Monthly Archives: February 2011

Conventional Misconceptions: Infinite Regressions, Computing Power, and Brain Simulations

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Some people are skeptical about the possibility of simulating a brain, ever. *cracks knuckles* It’s rebuttal time. And maybe this post is going to strike an aggressive chord, but point-by-point counterarguments are the only good counterarguments.

SO. Let’s roll.

“There’s no reason to think it will ever be possible to scan the human brain and create a functionally equivalent copy in software. Hanson is confused by the ease with which this sort of thing can be done with digital computers. He fails to grasp that the emulation of one computer by another is only possible because digital computers are the products of human designs, and are therefore inherently easier to emulate than natural systems.”

Barely out of the gate and we’re faced with a statement the refutation for which demands proving a negative. There’s no reason to think the brain can be simulated? “Well, prove that it’s impossible,” says the budding but overeager logician. Of course, proving the certainty of an impossibility is impossible (when you’re ignorant of a system’s parameters, that is). The problem with this series of assertions is that there is no evidence offered to substantiate what appears to be a thesis. The claim “brains can never be digitally simulated” at least demands follow-up samples of evidence.

It is obvious from the following lines “Hanson… etc.” that this author intended to critique someone’s reasoning, not supply direct evidence for his topic sentence. There is simply an error in organization occurring here; only after explaining Hanson’s alleged confusion is the time right to continue by making a statement like “brains can’t be emulated on computers”. That way, you can conclude demi-reasonably that brains can’t be simulated because Hanson fails to understand the limitations of computing. After that, you can strengthen your contention against Hanson by adding in citations. Of course, you’re still in the dark in terms of credibility since what some random guy says about whether or not computers can be simulated doesn’t affect whether they actually can be.

Not only is this opening argument feebly constructed; it is presumptuous to boot. Hanson’s belief that brains can someday be simulated virtually isn’t necessarily the product of confusion over the ease of porting. This author is overemphasizing Hanson’s arguable misuse of the verb “port”, when in fact Hanson was probably using it in a general sense to indicate simulation. Hanson may just think the brain is simulate-able in the future because… well, because people have simulated parts of it already. And the level of accuracy to which these simulations resemble real brains can only improve as experimental neuroscience progresses.

But hey, there’s always a chance to redeem the arguments proposed:

“The word “port” doesn’t make any sense in this context because the human brain isn’t software and he’s not proposing to modify it. What [Hanson] means is that we’d emulate the human brain on a digital computer. But that doesn’t really work either. Emulation works because of a peculiar characteristic of digital computers: they were built by a human being based on a top-down specification that explicitly defines which details of their operation are important. The spec says exactly which aspects of the machine must be emulated and which aspects may be safely ignored. This matters because we don’t have anywhere close to enough hardware to model the physical characteristics of digital machines in detail. Rather, emulation involves re-implementing the mathematical model on which the original hardware was based. Because this model is mathematically precise, the original device can be perfectly replicated.”

The first couple declarations in this segment are fairly on point; emulating the brain in a digital framework isn’t quite the same as porting software from one operating system onto another. Hanson probably would be better off just using “emulation” as his go-to descriptor. However, again, Hanson probably means to imply simulation, not emulation. It’s also true that we currently lack the technology to fully simulate computers–that is, including their hardware aspects. But that’s currently. Still no evidence is provided suggesting that such technology won’t exist in the future. And on the other hand, both theory and technology are constantly advancing in a direction that strongly suggests that brain simulation will be within reach someday. Not now, but someday.

Now, let’s address the argument which states that top-down design simplifies emulation. Yes. Yes it does. Why this precludes emulating a brain remains a mystery, however. Certainly, top-down design enables an individual porting software to allocate resources in different ways according to functional goals (you want to make a toaster, there are about three hundred godzillion ways, but they will all toast bread, or toast toast… or something). However, the brain follows rules just like any system. Ever since the Hodgkin and Huxley proposed their model of action potential propagation in 1952, flurries of biologically apt mathematical models have populated the field of theoretical neuroscience. These can all be implemented in virtual environs, the only constraint is processing power. And again, technology is constantly advancing processing power.


“You can’t emulate a natural system because natural systems don’t have designers, and therefore weren’t built to conform to any particular mathematical model. Modeling natural systems is much more difficult—indeed, so difficult that we use a different word, “simulation” to describe the process. Creating a simulation of a natural system inherently means means making judgment calls about which aspects of a physical system are the most important. And because there’s no underlying blueprint, these guesses are never perfect: it will always be necessary to leave out some details that affect the behavior of the overall system, which means that simulations are never more than approximately right.”

