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Are brains analog or digital?
By Andrew Orlowski in San Francisco
A new study conducted at Cornell University suggests that we think in analog, not digital. It's a bold claim which, if true, threatens to make thirty years of linguistics and neuroscience metaphors look very silly indeed.
Professor Michael Spivey, a psycholinguist and associate professor of psychology at Cornell claims that the mind "should be thought of more as working the way biological organisms do: as a dynamic continuum, cascading through shades of grey."
And that's a good description of the difference between the way analog and computers work. And The Professor wants you to know this. Although he says it in a funny sort of psycho-babble.
For example, Spivey eschews the word "brain" in his research, making the heroic leap to the word "mind" to explain his discoveries. I'm not telling you about your brain, he's saying, but about your mind. Yes, yours.
Some may think this very presumptious, but in fact this isn't uncommon in the jargon employed by fringe areas of enquiry today. For example, the Anglo-American "philosophy" camp has an exciting project, "The Philosophy of the Mind". Revelations such as "thermostats have souls," are considered a major breakthrough, apparently. Members of this camp earnestly discuss whether the mind is more like a worn-out, replaceable drive belt, or whether it's more like a DLL in a Windows-like operating system. But groups like this are plentiful on the internet, a place where you'll find people who believe vapor trails are impregnated with mind-controlling dye. In each case (as opposed to Confuscian or Hindu and Buddhist thinking), the mind is fairly oily, and ugly, and eminently disposable component.
Back to the research. The researchers observe that "even partial linguistic input can start [our emphasis] the dynamic competition between simultaneously active representations," proudly. Quite what they mean by the rather open-ended term "active representations" is never explained.
Cornell's sort of PR-department must have been puzzled too, because they hedged their bets with a release headed: "New Cornell study suggests that mental processing is continuous, not like a computer."
But, wait a second. Not like which computer? The one that crashed a minute ago leaving only a couple of ghostly dialog boxes on the screen, one of which said something like, "Do You Wish To Cancel Your Changes?" with the options "Yes" "No" and "Cancel"? If the mind is a computer, this isn't the sort of confusion any mind would want to find itself in. Maybe Spivey means some other kind of computer? Or some other kind of mind.
We'll return to that question in a moment, but we immediately see that Professor Spivey's approach is beginning to raise one or two more urgent questions.
The study examined the behaviour of only 42 students. That number might be significant - it might not. The test itself required users to click on pictures on a computer screen corresponding to a word that was read out. When near-homophones were presented as the choice, such as "candy" and "candle", the students were slower to click on the correct object, and "their mouse trajectories were more curved".
"When there was ambiguity, the participants briefly didn't know which picture was correct and so for several dozen milliseconds, they were in multiple states at once," he says. "They sort of partially heard the word both ways, and their resolution of the ambiguity was gradual rather than discrete;" from which he concludes, "it's a dynamical system."
(Or maybe the eager-to-please students were just trying too hard. There's no indication of the make-up of the group).
But Spivey is on a mission. The following phrase betrays his presence amongst us as an Emergent Person:
In the "dynamical system" approach he endorses, he tells us, "perception and cognition are mathematically described as a continuous trajectory through a high-dimensional mental space; the neural activation patterns flow back and forth to produce nonlinear, self-organized, emergent properties - like a biological organism."
In other words, he's saying that if you look at big things - and you can give them a stray, or opaque name, such as "systems" - there are smaller things swimming around inside, that may explain their behaviour. But anyone who's ever looked at a goldfish bowl knows this, and it's hardly the basis for a new science. Spivey already has a firm metaphor for how the mind should work, and is looking for evidence - or anything, really - that fits this metaphor.
By which point we were completely baffled by what Spivey was really trying to say.
So we turned to a real scientist for an explanation.
We can't turn off Analog
Did this make sense to neuroscientist Dr Bill Softky? Softky studied under Carver Mead at CalTech and recently worked at the Redwood Neuroscience Institute. He also knows a little about how computers work, and was awarded a prestige Microsoft prize for his work on the Intrinsia debugger - even though he's never worked for Microsoft.
