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The Digital Brain

Individual brain neurons contribute
to the brain 's unmatched complexity

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The computing power inside your skull vastly exceeds that of any supercomputer in the world. But for the past half century, neuroscientists have generally supposed that the process by which the brain achieves its phenomenal performance is fundamentally similar to the way electronic computers work. According to the conventional view, thinking takes place through the aggregate action of billions of simple elements--cells called neurons--that are wired up in an extremely complicated way. Supercomputers are likewise built of millions of interlinked simple switches, consisting of transistors on silicon chips by companies such as Intel.

Recent research is forcing a re-evaluation of this standard model. Individual neurons, it turns out, are not so simple after all: experiments have shown that they can actually perform surprisingly complex calculations and register fine discriminations. It is even possible that networks of interacting molecules within an individual neuron might perform specific computations, Christof Koch of the California Institute of Technology reported in the January 16, 1997 issue of Nature. The organ of thought is looking far more complex than scientists believed just a few years ago.


Koch's conclusions are based on studies of the precise electrical behavior of cells in the brain. Neurons conduct signals in the form of tiny electrical impulses, known as spikes. Messages travel from one neuron to another as pulses of chemicals that are released at specialized junctions, or synapses; there are trillions of such junctions in the human brain. How and when synapses relay messages between neurons is crucially important in controlling mental activity. Moreover, neuroscientists believe that learning occurs through a change in the strength of certain synaptic connections. A frequently-used synapse becomes stronger, whereas an infrequently used one may grow weaker over time.

Researchers have long understood the basic division of function in the neuron. One set of branch-like extensions from the cell bears incoming synapses; another set of branches, usually located at the end of a long threadlike extension, processes outgoing messages. In the traditional view of the neuron, which goes back to experiments conducted in the 1940s, the cell functions as a fairly simple on-off switch. A spike would be initiated in a neuron if the total amount of stimulation at all the incoming excitatory synapses exceeded some critical level. (Conversely, if the neuron received enough inhibitory synaptic signals, it would stop producing spikes.)

Yet as Koch observes, scientists have discovered that neurons actually have numerous electrically-active components in the incoming branches. These active components, which include the NMDA receptor, a protein that spans the neuronal membrane, modify the effect of incoming messages. For example, the active components ensure that spikes received at synapses that are adjacent to one another carry more weight than spikes received at widely-separated synapses. Computer simulations show that active elements probably multiply the influence of adjacent synapses, rather than merely adding them together as the traditional neurologists had supposed. This finding adds a layer of complication to the picture of how the brain works.

And the story gets still more involved. Koch notes that the conventional idea that the timing of individual spikes is unimportant turns out to be quite wrong. Researchers had generally supposed that the representation of information in the brain depends essentially on the overall rate of firing of the neurons. But experiments over the past few years have shown conclusively that some cells in monkeys' brains can adjust the intervals between spikes in increments as little as one hundredth of as second. Moreover, the temporal patterns of spike activity across different neurons is sometimes controlled with an even finer accuracy of about one thousandth of a second. Contrary to the common wisdom, "the brain appears to care a great deal about timing," Koch says.


These results raise a new question: what is the purpose of all of that very precise neural timing? Koch points toward breaking research that may offer a clue. Spikes, once initiated in a neuron, do not propagate only in the "forward" direction--that is, toward the synapses that relay outgoing messages. Rather, experiments on isolated brain tissue indicate that spikes also move backwards, up the neuron's input branches.

The effect that these back-propagated spikes have on the active components of the brain--if indeed the phenomenon occurs in intact animals-- is far from clear. But a study published in the January 10, 1997 issue of Science by Henry Markram of the Weizmann Institute for Science and his collaborators suggests that back-propagated spikes can dramatically influence the way a neuron processes an impulse. The precise order in which one spike arrives at a synapse and another one back-propagates to the receiving neuron greatly influences the subsequent strength of a synapse, Markram's group showed. If the back-propagated spike arrives first, the synapse is weakened; conversely, if the back-propagated spike arrives second, the synapse is intensified.

This unexpected phenomenon might specifically boost the synapses that are conveying messages while suppressing random or unimportant signals. Other research conducted in the past year has shown that synapses can quickly adapt to the incoming rate of spikes at different synapses. In this way, the synapses can remain highly responsive to any sudden changes in electrical activity over a large range of background levels.

Taken together, Koch believes, these new insights into the capabilities of the single neuron suggest the brain should really be viewed as a hybrid computer, one that employs both digital pulses (between neurons) and analog computations (within them). The brain, then, is quite unlike a digital computer in its basic underpinnings. Even if the brain is built of hybrid digital-analog neurons, it need not have any computational powers that are utterly beyond those of a simple digital computer. But simulating such a brain using hybrid digital-analog elements may take thousands of times longer than it would take to simulate a brain built of the same number of simple neurons, points out Douglas R. Hofstadter of the University of Indiana.

So humans have their unique uses after all. Intel will not, it seems, be coming out with a replacement for your brain anytime soon.

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