See, the difference here is the Duke researchers, and what I write here, is descriptive. What the brain may be doing is the equivalent of a statistical analysis, where the express purpose is to link raw sensory input into a perceptual quality. However, the actual description of thought eludes researchers at the moment. I can tell you in detail how the peripheral olfactory system responds to volatile chemical compounds. Is any of this mechanistic description good for telling us how we perceive odors, or at what point neuronal activity turns into a thought? One short circuit to this argument is that mechanism is not quite the same as a functional analysis. If we can identify some machine as a combustion engine, can we say with certainty that the engine belongs to a car or to a plane?
Another point is that you confuse evolution of a system (and system effects) with how the detail actually plays out. Your evolution example is not quite proper, since you assume that the details are the goal, and not the system to handle change. It isn't that the brain necessarily needs to know what it has seen before; it's just that the brain (i.e. neurons) can organize their activity in such a way that subsequent exposure to the same stimulus evokes activity in that same set of neurons. In the hippocampus (in rats, where this research was done), there are actually neurons that are sensitive to location. That's right, there are a group of neurons where, if a rat is let loose in a novel or an old environment, activity from cells are "mapped" to locations in that physical field. That is to say, a few neurons respond when the animal is at a particular point in that testing field. How do these neurons "know" when to fire? Is the rat consciously aware of its absolute location in that field? We still don't know (this research was done about 10 years ago.) Don't make the mistake of misunderstanding the mechanistic description for the phenomenon we call "thinking." When those researchers write about a "reflex", what they mean is that, neuron ensembles respond to a stimulus according to a "best-fit" manner. Stimuli with similar attributes (for example, then entire set of faces) evoke activity in neurons that have similar responses to those stimuli. In that sense, neural activity in the visual system is somewhat like a reflex: hitting the same spot (or showing rectangles differing only by color, or by size) will likely evoke the knee-jerk reflex (or the neurons that respond to rectangles will respond to all those slightly differing rectangles.)
Sometimes, scientists or the press get out of hand, and they start using non-specific words, or words with loaded meanings (but which refer to specific concepts in neuroscience). Or, genuine misunderstandings occur where laymen think a piece of research says something much more that what research usually says (trust me, this happens a lot. I explain mechanisms of smell, for instance, and everyone will start talking about how some smells evoke wonderful memories and must therefore be a primal, ur-sense... )
The problem you may have with what the researchers describe is that you may not see where emergence can occur. I've said that the brain (neurons, actually) adapts their activity based on the input. It does so by altering the connections (synapses) between neurons. Sometimes, this means causing the cell to "fire" when a particular set of synapses are active; sometimes it means the opposite. But only in this way do we mean that the system "remembers" and "knows" what has happened before, without the self (or ego, or id) having had conscious recognition thereof. Those researchers were writing about the details of how neurons respond; yes, ideally, this would also mean that the brain must be conscious of such changes. Once again, by documenting such small-scale, but important changes, we may get an idea of how the brain actually does thinking. As for the example I used, I only mean to address the common basis of the machinery. When I wrote about the brain banking on consistent, physical phenomena, of course I only meant that in an aggregate, general descriptive sense. The brain doesn't know what it is going to see. The system has evolved, however, to handle physical stimuli in a certain way that seems consistent across many species of animals.
It isn't all semantics or syntax
on
Vision is a 'Reflex'
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· Score: 2, Interesting
Sorry, I'm not putting this very well. Basically I'm trying to say that either their claim is banal - the obvious fact that our eyes are only capable of creating objects in our 'minds' based on things that have been saliant in the past (such as emphasising red objects - i.e. berries - in a green field - i.e. leaves - more that they actually contrast), since obviously our visual system has evolved based on what has been saliant in the past. Or they are making an incorrect claim that current vision is just 'seeing the past' because we don't actually get new ideas from our visual fields, we just try to fit it into previous sets of sense data. The reason that this must be incorrect is that past sense data is no more 'real' no more 'seeing actual objects' than current sense data. So if I see an apple now, it isn't fair to say I only know it's an apple because I've seen apples before because the only sense in which I've seen apples before is the sense in which I'm currently seeing apples. There isn't a 'good old days' when we really saw things, and which we're just reminding ourselves of every time we try to see again... -- SmileyBen
You missed the forest for the trees. Consider the following experiment: Someone draws a few lines on a canvas. Ask hundreds, or thousands of people to trace the lines with their fingers, or a stick. Eventually, you'll be left with a canvas with furrows where the drawn lines were. The basic, and banal, interpretation is that those people tested perceived the lines the same way. If the sample size is large enough, and properly random, one can make a statistical inference about the population (that is, all individuals contained in the human-group.)