First of all, nature conforms to mathematical models all the time. What are the fundamental laws of physics if not mathematically expressible parameters with which nature complies? Certainly, much theory derives from flawed experimental and observational data and is thus fated never to be altogether “perfect”, but science self-corrects and therefore approaches reality ad infinitum. And there’s plenty of data that can be excluded from many simulations; probability algorithms for quantum tunneling effects, for instance, aren’t exactly essential components for weather simulations. Same goes for brains. That’s a judgment call that can be made without expectation of significant error.

As mentioned before, processing power comes into play here.  Omissions of variables are often influenced by processing constraints; however, as processors improve, this issue will dwindle.

The “approximately right” phrase used above to connote inadequacy is anything but; for instance, most protein simulations neglect the influences of gravity. And guess what, doing so doesn’t render the results of their walks inadequate. Adding in gravity algorithms would only make the simulation “more real”, not more valuable. Some variables simply are more important to describing the components of a natural phenomenon than others, and this is measurable. If there is no significant loss of accuracy when ignoring a particular set of rules, then those rules don’t need to be implemented algorithmically.

And finally:

“Scientists have been trying to simulate the weather for decades, but the vast improvements in computing power in recent decades have produced only modest improvements in our ability to predict the weather. This is because the natural world is much, much more complex than even our most powerful computers. The same is true of our brains. The brain has approximately 100 billion neurons. If each neuron were some kind of simple mathematical construct (in the sense that transistors can be modeled as logic gates) we could imagine computers powerful enough to simulate the brain within a decade or two. But each neuron is itself a complex biological system. I see no reason to think we’ll ever be able to reduce it to a mathematically tractable model. I have no doubt we’ll learn a lot from running computer simulations of neurons in the coming decades. But I see no reason to think these simulations will ever be accurate (or computationally efficient) enough to serve as the building blocks for full-brain emulation.

This is pretty cogent, actually. There was some evidence (though no exact statistics, but there aren’t many of those in this post either) provided to suggest that technological advancements don’t contribute dramatically to improvements in simulatory accuracy. Also true is that logic gates cannot sufficiently describe neurons; indeed, they are highly electrochemically dynamic systems coming in myriads of different morphologies, all of which influence their behavior. Those facets of neurons are necessary components to a good simulation. However (the pretentious sibling of “but”), the author still sticks to his guns on the basis of “seeing no reason” not to.

Well, here are a few reasons:

  • BrainGate uses microelectrodes to research activational patterns of sensorimotor neurons. These findings are used to develop brain-computer interfaces (BCIs), which enable translation of stimuli into electrical schemes the brain can interpret as well as brain-control of prosthetic apparatuses. With electrical signals alone, these technologies are already good enough to restore functionality to impaired individuals. As the data accumulates, the degree to which functionality is restored will increase.
  • The Neurally-Controlled Animat is an organism that effectively exists in a virtual environment. Neural tissues arranged on a multi-electrode array respond to controlled stimuli while all their responses, plastic changes, and so on, are recorded in real time. In this way, we acquire large volumes of information on the dynamics of real individual neurons as well as neuron clusters within a digital framework.
  • Hippocampal prostheses are brain implants intended to replace damaged or deteriorating hippocampal tissue. They function using computational models of hippocampal function and have successfully replicated functionality in rats.
  • The Blue Brain Project, first of all, is awesome. Second of all, this enterprise has resulted in 10,000 neurons of a rat neocortical column being simulated to biological accuracy (admittedly, that accuracy isn’t specified). Needless to say, the vault of supercomputers behind this is gargantuan. But from the project’s inception in 2002, it only took until 2006 to get the whole column simulated.

When considering the progress and trajectory of current research in neurotechnology, including brain-computer interfaces, neuroprosthetics, hybrots, and computational neuroscience, you must at least acknowledge the possibility that a simulated brain is on the horizon.

Now, while still on topic, this may be a good time to point out a common fallacy attributed to comprehensive brain simulations. Claims flit about here and there proposing that simulation of a whole brain is impossible due to infinite regressions of inventory. If one intends to store data on every neuron in the system, then there will have to be storage accommodations made for the storing mechanisms, and the mechanisms storing that data, and so on. This is simply false; assuming you can simulate a complete brain, it does not contain information about itself that real brains don’t. Brains in reality don’t have a neuron to account for every neuron. That would indeed create an infinite regression, but that’s obviously not how the brain works. If you were simulating a brain, the system in which it operated would store information about all neurons, not the virtual brain itself.

