so, how would one go about understanding how a computer works. well, unfortunately, the answer to this question largely depends on the motivation for asking it. for instance, if one knows how a PC works, but not a mac, then the answer would look very different then the answer to the same question from somebody who knows nothing about computers at all. thus, to appropriately answer the question: "how should one go about trying to understand how the brain works?" one should probably first specify a set of motivating factors (and maybe also desirata). so, some things we'd like include:
1) memory augmentation: our memories are limited in ways that are often detrimental to quality of life. how often is one arguing about whether or not one spouted a particular utterance? also, if i could remember everything i learned, i wouldn't need to look things up again, or even keep books after reading them.
2) optimal learning: we spend a large fraction of our lives learning knowledge that we then apply to our daily lives, whether it is in the form of wisdom or semantic information or something else, it often takes many years for us to achieve satisfactory mastering of a discipline. if we could learn more faster, technology and development could advance faster as well.
3) creative juices: while "creativity" is not particularly well understood feature of the human experience (at least i haven't found a satisfactory account of it), i still feel comfortable suggesting that if we were more creative, we could more quickly find better solutions to current problems.
4) "objective" perspectives: our lack of predictive power often results in our experiences being severely biased by previous experience. if we could somehow "objectify" our perceptions, we may be better at predicting the responses of others, and therefore be able to have more fruitful relationships.
5) better language: surely, languages are a very cool invention (or discovery, depending on perspective). and yet, they are not quite as expressive as they could be. some ideas are very difficult to express using language (for instance, abstract concepts such as the wave-particle duality). it would be great if somehow we could make languages have more expressive power.
6) love: something we all (or nearly all) of us want more of, both on the receiving and giving sides. if everybody loved one another, i imagine that many of todays problems would cease. clearly, this is a very hippie-dippie idea, and maybe seems somewhat in juxtaposition with a set of desirata for contemporary neuroscience. but, who better to figure out such a thing?
7) introspective accuracy: a common finding in psychological studies is that introspection is simply not that accurate. it'd be great if when we reflected on why we responded in the way we did, we could be more accurate.
although i have just enumerated 7 desirata, only the first two are "real" neuroscientific questions, in the sense that only two can even be expressed as questions using a neural vocabulary. the relationship between neural hardware and creativity, perspective, language, love, and introspection is so tenuous at this point, that it is probably not even worth considering until further notice. furthermore, the first two: learning and memory, are conserved evolutionarily, so we can start out by studying significantly simpler systems.
as a side note, people may argue with my desirata. ok, i'm not for everyone, and neither are my ideas. i'm happy to hear about alternative desirata...
Showing posts with label neuroscience. Show all posts
Showing posts with label neuroscience. Show all posts
Saturday, April 5, 2008
a good analogy for trying to figure out how the brain works
imagine finding a TV screen on the ground, and not knowing what it did or how. how could one figure out how it works. one strategy would be to look at each pixel in isolation, and see how it responded to various inputs, and then try to determine the "pixel-code", mapping the inputs to statistical regularities of the outputs. this might work. alternately, one could start with the simplest TV one could find that shares the same essential properties, and begin exploring the circuit underlying the behavior (ie, the mechanisms). upon developing the underlying operational principles, ie, the functions that resistors, capacitors, etc. perform, one could then scale up to increasingly complex systems. eventually, one could build up to something like a jumbotron, but it would be ill-advised to study a jumbotron, without first understanding a 4" black and white TV.
i think a similar argument applies to neuroscience. we could just start sticking electrodes in the brains of primates and humans, and hope that we can figure things out. or we could start with a much simpler system, and try to unravel the basic governing principles at work. this analogy breaks down, however, in a number of places.
first, i think the things that are especially cool about brains, are things that humans definitely do, and other animals do to a lesser degree. as the brain becomes less complex, the megacool properties become less pronounced. for instance, here is something especially cool that we do. you tell me the meaning of a word, and i then understand it, possibly forever. it is not clear what a homolog of that is in the animal kingdom. fortunately, other supercool attributes of human cognition do seem to have homologs. for instance, our ability to recognize objects. this is a megahard problem computationally. somehow, however, pretty much all animals have figured out how to do it. it is a necessary condition for behavior, at least at a very coarse level (ie, determining whether objects are predators or prey). so, this fear may be mitigated by studying properties that are conserved evolutionarily.
second, analog circuit elements are relatively simple as compared with neurons. this fear assumes that the fundamental (ie, "atomic") unit of neural computation is a neuron. so, one way to mitigate this fear is to postulate that the fundamental unit is something much simpler, ie, a synapse. while synapses are still much more complicated than analog circuit elements (eg, modeling a synapse "accurately" probably requires several states or dimensions, whereas analog circuit elements only require one), they are certainly closer, and it probably doesn't make much sense to postulate anything more atomic than a synapses. on this perspective, neurons become somewhat like integrated circuits, and then the brain becomes the whole circuit board.