Of course, this experiment is banal, for all we do conclude from it is that, for whatever individualistic, subjective perceptions about the world, all humans (and let's face it, it's most likely all other vision enabled animals) have a common mechanism by which those percepts are created. You've ignored that when the brain creates a visual image, it must have trained before-hand. The training likely continues throughout life, and, while images are not always created de novo, it may enable the brain to make do with an image that results from a combination of stored percepts and new information about the visual environment.
How do we know where such percepts are stored and generated? In the temporal and occipital cortices. But that doesn't say anything about the mechanism by which visual information storage, retrieval, recombination, and generation happen. As it is, the significance of what the Duke researchers suggest (and they aren't the only ones) is that the visual system banks Bayesian statistical sorting to select the likeliest base percept based on the information at hand. Such an algorithm, if you will, only occurs after a training period (otherwise, where would all those percepts come from?) The brain then is actually banking on the replicability of natural phenomena: light striking objects and reflecting a particular set of wavelengths consistently. Photon scatter, absorption, and transmittance properties are conserved by the same materials. Only in such a world is it useful for the brain to assign percepts called color and shapes to these sensations. While these assignments may in fact be arbitrary (for whatever reason, blue looks blue -- but what if blue looked red? Does it matter?), so long as the assignment remains consistent, the brain can confidently assign and sort incoming raw information into perceptions.
To say that science cannot contribute to our understanding of subjective perception is inane. I can identify men who are color-blind, and women who perceive four base colors rather than the three everyone else perceives. How? Well, don't forget, that the actual way something looks in your mind's eye is irrelevant: the only condition is that you see things your way, consistently. Testing for subjective color perception is as follows. Take a red background and write a number in green (or vice-versa). Show it to a person whom you think is color blind (red-green colorblindness happens to be the most frequent form in men.) A colorblind person will not be able to tell you what number you've written. It's as simple as that. He simply cannot distinguish reds from greens. Notice I never said that he sees reds as greens or greens as reds. It doesn't matter. We've identified that he cannot distinguish between the two. As it turns out, there's a molecular basis for this: he has a misfunctioning red-green receptor protein. Now, what is most interesting is that this protein is X-linked; men are more frequently colorblind because they only receive one copy, on the X chromosome. Since they are male, they must have a Y chromosome, given by their fathers. Females are more commonly carriers, and they'll need two busted copies before they become colorblind. So, how do these women perceive color, then, if they have 2 normal color receptors, and then one good red-green receptor and one bad red-green receptor? It turns out that they functionally have four photoreceptors; they can consistently distinguish colors that those of us with 3 photoreceptors cannot. They consistently detect the differences, in the same way. Sure, one may never know how it is to see so many colors, but we can actually identify those people that do. This isn't just syntax and semantics, people.
A second example: Do you think you have sharp vision? Do you think your peripheral vision is as good as your central vision? I can tell you that no, your peripheral vision sucks, and it doesn't take too much to show anyone. Look at a book or newspaper. Focus on a word. How many words can you perceive clearly around that one word? It won't be too many. The density of photoreceptor changes at different locations in the eye. The fovea has the highest photoreceptor density, and you can make up all sorts of stories about how density of sensors lead to sharpness of "picture." It also happens that only this foveal region (probably about 1/50 of the entire area of the retina) contains color receptors. That's right, if you focus on one spot, you'll realize that you can perceive colors in your peripheral vision. But you aren't really getting real-time color information - you have no color sensors there! Your brain must be creating the perception of color -- perhaps in the statistical way the Duke researchers write about in their book. Not only that, the periphery doesn't provide as sharp a picture either (and if you believe the results of the word-view test, it doesn't seem like you have to go far from the fovea before your brain needs to "fill-in".)
