I've been taking care of Nanette's ranchette for her while she and Chuck travel the world. They're doing a sort of post-retirement grand tour, having already done the retire to the ranch thing. I get the benefit of using her pastures for my stock, and she gets some peace of mind knowing that an uptight everything-must-fit manager is overseeing her dominion. She and Chuck stop by once or twice a year and I see that when they arrive all is in order. It's almost as if their own ranch is a B&B that they visit now and again. This is an emerging profession of sorts - ranch butler, a.k.a. mouse catcher - as more urban refugees buy up ranch land but have no interest or expertise in the grungy details.

In general, I don't do television, but Nanette has a big screen and satellite programming. The last time she visited it was on the blink, a failure on my part. I didn't know it was down because I never turned it on. So, I regularly turn it on now just to see that it works. It's a time waster but not unpleasant. I have that weakness of the non-video person - the presence of a working TV induces a semi-catatonic state of slack-jawed absorption. I visited Warren and Mary Lee the other day - Nanette's neighbors and owners of yet another ranchette I manage - and stood tansfixed in their living room watching a golf match! It's not that golf is in the least bit interesting to me, it was just the TV effect.

The effect is multiplied if the programming is interesting. So, when I recently happened on a rerun of Hitchhiker's Guide to the Galaxy - a book that I've read and liked - I was frozen in place till the end. Today, with that fresh in my mind, this bit of new research triggered some speculative thoughts.

Researchers at the University of Rochester may have answered one of neuroscience's most vexing questions--how can it be that our neurons, which are responsible for our crystal-clear thoughts, seem to fire in utterly random ways?

In the November issue of Nature Neuroscience, the Rochester study shows that the brain's cortex uses seemingly chaotic, or "noisy," signals to represent the ambiguities of the real world--and that this noise dramatically enhances the brain's processing, enabling us to make decisions in an uncertain world.

"You'd think this is crazy because engineers are always fighting to reduce the noise in their circuits, and yet here's the best computing machine in the universe--and it looks utterly random," says Alex Pouget, associate professor of brain and cognitive sciences at the University of Rochester.

Improbability drive? mmm, no, just the opposite.

Pouget's work for the first time connects two of the brain's biggest mysteries; why it's so noisy, and how it can perform such complex calculations. As counter-intuitive as it sounds, the noise seems integral to making those calculations possible.

In the last decade, Pouget and his colleagues in the University of Rochester's Department of Brain and Cognitive Sciences have blazed a new path to understanding our gray matter. The traditional approach has assumed the brain uses the same method computation in general had used up until the mid-80s: You see an image and you relate that image to one stored in your head. But the reality of the cranial world seems to be a confusing array of possibilities and probabilities, all of which are somehow, mysteriously, properly calculated.

The science of drawing answers from such a variety of probabilities is called Bayesian computing, after minister Thomas Bayes who founded the unusual branch of math 150 years ago. Pouget says that when we seem to be struck by an idea from out of the blue, our brain has actually just resolved many probabilities its been fervently calculating.

"We've known for several years that at the behavioral level, we're 'Bayes optimal,' meaning we are excellent at taking various bits of probability information, weighing their relative worth, and coming to a good conclusion quickly," says Pouget. "But we've always been at a loss to explain how our brains are able to conduct such complex Bayesian computations so easily."

Two years ago, while talking with a physics friend, some probabilities in Pouget's own head suddenly resolved.

"One day I had a drink with some machine-learning researchers, and we suddenly said, 'Oh, it's not noise,' because noise implies something's wrong," says Pouget. "We started to realize then that what looked like noise may actually be the brain's way of running at optimal performance." . . .

"The cortex appears wired at its foundation to run Bayesian computations as efficiently as can be possible," says Pouget. His paper says the uncertainty of the real world is represented by this noise, and the noise itself is in a format that reduces the resources needed to compute it. Anyone familiar with log tables and slide rules knows that while multiplying large numbers is difficult, adding them with log tables is relatively undemanding.