"Because there is no accepted answer for how the brain works, people can say anything. The threshold for disproving something is higher than the threshold for saying it, which is a recipe for the accumulation of bullshit," he says.
Go on, Bill, tell us what you really think.
As people throw the computer metaphor around, they appear to be talking about quite differing ideas of what a computer really is, and the conversations seem to fly right past each other. Softky appears to be on safer empirical ground on what we might more usefully call a "circuitry" metaphor.
"We know that with brain neurons, at least 90 per cent of the bandwidth they use is digital. There is a fibre or there is not a fibre, there is a pulse or there is not a pulse; there is a ground truth to what we see," he explains.
"People see analog signals sloshing around the brain in MRI scans all the time, but much of that is from instrumental blur; the individual circuit elements and computations are still digital."
The two views then, would appear to be irreconcilable.
Or maybe not. Dr Softky says he agrees with much of what Professor Spivey values too, as expressed in a Slashdot post, where he defends the value of probablistic algorithms and neural networks, "(programmed on digitial computers)" as useful and informative ways to build simulations of various human mental processes.
So is saying that the brain works like an analog computer a better fit? Analog computing is still capable of extaordinary computation quite beyond the capabilties of a Turing machine, or a digital computer. You can see its appeal.
Today's digital computers are fast and cheap, easily produced, and ubiquitous, but that's the consequence of politics. And so analog computing is economically and philosophically unacceptable now we live in the "digital era", or "information society", or however it's branded this week. Such arguments neglect the fact that today's "economics" is entirely an agent of politics. In other words, what science does is exactly what we deem acceptable. And so, as Stephen Jay Gould pointed out, just as you can't unwind the tape of evolution and be guaranteed an instant and indentical replay, you can't assume that science would trick out just as it did. Science has always been contingent on economics and ethics, things which science can help inform, but ultimately can't decide for itself.
But it gets interesting. The two views are apparently not irreconcilable.
"I like his point about Hidden Markov models, which are practically the only 'perceptual' system of any use at all. Brains definitely work by trying to figure out what's in the world, and to do that they need probability estimates, which means analog values assigned to multiple possibilities at once (i.e. no clear "winner" at first)," says Softky.
(Jeff Hawkins took some convincing on the value of probabilities, but is now a convert.)
Softky continues -
"But it's a long way from saying that the brain represents probabilities, to somehow saying that's all it does, or saying the circuite elements do that."
"By analogy: speedsheets, tax software, cell phones, and music players all clearly represent analog values too. Does that mean they're 'analog computers'?" he asks.
"Virtually every electronic device that deals with analog information uses digital elements to do so (except for old-fashioned radios and tape players)."
"The outside world is analog in many respects, so brains have to reflect that. But efficient and modular processing elements are digital, so brains ought to take advantage of that too."
Then again, perhaps it's time the computer metaphor was dropped altogether from what may still exist as the "hard sciences", and certainly from the social sciences. Most of today's premiers obliging fire up the computer metaphor when they're stuck for ideas.
Spivey's description of a computer fails to apply to analog hardware, but it doesn't really apply to vector or superscalar processors either. And are we describing the 'chip', or the 'system'? If we can't agree to agree on what a computer looks like, we can't really begin to guess which kind of computer we most resemble. (And at this point you wonder if grown-ups haven't got better things to do than debate such things. What kind of carpet are we? Or car key? Who cares?)
So comparing the brain to a computer isn't fair to humans, and it isn't even fair to computers. You have to allow science to be science, and the metaphors to live their own life. Neither party can't make what David Letterman might call an "assgrab", in order to claim the authority of the other - and recent history is full of such presumptions - without anticipating some pushback. Both camps have, of late, settled into a state of snarling mistrust.
What Spivey's excercise seems to prove is that you can't attempt to "unite" the two camps unless one's own work is very firmly on terra firma to begin with. And when we see Spivey's students moosing around with a mouse, we can see it isn't.
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