No scientist denies that new information cannot be received by the brain. After all, and especially if the nervous system is one big Bayesian statiscal inference machine, the brain will need to see new things, and assign the probabilities accordingly. The actual mechanism is still being researched. There is a place for syntax and semantics, but at the level of biology, there is only one mechanism that matters: the one the animal uses.
Slashdot Mirror
See, the difference here is the Duke researchers, and what I write here, is descriptive. What the brain may be doing is the equivalent of a statistical analysis, where the express purpose is to link raw sensory input into a perceptual quality. However, the actual description of thought eludes researchers at the moment. I can tell you in detail how the peripheral olfactory system responds to volatile chemical compounds. Is any of this mechanistic description good for telling us how we perceive odors, or at what point neuronal activity turns into a thought? One short circuit to this argument is that mechanism is not quite the same as a functional analysis. If we can identify some machine as a combustion engine, can we say with certainty that the engine belongs to a car or to a plane?
Another point is that you confuse evolution of a system (and system effects) with how the detail actually plays out. Your evolution example is not quite proper, since you assume that the details are the goal, and not the system to handle change. It isn't that the brain necessarily needs to know what it has seen before; it's just that the brain (i.e. neurons) can organize their activity in such a way that subsequent exposure to the same stimulus evokes activity in that same set of neurons. In the hippocampus (in rats, where this research was done), there are actually neurons that are sensitive to location. That's right, there are a group of neurons where, if a rat is let loose in a novel or an old environment, activity from cells are "mapped" to locations in that physical field. That is to say, a few neurons respond when the animal is at a particular point in that testing field. How do these neurons "know" when to fire? Is the rat consciously aware of its absolute location in that field? We still don't know (this research was done about 10 years ago.) Don't make the mistake of misunderstanding the mechanistic description for the phenomenon we call "thinking." When those researchers write about a "reflex", what they mean is that, neuron ensembles respond to a stimulus according to a "best-fit" manner. Stimuli with similar attributes (for example, then entire set of faces) evoke activity in neurons that have similar responses to those stimuli. In that sense, neural activity in the visual system is somewhat like a reflex: hitting the same spot (or showing rectangles differing only by color, or by size) will likely evoke the knee-jerk reflex (or the neurons that respond to rectangles will respond to all those slightly differing rectangles.)
Sometimes, scientists or the press get out of hand, and they start using non-specific words, or words with loaded meanings (but which refer to specific concepts in neuroscience). Or, genuine misunderstandings occur where laymen think a piece of research says something much more that what research usually says (trust me, this happens a lot. I explain mechanisms of smell, for instance, and everyone will start talking about how some smells evoke wonderful memories and must therefore be a primal, ur-sense... )
The problem you may have with what the researchers describe is that you may not see where emergence can occur. I've said that the brain (neurons, actually) adapts their activity based on the input. It does so by altering the connections (synapses) between neurons. Sometimes, this means causing the cell to "fire" when a particular set of synapses are active; sometimes it means the opposite. But only in this way do we mean that the system "remembers" and "knows" what has happened before, without the self (or ego, or id) having had conscious recognition thereof. Those researchers were writing about the details of how neurons respond; yes, ideally, this would also mean that the brain must be conscious of such changes. Once again, by documenting such small-scale, but important changes, we may get an idea of how the brain actually does thinking. As for the example I used, I only mean to address the common basis of the machinery. When I wrote about the brain banking on consistent, physical phenomena, of course I only meant that in an aggregate, general descriptive sense. The brain doesn't know what it is going to see. The system has evolved, however, to handle physical stimuli in a certain way that seems consistent across many species of animals.
You missed the forest for the trees. Consider the following experiment: Someone draws a few lines on a canvas. Ask hundreds, or thousands of people to trace the lines with their fingers, or a stick. Eventually, you'll be left with a canvas with furrows where the drawn lines were. The basic, and banal, interpretation is that those people tested perceived the lines the same way. If the sample size is large enough, and properly random, one can make a statistical inference about the population (that is, all individuals contained in the human-group.)