The brain is apparently designed in a similar manner--"coding" the possibilities it encounters into a format that makes it tremendously easier to compute an answer.

Pouget now prefers to call the noise "variability." Our neurons are responding to the light, sounds, and other sensory information from the world around us. But if we want to do something, such as jump over a stream, we need to extract data that is not inherently part of that information. We need to process all the variables we see, including how wide the stream appears, what the consequences of falling in might be, and how far we know we can jump. Each neuron responds to a particular variable and the brain will decide on a conclusion about the whole set of variables using Bayesian inference.

As you reach your decision, you'd have a lot of trouble articulating most of the variables your brain just processed for you. Similarly, intuition may be less a burst of insight than a rough consensus among your neurons.

Pouget's concludes: "but I've been wrong before". It's an interesting explanation of observed systems not yet well understood. I was reminded of a post from last April about another bit of semi-mysterious cortical behavior.

Everybody has experienced a sense of "losing oneself" in an activity--whether a movie, sport, sex, or meditation. Now, researchers have caught the brain in the act of losing "self" as it shuts down introspection during a demanding sensory task. The researchers--led by Rafael Malach and Ilan Goldberg of the Weizmann Institute of Science reporting in the April 20, 2006, issue of Neuron--say their findings show that self-related function actually shuts down during such intense sensory tasks. Thus, an "observer" function in the brain does not appear to play an active part of in the production of our vivid sensory experiences. These findings go against common models of sensory experience that assume that there is some kind of "homunculus", or observer function in the brain that "looks at" sensory brain areas. Thus the finding, they said, has significance for understanding the basic nature of consciousness and perception. . .

"To conclude, the picture that emerges from the present results is that, during intense perceptual engagement, all neuronal resources are focused on sensory cortex, and the distracting self-related cortex is inactive. Thus, the term "losing yourself" receives here a clear neuronal correlate. This theme has a tantalizing echoing in Eastern philosophies such as Zen teachings, which emphasize the need to enter into a 'mindless,' selfless mental state to achieve a true sense of reality," they wrote.

It seems relevant to Pouget's observation that "As you reach your decision, you'd have a lot of trouble articulating most of the variables your brain just processed for you. Similarly, intuition may be less a burst of insight than a rough consensus among your neurons." Your self-related cortex has no clues about how the Bayesian inferences of your sensory cortex were done, and the attempt to monitor and understand seems to degrade performance. "Use the force Luke." A post from a couple of years ago focused on this a bit, referencing a Chris Genovese post that cautioned that "this does not mean, as has been claimed in some over hyped news articles, that we are all 'hard wired Bayesian with a subconscious grasp of deep mathematics' ", while noting that dogs do it too, maybe even better. It is non-conscious, even anti-conscious computation.

OK, now that I have all those balls in the air I can get to the point - the relationship of Hitchhiker to all of this. The semi-joking notion that the earth as a whole was (is?) a computing device created by cosmic mice to calculate the answer to a (lost) question, unbeknownst to the earthlings, parallels the emerging and still somewhat speculative relationship of the sensory cortex to the clumsy yet conscious prefrontal cortex. A less-joking notion is that this is true at many levels - invisible hand and all that - and gives further insight into why experts are so inexpert. It relates to the gaggle of earlier posts about expertise and decision making that played off the work of Surowieki, Tetlock, Page and others. It may help the doggedly conscious control advocates understand why their systems always crash, and seem so clumsy and simplistic in hindsight after the fall. It may also give insight into why proposed grand projects should be viewed sceptically - everything from armed interventions to global emissions protocols.

We will get better answers, better results, if we focus on supplying the distributed social mind with good information rather than the pollution of biased and spun deceits intended to skew the system. That we can't explain how the inferences are made isn't a cause for suspicion. That the seemingly chaotic, or "noisy," signals enhance the social mind's processing isn't surprising. It's not noise, it's "variability."