The music of the brain

How can the human brain, composed of hundreds of billions of individual neurons, produce a single mind, a single consciousness? How is thought possible? These questions have motivated researchers for generations and remain unanswered. But the past few years have seen a tidal shift in understanding the brain. Instead of considering the brain as a vast computer, processing and storing information in individual neurons, says Dr. Rafael Yuste, professor of biology at Columbia, the new model depicts the brain "harnessing together ever-shifting neuronal networks, which work in a complex pattern of synchrony like musicians in an orchestra." The process of thought is a symphony produced by the brain as a whole.

Brain as computer?

Since at least the mid-1970s, the dominant model of the brain has been hierarchical, modeled on digital computers. In brief, the hypothesis held that single neurons operated by detecting features in the environment. At the base level, neurons in the optic region of the brain, for example, would detect simple features such as lines and edges. Higher-order neurons, linked to hundreds of lower-order neurons, detected more sophisticated features: a neuron might be sensitive to red balls or green squares. At the highest level, cardinal neurons would integrate sensations to recognize concepts, such as "grandmother's face." In the hypothesis, a single neuron would be sensitive to each concept; there would thus be a "grandmother's face neuron." Memories would be laid down by changes in the ways neurons were linked to each other.

The similarity to computers is clear, with neurons replacing transistors. The brain, in this view, resembles a hierarchical corporation, with low-level office workers passing information up the chain to executives at the top and getting their orders in turn passed down the chain, each dealing only with a few superiors and subordinates.

There were problems with the hypothesis from the start. First was the problem of "binding": How could information obtained by different means be bound together into a single perception? How could the separate neurons that recognized Grandmother's face, her voice, and the word Grandmother all somehow work together to create a single perception of Grandmother? Closely linked with this was the problem of how individual neurons could produce a single consciousness. In addition, the amount of information that could be stored in even the hundreds of billions of neurons in the human brain seemed grossly inadequate to account for actual human memories, which still dwarf the memory capacities of any computer.

More critically, the hypothesis lacked experimental support. Individual neurons did respond to certain features, like lines or edges; however, they responded not to just one, but to a statistical mix of several such features. Nor could a neuron, with an average of 10,000 contacts, or synapses, from other neurons, respond reliably to the input of another individual neuron. There was no one-to-one correspondence between the response of individual neurons and any kind of information.

Cooperation, not hierarchy

Almost as soon as the single-neuron doctrine was formulated, an alternative viewpoint started to emerge, initially among a small number of researchers, including E. Roy John of NYU and W. R. Freeman of the University of California at San Diego. They argued that information in the brain is stored and processed only when millions of neurons work together with their electric potentials correlated or synchronized in patterns of firings at various frequencies. The large-scale electrical fields produced by the brain and measured in electroencephalograms (EEG), these researchers reasoned, can be produced only by the cooperative actions of many neurons. These cell assemblies, as they are called, are not anatomical entities but temporary functional collections of neurons, scattered across wide areas of the brain or even the entire brain, whose firings are synchronized at a given frequency.

Observers cannot gather information by examining the firing pattern of a given neuron, but only by looking at the correlations--synchronous activity--among many neurons. Importantly, each neuron can simultaneously be part of several assemblies, each operating at different frequencies. By analogy, this is like a person playing one drum in time with one group of drummers and another in time with a different, faster group of drummers, or playing cello in tune with one group and an oboe with another.

Cell assemblies make the problem of binding more tractable. Assemblies concentrated in auditory areas and in visual areas, for example, can overlap in the frontal cortex, the hippocampus, and other central areas, linking visual and auditory inputs together with memories into a single perception.

The tide shifts

For years, this view remained the nearly heretical view of a small group of researchers, but in the 1990s this has begun to change. "The tide is definitely turning," explains Yuste, who trained under both Torsten Wiesel, one of the founders of the old model, and David Tank, a pioneer in the new one. "The weight of evidence in favor of a neural-network or cell-assembly model is growing, and there has been a lack of progress with the old paradigm." In particular, more researchers are coming to see that it is not the firing of a single neuron that matters, or the rapidity of that firing, but the timing relative to other neurons: which neurons are firing together, at what frequencies, and in what correlated patterns.

This growing evidence became clear at a major international workshop in 1997, at Sde Boker, Israel.¹ "People were surprised at the extent that researchers using different methods were coming to the same conclusions," Yuste recalls. Yuste's own work is part of that body of evidence. He is developing a new technique to actually see neurons in action, using fluorescence. One of the problems in observing hundreds or thousands of neurons pulsing simultaneously is that the conventional probes are electrical and very localized; observing hundreds of neurons would take hundreds of micro-probes. However, Yuste is able to look at many neurons simultaneously by using a dye that fluoresces when the neurons fire spikes of electrical activity. Currently, he is using the brains of young rats, removed from the animal and kept alive for several hours in a nutrient bath. However, he hopes eventually to study the brains of living rats, exposed during operations.

"Our experience showed clearly that networks of neurons pulse in synchrony in a changing pattern," says Yuste, who worked together with Daniel Rabinowitz, associate professor of statistics at Columbia, to analyze the data. "We compared our results to simulations, where the neurons were pulsing randomly, and we're convinced these are real patterns. They are distributed throughout the region we're looking at (about half a millimeter wide), containing tens of thousands of neurons." Neurons react differently to input pulses they receive that are simultaneous with the output pulse they produce than to those that are not, Yuste and his colleagues found. "We are using fluorescence techniques to look at the dendritic spines which act as the inputs to a neuron, each contacting the axon carrying the output from another neuron. There are thousands of such spines for each neuron. When the spines got a pulse from another neuron, and the spine's own neuron pulsed simultaneously or within a very short time afterwards, the spine received a rush of calcium," Yuste explains. He believes that such large calcium fluxes could set off change in the spine that might make it more sensitive to pulses in the future, thus altering its behavior. Such changes in thousands or millions of neurons acting together might form the basis for memory.

