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Neurons are more complex than believed Scientific American

Neuroscientists have long known that timing plays some role in the brain's processing of information. They don't have many other choices. Neurons resemble digital switches, which are either "on," firing, or off, quiescent. The electrical spikes that neurons generate in response to stimulus from other neurons display uniform duration-about one millisecondand intensity. Information must, therefore, be encoded in the timing of neural spikes. The question is, How? According to one common view, signals may be encoded in the average rate at which neurons fire over a given period, just as signals in a telephone line are embodied in the rate at which electrons flow through it. But many neuroscientists have assumed that neurons in the cortex, where some of the brain's most sophisticated information processing takes place, are subject to too much noise, too many random processes, for the timing of any single, individual spike to matter much. Terrence J. Sejnowski of the Salk Institute for Biological Studies in San Diego thinks the capabilities of cortical neurons may have been underestimated. Research by him and others suggests that signals transmitted between neurons in the cortex might actually be timed with exquisite precision. In fact, Sejnowski adds, timing might be vital to the brain's processing of inforniation.

In an experiment described in Science, Sejnowski and Zachary F. Mainen, isolated a section of a rat's cortex in a dish and attached electrodes to the "spike-generation zone" of various neurons. The researchers monitored the spikes emitted by neurons as they were stimulated with electrical signals resembling those received from other neurons in the brain. Sejnowski explains that if neurons were indeed "sloppy integrators," as some scientists have assumed, their response to identical forms of stimulation would almost certainly show random variation. But Sejnowski and Mainen found that when the stimulus consisted of a pattern of pulses with strong fluctuations, identical stimulation patterns generated virtually identical firing patterns. The intervals between the spikes in each pattern varied by less than a millisecond. Although these results do not demonstrate that precise timing plays a role in the brain's functioning, they do show that such timing is possible in the cortex. John Hopfield also demonstrates that neural networks can respond more rapidly to complex pattems if they encode data not just in the rate of firing but in the relative arrival times of individual spikes. The finding makes intuitive sense, he argues. In the precision timing approach, data can be conveyed by the arrival of a single spike, whereas if firing rate alone is used, many spikes are required to represent a single piece of information. "It's a more efficient use of the available hard ware," Hopfield explains. Recent studies of the echolocation of bats by a Japanese group show how timing can solve an information-processing problem, according to Hopfield. Ideally, he explains, bats seeking to measure precisely their distance from an insect would emit extremely short but loud chirps of uniform pitch, or frequency. Instead the bat utters a longer chirp that starts at a relatively low pitch and swoops upward; the total energy of such a chirp is greater than the bat could achieve in a much shorter chirp. So how does the bat achieve high precision with such spread-out chirps? The answer has to do with the fact that different neurons in the bat's auditory cortex respond to different frequencies of sound. When the echoed chirp returns, neurons sensitive to low-frequency ,sound fire first and those sensitive to higher frequencies an instant later. But time delays in the circuitry of the bat cause these initial signals to feed into the next level of neurons-those involved in distance estimation-at precisely the same time. Sejnowski thinks that as researchers explore the brain more closely, they are likely to find more evidence that timing is crucial to the mind's operation. Neuroscience, he declares, "is on the brink of appreciating the complexity and potential implications of temporal neural computation." -John Horgan