SEATTLE—Consciousness has the distinction of being “the problem” in neurobiology—one even more difficult to understand than sleep, according to Giulio Tononi, MD, PhD. Therefore, he and his colleagues have devised a working definition of consciousness as a starting point for solving its mysteries.

“Consciousness is everything that goes away when we fall into dreamless sleep; everything we hear, see, feel, remember, think—everything that fills our experience,” said Dr. Tononi. It includes the ability to reflect on one’s experiences, recall the past, and anticipate the future. In addition, according to Dr. Tononi, consciousness encompasses not only awareness of the environment but also dreams, which demonstrate the brain’s ability to generate consciousness even during sleep.

Efforts to understand consciousness have gone beyond mere definitions, however. Researchers are already attempting what had previously seemed impossible—to explain consciousness scientifically: particularly, how it originates and exactly where in the brain it occurs. Dr. Tononi, who is a Professor of Psychiatry at the University of Wisconsin, Madison, described these endeavors at the 16th Annual Meeting of the Associated Professional Sleep Societies.

Early attempts at a scientific explanation of consciousness suggested that portions of the reticular formations are vital for processing life experience and that consciousness is very difficult without them. “But they are not the seat of consciousness,” Dr. Tononi stated. In an effort to determine what is, researchers are studying cortical function both in humans and in other primates whose brains are similar to those of humans. For example, of the 32 cortical areas in the macaque brain (and their related thalamic sections), most seem responsible for some aspect of consciousness, such as perception of motion, shapes, or faces.

However, consciousness does not appear to rely entirely on any one area of the thalamocortical system, he said. Rather, it “seems to depend on the interaction of many different areas.” Conversely, other large chunks of neural tissue—the cerebellum, for example—have little or nothing to do with consciousness. “We all know that if you take out the cerebellum in an adult human being, consciousness is hardly affected,” Dr. Tononi pointed out.

INTEGRATION AND DIFFERENTIATION

What distinguishes brain areas that are involved in consciousness from those that are not? Integration and differentiation, according to Dr. Tononi. Because of cooperation between the involved brain areas, consciousness occurs as a whole (integration). Yet the interactions among many brain areas are so complex that an enormous repertoire of conscious experiences is possible. Depending on how stimuli are interpreted, individuals experience one particular conscious state while the remaining possibilities are discarded (differentiation). This process is continuous, occurring every fraction of a second.

The normally integrated nature of consciousness can be better appreciated when one observes those individuals who lack it. “Split-brain” patients, for example, exhibit dual consciousness because their brain hemispheres are disconnected, usually as a result of a surgical procedure such as callosotomy. The differentiation of consciousness is evident in that an enormous repertoire of possible conscious states is always available every fraction of a second: One could show any slide, or any frame of a motion picture, and within a fraction of a second we experience a different conscious image. The differentiation of conscious experience is reflected in the constantly changing patterns of neural activity when we are conscious. By contrast, when consciousness is reduced or lost, as in deep, slow wave sleep or during epileptic seizures, all neurons do is either fire or be silent together.

CONSCIOUSNESS, STATISTICALLY SPEAKING

It is impossible to formulate a neural view of consciousness without a more precise understanding of integration and differentiation, Dr. Tononi stressed. Thus, for the past several years, he has been developing a statistical measure called neural complexity. “All this does is measure how much of a [neural] system is integrated and yet has a large repertoire of available [conscious] states,” he explained.

The first step in measuring neural complexity is calculating integration and differentiation. Integration is characterized by statistical dependence among large subsets of a neural system, and differentiation involves statistical independence of small subsets in the system. Values of neural complexity are obtained from estimates of the average deviation from statistical independence among subsets of increasing size. Neural complexity is considered high when integration and differentiation coexist in a neural system; it is low when the components of the neural system are completely dependent or independent.

The cerebral cortex is an example of a neural system that is highly complex and thus more apt to contribute to consciousness. Studies of the brain in computer simulations have linked the cerebral cortex’s connectivity patterns—a high density of connections, strong local connectivity organizing cells into neuronal groups, patchy connectivity among neuronal groups, and prevalent reciprocal connections—with high neural complexity values.

Dr. Tononi emphasized that his work on neural complexity is still in the early stages and that the validity of this measure is tentative. “But at least it gives us the opportunity to think about ways of testing it,” he concluded.

NR

—Timothy Begany

Suggested Reading
Edelman GM, Tononi G. A Universe of Consciousness: How Matter Becomes Imagination. New York, NY: Basic Books; 2001.

Sporns O, Tononi G, Edelman GM. Connectivity and complexity: the relationship between neuroanatomy and brain dynamics. Neural Netw. 2000;13:909-922.

Tononi G, Edelman GM. Consciousness and complexity. Science. 1998;282:1846-1851.

Tononi G, Edelman GM. Consciousness and the integration of information in the brain. Adv Neurol. 1998;77:245-279.

Tononi G, Sporns O, Edelman GM. A measure for brain complexity: relating functional segregation and integration in the nervous system. Proc Natl Acad Sci U S A. 1994; 91:5033-5037.

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