IBM researchers in November said they had simulated a brain with 1 billion neurons and 10 trillion synapses.IBM researchers in November said they had simulated a brain with 1 billion neurons and 10 trillion synapses. (Mark Lennihan/Associated Press)When researchers associated with IBM announced last month that they had created a computer simulation that could be likened to a cat's brain, they hadn't talked beforehand to Ben Barres. They would have profited enormously from the conversation if they had.

In a widely covered announcement, IBM said in November that its researchers had simulated a brain with 1 billion neurons and 10 trillion synapses, which it noted was about the complexity of a cat's brain. That led many writers to conclude that IBM computers could, as one put it, "simulate the thinking power" of a cat, though Forbes' Andy Greenberg was far more careful in his portrayal.

Getting a computer to work like any sort of brain, even little Fluffy's, would be an epic accomplishment. What IBM did, unfortunately, didn't even come close, as was pointed out a day later by other researchers, who published a letter scolding the company for what they described as a cynical PR stunt.


Any potential over-claiming aside, IBM's brain research follows the same pattern of similar explorations at many other centers. The logic of the approach goes something like this: We know the brain is composed of a network of cells called neurons, which pass messages to each other through connections known as synapses. If we build a model of those neurons and synapses in a computer, we will have a working double of a brain.

Which is where Ben Barres can shed some light. Barres is a neurobiologist and a specialist in something called glial cells. These are brain cells that are nearly as populous as neurons, but which are usually overlooked by researchers because they are presumed to be of little use; a kind of packing material that fills up space in between the neurons, where all the action is.

Barres, though, has made remarkable discoveries about glials. For example, if you take them away, neurons basically stop functioning properly. How? Why? We have no idea.

He does his research in the context of possible treatments for Alzheimer's, but the implications for modeling the brain are obvious, since you can't model something if you don't know how it works.

"We don't even begin to understand how neural circuits work. In fact, we don't even know what we don't know," he says. "The brain is very far from being modeled."

The computer can be a tempting metaphor for the brain, because of the superficial similarities. A computer has transistors and logic gates and networks of nodes; the various parts of the brain can be described in similar terms.

Barres says, though, that engineers seem to have a diminished ability to understand biology, in all its messy glory. Glial cells are one example, as they occupy much of the brain without our knowing barely the first thing about what they really do.

Another example, he says, involves the little matter of blood. Blood flow through the brain — its amplitudes and vagaries — has an enormous impact on the functioning of brain cells. But Barres said it's one that researchers have barely even begun to think about, much less model in a computer.

There are scores of neuroscientists like Barres, with deep knowledge of their special parts of the brain. Most of them will tell you a similar story, about how amazing the brain really is and about the utterly shallow nature of our current understanding of it.

Remember them the next time you read a story claiming some brain-like accomplishment of a computer. The only really human thing these programs are doing is attracting attention to themselves.