Of course, this experiment is banal, for all we do conclude from it is that, for whatever individualistic, subjective perceptions about the world, all humans (and let's face it, it's most likely all other vision enabled animals) have a common mechanism by which those percepts are created. You've ignored that when the brain creates a visual image, it must have trained before-hand. The training likely continues throughout life, and, while images are not always created de novo, it may enable the brain to make do with an image that results from a combination of stored percepts and new information about the visual environment.
How do we know where such percepts are stored and generated? In the temporal and occipital cortices. But that doesn't say anything about the mechanism by which visual information storage, retrieval, recombination, and generation happen. As it is, the significance of what the Duke researchers suggest (and they aren't the only ones) is that the visual system banks Bayesian statistical sorting to select the likeliest base percept based on the information at hand. Such an algorithm, if you will, only occurs after a training period (otherwise, where would all those percepts come from?) The brain then is actually banking on the replicability of natural phenomena: light striking objects and reflecting a particular set of wavelengths consistently. Photon scatter, absorption, and transmittance properties are conserved by the same materials. Only in such a world is it useful for the brain to assign percepts called color and shapes to these sensations. While these assignments may in fact be arbitrary (for whatever reason, blue looks blue -- but what if blue looked red? Does it matter?), so long as the assignment remains consistent, the brain can confidently assign and sort incoming raw information into perceptions.
To say that science cannot contribute to our understanding of subjective perception is inane. I can identify men who are color-blind, and women who perceive four base colors rather than the three everyone else perceives. How? Well, don't forget, that the actual way something looks in your mind's eye is irrelevant: the only condition is that you see things your way, consistently. Testing for subjective color perception is as follows. Take a red background and write a number in green (or vice-versa). Show it to a person whom you think is color blind (red-green colorblindness happens to be the most frequent form in men.) A colorblind person will not be able to tell you what number you've written. It's as simple as that. He simply cannot distinguish reds from greens. Notice I never said that he sees reds as greens or greens as reds. It doesn't matter. We've identified that he cannot distinguish between the two. As it turns out, there's a molecular basis for this: he has a misfunctioning red-green receptor protein. Now, what is most interesting is that this protein is X-linked; men are more frequently colorblind because they only receive one copy, on the X chromosome. Since they are male, they must have a Y chromosome, given by their fathers. Females are more commonly carriers, and they'll need two busted copies before they become colorblind. So, how do these women perceive color, then, if they have 2 normal color receptors, and then one good red-green receptor and one bad red-green receptor? It turns out that they functionally have four photoreceptors; they can consistently distinguish colors that those of us with 3 photoreceptors cannot. They consistently detect the differences, in the same way. Sure, one may never know how it is to see so many colors, but we can actually identify those people that do. This isn't just syntax and semantics, people.
A second example: Do you think you have sharp vision? Do you think your peripheral vision is as good as your central vision? I can tell you that no, your peripheral vision sucks, and it doesn't take too much to show anyone. Look at a book or newspaper. Focus on a word. How many words can you perceive clearly around that one word? It won't be too many. The density of photoreceptor changes at different locations in the eye. The fovea has the highest photoreceptor density, and you can make up all sorts of stories about how density of sensors lead to sharpness of "picture." It also happens that only this foveal region (probably about 1/50 of the entire area of the retina) contains color receptors. That's right, if you focus on one spot, you'll realize that you can perceive colors in your peripheral vision. But you aren't really getting real-time color information - you have no color sensors there! Your brain must be creating the perception of color -- perhaps in the statistical way the Duke researchers write about in their book. Not only that, the periphery doesn't provide as sharp a picture either (and if you believe the results of the word-view test, it doesn't seem like you have to go far from the fovea before your brain needs to "fill-in".)
No scientist denies that new information cannot be received by the brain. After all, and especially if the nervous system is one big Bayesian statiscal inference machine, the brain will need to see new things, and assign the probabilities accordingly. The actual mechanism is still being researched. There is a place for syntax and semantics, but at the level of biology, there is only one mechanism that matters: the one the animal uses.