and humans imitate the behaviors they observe. Ramachandran theorizes that this sophisticated system of mirror neurons not only evolved to create awareness of others but also brought about self-awareness in humans. He fittingly dubbed these neurons “empathy neurons.” Based on this theory, he suggests that Cotard syndrome may result from damage to mirror neuron circuits, causing a person to lose that self-awareness.

Such bold leaps may make some scientists uneasy, but they are also what make Ramachandran so provocative and his book such an entertaining read.

Let's see what other provocative things he has to say, I will read the book, but may jump around and summarize the mirror neuron parts if what he has to say tweaks my interest. Stay tuned, and Happy New Year...

Rhody...

 

[rhody]

http://www.ted.com/talks/stefano_mancuso_the_roots_of_plant_intelligence.html" before you say, Rhody has lost it, he is nuts... fast forward to 9:40 in the talk,

10:00 Action potentials the same signals you see operating in neurons in the brain...

and at 9:45 root apex and movement without a brain... my thought possible correlation with how neurons expand, branch in the brain... in small region with highest consumption of O2 in the plant. Could sensitive instruments detect similar growth potentials exhibiting themselves in the human brain ? Is this mere coincidence ? You decide... with an open mind of course.

Rhody...

 

[atyy]

http://www.ted.com/talks/stefano_mancuso_the_roots_of_plant_intelligence.html" before you say, Rhody has lost it, he is nuts... fast forward to 9:40 in the talk,

10:00 Action potentials the same signals you see operating in neurons in the brain...

and at 9:45 root apex and movement without a brain... my thought possible correlation with how neurons expand, branch in the brain... in small region with highest consumption of O2 in the plant. Could sensitive instruments detect similar growth potentials exhibiting themselves in the human brain ? Is this mere coincidence ? You decide... with an open mind of course.

Rhody...

Oh, I can believe plants are intelligent. But you seem to be implying that humans are too. Please give some evidence for that!

BTW, patch clamping is used to study ion channels in plants and the mammalian brain. Also there are neurons that communicate without "standard" action potentials in c elegans and the retina.

 

[rhody]

Here's a dynamics article on "stable chaos". It reference neural networks and has some of the themes in this thread so I thought it might be of interest.

http://arxiv.org/PS_cache/arxiv/pdf/0902/0902.2545v1.pdf

Pythagorean, Atty,

I saw this article online: http://physicsworld.com/cws/article/news/41659" and I thought of this post you made awhile ago: From the article:

From thunderous mountain landscapes viewed from above to the erratic trajectories of Brownian motion, fractal patterns exist at many scales in nature. Physicists believe that fractals also exist in the quantum world, and now a group of researchers in the US has shown that this is indeed the case. This image shows the fractal pattern that results when the waves associated with electrons start to interfere with each other.

and

Serendipitous discovery

Talking about his research, Yazdani admits that observing these fractals was not the primary aim of this research. "We do this stuff every day, but once we managed to get the experiment to work with this material, we were confronted with what look like random patterns," he says. His group went on to develop the theory and realized that the electrons they were observing were on the brink of localization.

Rhody...

 

[rhody]

http://fastflip.googlelabs.com/view?q=section%3ASci/Tech&a=SCKL3OEgtcGXnM&source=news&type=embed"

Asleep or awake, brain activity is delicately balanced between inactivity and runaway catastrophe, according to a new study

There are hints in this research at "underpinning concepts or principles at work here", something that I have long believed but had little proof for:

In recent years, neuroscientists have noticed a remarkable pattern in the way neurons fire in brain samples. This activity seems to occur in avalanches which vary in size with a distribution that is scale invariant.

Scale invariance is a somewhat counter intuitive phenomenon. It means that the scale at which you examine data makes no difference to the distribution you observe. In other words, the distribution looks exactly the same whether you look at it close up or from far away.

Scientists have seen this kind of behaviour, called criticality , in all kinds of systems: the size of earthquakes, forest fires, epidemics and so on--all have the same kind of distribution.

It occurs in systems that are delicately balanced between inactivity, where the changes are always small, to a state of over activity where any change tends to be runaway.

and

One idea is that this process of learning generates dramatic changes not just in firing rates but also in the distribution of avalanches that this creates. However, Ribeiro and co found no such change in the before and after signals.

This makes me wonder what time periods were used by the researchers to collect and analyze the data. I am convinced for massive change to occur it must take place over 4 to 6 weeks usually with an hour or so of intense focused activity for five days a week. This is from Dr Merzenich's findings and his approach to learning http://en.wikipedia.org/wiki/Fast_ForWord" which addresses the time and frequency needed to achieve neuronal re-wiring if you will.

Rhody...

P.S. Thread bump, wake up call, time to get to work guys... hehe...

 

[rhody]

Ok, thread bump turns into thread crash...

I saved this link awhile ago article was posted in April 09, I was digging through my links and thought it may be worth posting. Maybe not, considering this tough crowd.

http://www.wired.com/wiredscience/2009/04/Newtonai/"

The researchers have already applied the program to recordings of individuals’ physiological states and their levels of metabolites, the cellular proteins that collectively run our bodies but remain, molecule by molecule, largely uncharacterized — a perfect example of data lacking a theory.