"Yuste's pioneering use of state-of-the-art laser-based techniques has really revolutionized this field, opening up new ways of visualizing how the brain works," comments Dr. Steven Siegelbaum, professor of pharmacology at the Center for Neurobiology and Behavior at Columbia's College of Physicians & Surgeons. "Not only do these techniques allow us to see how groups of neurons communicate together, but they also allow us to see what individual dendritic spines are doing. Previously, they were just too small to see their functioning in living tissue." A number of laboratories, including Dr. Siegelbaum's, are now applying the same techniques to related studies of the brain.

Electric harmony

While Dr. Yuste has focused his work on synapses and the spike potentials that flow across them, other researchers have shown that far more is going on in the brain. The patterns seen in EEG recordings are produced not only by the spike-like pulses of neurons but by wave-like electric fields, continuously produced by neurons at their surfaces, which spread through the space between the neurons in complex patterns. While this EEG field once was viewed as the background noise behind brain functions, evidence now indicates that it is an actual signal encoding information affecting the actions of individual neurons, helping to draw them into the synchrony that in turn produces the large-scale fields and simultaneous pulse firings.

One of the mysteries of the electric oscillations in the brain is how they are synchronized across large regions in a way that seems too tightly linked for the relatively slow pulses carried through the synapses. Roger Traub, formerly of Columbia's neurology department but now at the University of Birmingham, England, recently demonstrated that fast oscillations link neurons together directly thorough electric field interactions, traveling from neuron to neuron at high speed and keeping them in beat the way sound waves keep musicians in time with each other.

These fast oscillations, beating at 50-200 Hz (roughly the same as the lowest two octaves on a piano) also seem to be intimately involved in the laying down of memories, Traub and his colleague found. When the oscillations occur in synchrony over a wide area, lasting changes in the electrical response of groups of neurons occurs, making it easier for such neurons to oscillate in synchrony in the future. It appears that the more the neurons oscillate in certain patterns, the easier it is for such patterns to recur, or to be recalled from memory.

If this new model is valid, observable differences should be seen in the correlation patterns of the EEG depending on what a subject is thinking, and experiments have demonstrated just that. For example, in work performed by Igor Holländer and colleagues² at the Institute of Information Processing of the Austrian Academy of Sciences and at the Institute of Neurophysiology of the University of Vienna, correlation maps of a subject (a musician) were made at six different frequency bands from 1.3 to 32 Hz using 19 electrodes at different points on the subject's head. The subject performed various tasks such as reading a newspaper, reading a score, listening to text and to a Mozart quartet, memorizing the quartet, and doing mental arithmetic. Maps were generated showing where the degree of correlation or synchrony between different parts of the brain increased or decreased from the resting state in each frequency band. Remarkable differences in the patterns emerged (see figure). Correlations were much stronger at the highest frequencies while listening to text and at the lowest while listening to music. High-frequency correlations were even stronger when mentally listening to the music (memorizing it), but the pattern was quite different when reading the score.

While a decade ago the dominant analogy for the brain was still the digital computer, today's brain models look more like a symphony orchestra or a chorus. Conscious states in this view consist of the pattern of variations in frequency, time, and space of the brain's electrical fields, generated by the correlated electrical activity of shifting assemblies of neurons, as members of a symphony orchestra or chorus work together in shifting patterns to produce a pattern of variations in frequency, time, and space of sound vibrations. Of course, the brain involves millions of "players" at any time, out of a population of hundreds of billions, and the "score" is improvised by the players collectively, like an extremely large jazz band.

The new model is still far from explaining how these shifting patterns of electrical and magnetic fields and the neurons that generate and interact with them produce the phenomenon of consciousness. There is no general agreement on this new model or its details. Yuste, for one, is skeptical that correlations really extend beyond very local areas of the brain. However, by focusing on the coordinated functioning of the brain as a whole, this approach seems to be a large step toward understanding that central fact of human experience.

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1. "The Neocortical Local Circuit," Sde Boker, Israel, May 4-8, 1997, sponsored by the Israel Science Foundation and the Zlotowski Center for Neuroscience, Ben Gurion University.

2. Holländer I, Petsche H, Dimitrov LI, et al. The reflection of cognitive tasks in EEG and MRI and a method of its visualization. Brain Topography 9 (1997): 177-189.

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Related links...

Neurological research at Columbia

Society for Neuroscience, including Journal of Neuroscience

William H. Calvin, The Cerebral Symphony (NY: Bantam, 1989)

Sites of interest, Columbia Neurosciences Society

Neuroguide, an online neuroscience index

BrainWeb simulated brain MRI database, McConnell Brain Imaging Centre, Montréal Neurological Institute, McGill University

Center for the Neural Basis of Cognition, Carnegie-Mellon/U. of Pittsburgh

Human Brain Project, National Institute of Mental Health

Cortical Neuron Net Database, Cornell

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ERIC J. LERNER is a physicist and free-lance science writer living in Lawrenceville, N.J., whose work has appeared in Discover, NJ Medicine, IBM Research, Laser Focus World, and many other publications. He is also the author of The Big Bang Never Happened (NY: Vintage, 1991).

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Photo Credits

Brain: Special Computer Effects Howard R. Roberts Dr. Rafael Yuste: Photo Jonathan Barkey Neuron: Photo Eric J. Lerner / Special Effects Howard R. Roberts

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