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If someone wished to make a really strong argument against the future possibility of brain simulation, the route that must be driven is one of data acquisition. The author of the blog post railed against here touches upon this with his mention of snowball effects. Our models are only as informed as we are, and the brain constantly revolts against being imaged well. Sure, we have fMRI, EEG, ERP, PET, SPECT, and other imaging techniques at our disposal, but the fact of the matter is that the brain’s activities are so dynamic, multitudinous, and difficult to scan that acquiring said data comprehensively and in real-time is pretty daunting. We don’t have the device(s) necessary to accomplish that task yet.

There is another way, however. While genetics is as much an enigma as neuroscience, if it advances more rapidly, simulating ground up genetic translation of the human body in a virtual setting would presumably create a viable, accurate brain. It’s based off the same encoding that our brains are, the trick is to ensure the accuracy of the algorithms denoting genetic activity. Since genetics, as a field, isn’t wrought with quite the same investigative quagmires as neuroscience, computational models may flourish sooner in that arena.

The Right and Wrong of Right and Left

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Today’s chiroscope:

Dextro (for right-handed sorts)

The Sun moves into the Sky Sign of Dextro today, introducing a season of rationality, stringency, and organization. This is the time to count things, become a computer programmer, or sequence your dimes by mint date. Dextro energy tends to be static and analytical, filled with inflexibility and an obtuse lack of emotion.

Sinistro (for lefties)

Flighty tasks involving arts and crafts may occasion your attention today. Be expressive with your friends, who admire your musical abilities and inability to manage a schedule. Sinistros need surprises and should always be ready to go out dancing, draw a pretty picture, or cry at random.

It’s an amusing dichotomy, that left brain/right brain personality scheme. Instead of divvying people up amongst twelve categories, as is the case with astrology, we place them in one of two. Sure, the online quiz you just took declared you 60% left-brained and 40% right-brained, but what you take away is that you’re a left-brained person, whatever that means.

But what does it mean? And on a relate note: how does it relate to handedness?

The overwhelming assumption about right and left brain hemispheres asserts that the left brain is logical and sequential while the right is emotional and creative. Without getting off on too much of a tangent about logic and emotion, it doesn’t take the most captious nitpicker to detect the lack of semantic clarity in this assumption (who knows what creativity is, really?). So let’s get a bit more exact.

In 1975, Kaplan and Tenhouten described three socioculturally determined modes of thought: propositional, appositional, and dialectical. Propositional thought encompasses linear reasoning; solving a basic algebra problem by using a set of steps in sequence is a good example. Language proceeds in a necessarily linear fashion (saying two words simultaneously can pose quite a challenge), and is thus propositional as well. Appositional thought refers more to holistic, synthetic thought processes. The instinctive ability to recognize faces without actively measuring distances between features is one such example. And when these two modes of thought do a little jig together, dialectical thinking results.

Experimental findings on functional hemispheric specificity fall nicely into a model wherein left=propositional and right=appositional. In a majority of cases (more on the exceptions later), language is predominantly governed by the left hemisphere. By contrast, music, which requires far more holistic and therefore appositional processing (being able to discern chords as built up from individual pitches, for instance), largely resides in the right hemisphere. Emotional affect, as construed from holistic data like gestures in conjunction with vocal tone and facial expressions, also lies within the domain of the right hemisphere. As such, when we hear people speak, it is the left brain that assigns meaning to the words but the right brain that evaluates whether their speech is blathering, grievous, heartfelt, excited, gloomy, sarcastic, etc.


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Dawson may tell you he's happy, but your right brain knows better.

However, don’t let this laterally weighted distribution of function convince you that things are completely clean-cut. Split brain, multilinguistic, and other studies have demonstrated that genetics, basic plasticity, developmental conditions, and so on can influence said dispersion in either symmetry or asymmetry-promoting ways. For example, people who acquire fluency in more than one language before the age or 6 (give or take a few months depending on the person) distribute their linguistic activation across both hemispheres equally. In general, it’s wise to bear in mind the yin and yang, overused as the image may be. Each hemisphere has a hand in the other’s business, sometimes even a whole arm.