Their results are still unpublished, but "we’ve found some interesting laws already, some laws that are not known," said Lipson. "What we’re working on now is the next step — ways in which we can try to explain these equations, correlate them with existing knowledge, try to break these things down into components for which we have clues."

Lipson likened the quest to a "detective story" — a hint of the changing role of researchers in hybridized computer-human science. Programs produce sets of equations — describing the role of rainfall on a desert plateau, or air pollution in triggering asthma, or multitasking on cognitive function. Researchers test the equations, determine whether they’re still incomplete or based on flawed data, use them to identify new questions, and apply them to messy reality.

Redemption ? or more cone of silence and near thread death ? lol.

Rhody...

 

[Pythagorean]

For "strange attractor" chaos, the largest lyapunov exponent is negative when you are "on" the attractor. In transient and stable chaos the lyapunov exponent is negative "on" the attractor, but the transient behavior appears very complicated. Transient and stable chaos are distinguished by positive and negative lyapunov exponents on the transients.

http://arxiv.org/abs/cond-mat/0401038
http://arxiv.org/abs/cond-mat/0603154
http://www.frontiersin.org/Computational_Neuroscience/10.3389/neuro.10.013.2009/abstract

thank you atyy, I didn't notice this post last time.

 

[Q_Goest]

Hey Rody, I enjoyed your links. Thanks.

atyy, congrats on being awarded SA.

 

[Pythagorean]

Thanks for the responces, folks. Perhaps I should clarify the question. My understanding is that neurons fire because of what occurs at the synapses (ie: they exchange information or interact at the synapses) but my impression is this article is suggesting neurons are interacting through this electric field as well. To what extent is this paper saying they intereact? Is it only that they synchronize their firing or is the author suggesting neurons are also 'talking' to each other through this field? That is, are the neurons allegedly exchanging information through the field in the same way they exchange information through synapses?

Theoretically, if you apply an electric field to a neuron, you could bring it closer to (or further from) threshold.

So if you have a whole network of neurons and you entrain them all with the same field, you're simply bringing them all closer to threhold at once, increasing the chance anyone of them will fire.

Whether the the brains electric field can actually do this, I'm not sure. Technically, there's induction between electrcally active neurons. But is it significant enough to affect the membrane potential? I think we'd néed more research results.

 

[minorwork]

Theoretically, if you apply an electric field to a neuron, you could bring it closer to (or further from) threshold.

So if you have a whole network of neurons and you entrain them all with the same field, you're simply bringing them all closer to threshold at once, increasing the chance anyone of them will fire.

Whether the the brains electric field can actually do this, I'm not sure. Technically, there's induction between electrically active neurons. But is it significant enough to affect the membrane potential? I think we'd need more research results.

Is taking a neuron for being the same type of conductor as a copper wire a bit of a stretch? Inductance's effect on current from a changing magnetic field is out of phase with a changing electric field's effect on current in a circuit.

 

[Pythagorean]

Any moving charge generates fields; Especially in the myelinated case, where the majority of ions travel quickly down the axon between the nodes. Are they significant fields? I don't know.

 

[apeiron]

Any moving charge generates fields; Especially in the myelinated case, where the majority of ions travel quickly down the axon between the nodes. Are they significant fields? I don't know.

Myelinated axons produce little in the way of local field potentials because they are, well, insulated.

If endogenous field effects are computationally important, then it is the dendritic synapses, and probably the axon hillock even more so, which would likely be the generator.

This is why it is plausible that hippocampal pyramidal cells might use this mechanism (they are like little oriented dipoles with a bunch of dendrites one end, a fat axon at the other). But stellate cells wouldn't (dendrites all over the place that cancel each other out).

 

[Pythagorean]

Myelinated axons produce little in the way of local field potentials because they are, well, insulated.

If endogenous field effects are computationally important, then it is the dendritic synapses, and probably the axon hillock even more so, which would likely be the generator.

This is why it is plausible that hippocampal pyramidal cells might use this mechanism (they are like little oriented dipoles with a bunch of dendrites one end, a fat axon at the other). But stellate cells wouldn't (dendrites all over the place that cancel each other out).

Just being insulated isn't enough of course until you've done the calculation to compare the higher current to the higher reluctance. And apparently, somebody has already bothered with the crayfish:

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC1327234/

(their result was as you say, negligible)

But I'm curious whether the electric fields are coupled through magnetic fields or concentration gradients or both?

 

[giann_tee]

The article sounds implausible to me, because neurons in the brain are extremely interconnected. Any destination neuron is reachable in 3 steps, so the strong interneuronal couplings must be the primary interactions that determine how the whole network will behave. On the other hand, I recall the elementary electric oscillating circuit, comprised of two elements, the capacitor and the solenoid. When the capacitor releases its current, the current builds the magnetic field. When the magnetic field in the solenoid degrades, it induces a reverse current that refills the capacitor. A neuron is a charged capacitor and a battery. Where is the influence of the transient magnetic field then? It is probably somewhere there, but it is very small.