third, one could argue that brains are much more general devices than TV's. but maybe that is not true. input to brains come in several possible forms: visual, auditory, etc. similarly, input to TV's come in several possible forms: tuners, cable, DVD's, etc. the output of brains also only have a few possibilities: speech, body language, movements, etc. similarly, TV's output only audio and visual signals. but brains seem to have something that TV's don't: internal states. ok, technically, TV's have 2 internal states: on and off. even if one postulates that different channels correspond to different internal states, the number of possible internal states for a TV pales in comparison to those of a brain, which are innumerable. so, let's switch the analogy from a TV to a computer. a computer (with all the appropriate dressings like an OS, programs, etc.) has may possible internal states. one may think of an internal state as follows: for a particular input, the output is different for a different internal state. so, for a computer, when running one program, a particular key stroke may lead to saving a document, whereas in another program, that same exact keystroke will lead to sending the document. in that sense, each program may be considered to correspond with a different internal state. and yet, computers are still insufficient, as the number of internal states for a computer is discrete and finite (eg, about 1 per program). however, in brains, the number of internal states may not be finite, and is certainly not discrete. for instance, i could be in a relatively good mood, in which case if i get hit by a car, it is not quite that bothersome; whereas if i were in a bad mood, it might be infuriating.
thus it seems as if even analogizing with the most sophisticated devices that humans understand (ie, computers) is insufficient, as the complexity of the human brain - at the level of internal states - is incomparably more complex. nonetheless, this seems as if its the best analogy that we can come up with, so we must work from there.
i think a similar argument applies to neuroscience. we could just start sticking electrodes in the brains of primates and humans, and hope that we can figure things out. or we could start with a much simpler system, and try to unravel the basic governing principles at work. this analogy breaks down, however, in a number of places.
first, i think the things that are especially cool about brains, are things that humans definitely do, and other animals do to a lesser degree. as the brain becomes less complex, the megacool properties become less pronounced. for instance, here is something especially cool that we do. you tell me the meaning of a word, and i then understand it, possibly forever. it is not clear what a homolog of that is in the animal kingdom. fortunately, other supercool attributes of human cognition do seem to have homologs. for instance, our ability to recognize objects. this is a megahard problem computationally. somehow, however, pretty much all animals have figured out how to do it. it is a necessary condition for behavior, at least at a very coarse level (ie, determining whether objects are predators or prey). so, this fear may be mitigated by studying properties that are conserved evolutionarily.
second, analog circuit elements are relatively simple as compared with neurons. this fear assumes that the fundamental (ie, "atomic") unit of neural computation is a neuron. so, one way to mitigate this fear is to postulate that the fundamental unit is something much simpler, ie, a synapse. while synapses are still much more complicated than analog circuit elements (eg, modeling a synapse "accurately" probably requires several states or dimensions, whereas analog circuit elements only require one), they are certainly closer, and it probably doesn't make much sense to postulate anything more atomic than a synapses. on this perspective, neurons become somewhat like integrated circuits, and then the brain becomes the whole circuit board.
third, one could argue that brains are much more general devices than TV's. but maybe that is not true. input to brains come in several possible forms: visual, auditory, etc. similarly, input to TV's come in several possible forms: tuners, cable, DVD's, etc. the output of brains also only have a few possibilities: speech, body language, movements, etc. similarly, TV's output only audio and visual signals. but brains seem to have something that TV's don't: internal states. ok, technically, TV's have 2 internal states: on and off. even if one postulates that different channels correspond to different internal states, the number of possible internal states for a TV pales in comparison to those of a brain, which are innumerable. so, let's switch the analogy from a TV to a computer. a computer (with all the appropriate dressings like an OS, programs, etc.) has may possible internal states. one may think of an internal state as follows: for a particular input, the output is different for a different internal state. so, for a computer, when running one program, a particular key stroke may lead to saving a document, whereas in another program, that same exact keystroke will lead to sending the document. in that sense, each program may be considered to correspond with a different internal state. and yet, computers are still insufficient, as the number of internal states for a computer is discrete and finite (eg, about 1 per program). however, in brains, the number of internal states may not be finite, and is certainly not discrete. for instance, i could be in a relatively good mood, in which case if i get hit by a car, it is not quite that bothersome; whereas if i were in a bad mood, it might be infuriating.
thus it seems as if even analogizing with the most sophisticated devices that humans understand (ie, computers) is insufficient, as the complexity of the human brain - at the level of internal states - is incomparably more complex. nonetheless, this seems as if its the best analogy that we can come up with, so we must work from there.
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