Speaking of hands and arms (flawless transition, wouldn’t you say?), how’s about we dabble in the issue of limb dominance. While there are all kinds of interesting combinations of limb dominance–right-handed but left-armed, ambidexterous but left-footed, and so on–on the whole, humans (other other hominids, for that matter) tend to favor a side of their body. And side-favoring works contralaterally (the opposite side) for hemisphere preference. Now, bearing in mind lateralized dispersion of function isn’t clean-cut, think about a left-handed person you know. Perhaps you’re left-handed. And you’re reading this. And any left-handed people you know are likely able to read this as well. So you’re clearly able to comprehend language. While lefties generally favor their right hemisphere more than do righties, they have perfectly functional left hemispheres.

This may sound like a defensive stream of thought, and that’s because it is. The stigma of left-handedness is wrought with the negative connotations of being a “right-brained” person: that is, emotional, unreliable, disorganized, and mathematically challenged. In fact, leftness itself is wrought with negative functions just by association with left-handedness; historically, majority rule has cast lefties (a minority) as outcasts. By extension, such superstitions as a cat crossing your path towards the left indicating misfortune pop up, perfectly exemplifying leftness hate. The Supreme Court really ought to do something about this OUTRAGE.

Nah, not really. But the point is, lefties aren’t really all that statistically more likely to be emotional, unreliable, blah blah blah than anyone else. In fact, one of the only marked differences that comes to mind is that lefties have lower life expectancies than right-handed people because tools and machinery are usually designed with righties in mind, and freak accidents happen. Oh yeah, and they’re slightly more likely to be supergeniuses. And also, they have a minority advantage in sports; everyone is accustomed to playing against righties, and when lateral dominance comes into play, a lefty comes as a surprise.


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Medals of sensitivity should be awarded to the organic chemists responsible for designating left orientation to the types of chiral molecules found chiefly in the human body.

A last tidbit:

According to some recent studies, inhibitory colossal projections from the left hemisphere tend to dampen creative thought, as measured by the ability to analyze problems according to novel ideas instead of learned frameworks. While constant oblivion of standard analytical contingencies is probably not a great thing (it’s a good idea to bear “stop, drop, and roll” in mind in case of fire, for instance), optimal behaviors are probably products of dialectical, bilateral thought. Every situation is different, and organisms can respond to them to their greatest advantage if they analyze them with both knowledge and intuition.

The actual last tidbit:

Apparently, orgasms are coincident with hyperfusion of the right hemisphere. That’s some important stuff right there.

OMG, they bastardized Kratos! You bastards!

Ah, Hercules. A delightful entertainment specimen from Disney’s Renaissance, to be sure. You got gospel-singing muses, action figures of Greek heroes, Danny DeVito as a cranky satyr, and a workout montage. And an almost Forrest Gumpian Venus de Milo creation joke. Oh, and don’t forget all the classic Disney staples: a musical number about not belonging, an animal companion who externalizes other characters’ thoughts, and obligatory wordplay cheese (“I thought you were going to be the all-time champ, not the all-time chump”). It really pulls out all the stops.

And yet, when Disney tried to slate an open-air premiere for Hercules in Greece, the nation’s government rejected the idea. The reason? In short, by not portraying Hercules as a bastard, Disney had bastardized Greece’s culture.

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"I'm the most famous bastard in all of Greece. I'm... I-I'm an action figure!"

Ok, that’s not the reason entirely (though Greek mythology certainly suggests cultural fondness for love children). But there’s truth to Greece’s sentiment about the matter; Hercules has about as much to do with the Grecian hero Heracles as No Child Left Behind has to do with education. So for fun, let’s get a few facts straight, however minimally.

It would seem that Disney could only muster the research powers to get Dionysis right, which makes one wonder about the screenwriters’ states of mind when they conceived the film. But in any case, it’s probably not wise to write a children’s film featuring a chief father figure whose favorite pastimes include abduction and rape. It’s understandable that adjustments need to be made. And it’s a modern adaptation, so there’s always an excuse for envisioning old characters and stories in new, audience-sensitive ways. Disney is a business, after all, and they have to be mindful of their surroundings (that is, zeitgeists and audiences).

The question is, what are the marks of a good adaptation? Spike Jonze’s (though perhaps more aptly Charlie Kaufman’s) Adaptation deals with the subject a good bit, showcasing, on the surface, the influence of authorship on adaptations of source material and vice versa. The conflict emerges from desiring faithfulness to the source material, but inevitably catering the adaptation to some value set. Often this value set emphasizes traditional, accessible stories. Hercules is a perfect example; the film’s audience consisted primarily of American families. As such, the classical Greek myth got turned into a typical Bildungsroman Disney story with Christian overtones. And it was a commercial success. And an undeniably amusing film, at the very least. But that doesn’t necessarily make it a good adaptation.

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This may have never happened in a single Greek myth, but it's still adorable.

So, yes– adaptations cannot help but deviate from their source material. In fact, they must do so by the very nature of being something besides the source material. But perhaps the finest mark of an adaptation is that it highlights aspects of the source material that motivate an audience to learn about the source, to engage in etymological inquiry instead of accepting the adaptation as supplantation for its origins. In effect, watching the film Jack Ketchum’s The Girl Next Door (not to be confused with the movie about a pornstar living next door) should spark audience’s interest in Jack Ketchum’s novel, which in turn should perk ears towards the events that the novel is based on (the torture and death of Sylvia Likens). If an adaptation interested you in an event, story, myth, or character so deeply that you felt you had to compare it to the source material to better educate yourself, a) you are just that sort of nerd or b) the adaptation is WORKING ITS MAGIC.

Of course you could just avoid the weird calculations involved in gauging your respect for source material and desire to create new things from it and just write an original story. CRAZY, RIGHT? Just a thought.

But the thing is, children’s movie adaptations bear the burden of educating and entertaining without causing undue offense. The “without causing undue offense” clause brings about a whole maelstrom of censorship opportunities, and many times these just flit about so awry that your resultant broth is rendered flavorless. Take the film adaptation of The Golden Compass, for example. In deference to Christian audiences coming to see the film with their children, the book’s core value–iconoclasm–was completed subverted by the filmmakers. Iconoclasm was the whole point of the story! You take that out, and it’s like Sex and the City without the sex or the city (I am scrambling for a better, less embarrassing analogy, but nothing’s coming).

In the case of the original Herculean myths, their core value lies in overcoming bastardy. Hera, as the slighted wife of a philanderer, despises Hercules and constantly vies to torment him. In essence, he spends a great deal of time trying to appease her (his Greek name, Heracles, an attempt at such in that some thought including Hera’s name in Herc’s would chill her out). With regard of trying to win “parental” blessings, confidence, and so on, the Disney film is surprisingly spot-on. The facts are all wrong, but ultimately, the notion of being a hero as a way of making your superiors proud remains constant. As such, Disney’s Hercules is not a total adaptation fail.

by Ninjatic on DeviantArt

And just a small aside:

Kratos is not a demigod. You silly, silly God of War fanatics. It’s a fun, honest-to-goodness good game–just make sure you don’t assume the game’s mythos reflects actual tenets of Greek mythology or that playing the game will crown you an expert in Greek mythology.

Look at this idiot

Look at this idiot. He looks ridiculous!

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Honestly, what on Earth compelled this moron to have eyes protruding at the apexes of stalks perpendicular to its body?

Now see, here’s a reasonable fruit fly, with its eyes no further from head than need be:

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And then take one more look at the stalk-eyed fruit fly:



Perhaps you’re thinking, “Aw, that trait was selected because it’s advantageous in the fruit fly’s environment.” Seriously though, I can conceive of no possible advantage to these eyes. They’re really more of an obstacle than anything else.

As it turns out, the force to blame is a mutation in female fruit flies. Said mutation spurs these insects to prefer males with eyes that stick out. This preference emerged even before there were any stalk-eyed males, but as soon as those males started appearing (again, random mutations at work), ALL the ladies preferred them, and then subsequent generations were born with progressively longer and longer stalks. In essence, the only advantage offered by the stalks has to do with sexual selection, and the only reason they haven’t died out is because the stalks aren’t sufficiently disadvantageous as to render the flies totally discombobulated.

The female preference bias is probably at work in many birds, especially those species in which males have absurdly flagrant features and females do not (peacocks being the most obvious example). It is amusingly evident in ducks, though in a purely structural (as opposed to observationally preferable) way. Female ducks have, over time, developed increasingly convoluted vaginas, thus hindering all but the mightiest would-be penises from getting very far. As such, in strange divergence from most birds (most male birds transmit semen using multi-purpose cavities called cloacas), ducks have evolved ballistic penises of generationally increasing convolution proportional to that of the females’ vaginas. These organs come in the most outrageous corkscrew shapes:

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So, to all men who’ve inherited undesirable traits from your fathers: you know they’re not to blame.