IMAGE:  February 2003 GRAPHIC:  University of Chicago Magazine
 
APRIL 2003
Volume 95, Issue 4
 
 
   
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GRAPHIC:  ResearchInvestigations
Jellyfish jumping in your head

When Jack Cowan read about a theory of forest-fire dynamics, the professor in mathematics, neurology, and the Committee on Computational Neuroscience couldn’t help but notice similarities to his own research on how nerve cells function in the brain’s neocortex.

The forest-fire model, presented in 1990 by the late Danish theoretical physicist Per Bak and his collaborators, recognizes trees in three states: green, burning, and burned. Neurons, Cowan determined in studies almost 35 years ago, also have three states: quiescent, or sensitive to stimuli; activated, when they become excited and produce a pulse; and refractory, recovering from firing a pulse.

PHOTO:  Jack Cowan and Tanya Baker’s “jellyfish” computer simulation demonstrates how neurons may fire in the brain’s neocortex. PHOTO:  Jack Cowan and Tanya Baker’s “jellyfish” computer simulation demonstrates how neurons may fire in the brain’s neocortex. PHOTO:  Jack Cowan and Tanya Baker’s “jellyfish” computer simulation demonstrates how neurons may fire in the brain’s neocortex.
Courtesy Jack Cowan
Jack Cowan and Tanya Baker’s “jellyfish” computer simulation demonstrates how neurons may fire in the brain’s neocortex.

Last spring Cowan applied the forest-fire model—an example of a dynamic system (along with earthquakes, traffic flows, and financial markets) that exhibits “self-organized criticality,” meaning it naturally evolves toward a critical state—to his mathematical neuron-network model. He reported his findings at February’s annual meeting of the American Association for the Advancement of Science, showing computer simulations of synchronized activity in neural networks.

In one simulation, which Cowan calls the “wave” or “spiral” pattern, curved segments collide and then dissipate. Based purely on the forest-fire model, the simulation doesn’t include about one-third of the neocortex’s neurons—inhibitory ones, which suppress brain activity, preventing excitatory neurons from firing too rapidly. The forest-fire prototype would be a more realistic neural model, Cowan realized, if it included a similar dampening system.

Then physics doctoral student Tanya Baker, SM’02, who works in Cowan’s computational-neuroscience group, added inhibitory neurons to the simulation. Rather than waves, the resulting pattern features tiny coils shooting forth, like paramecia or jellyfish jumping about—so Cowan and Baker named it the “jellyfish” pattern.

Both the wave and jellyfish patterns might occur during normal brain activity, or they may take place when the brain goes into an altered state. The wave pattern, Cowan conjectures, may represent what happens during epileptic seizures, while the jellyfish pattern may be the stuff of drug-induced hallucinations.

When people take mind-altering drugs, stare too long at bright light, or experience migraine headaches, epileptic seizures, or near-death experiences, chemicals such as serotonin and dopamine are blocked from stimulating inhibitory neurons. With fewer inhibitors working, too many excitatory neurons fire, and, as Cowan showed in a March 2001 Philosophical Transactions of the Royal Society of London study, people actually “see their neural activity as patterns before their eyes.”

But the patterns the neurons form in the visual cortex are not the same patterns seen by hallucinators because of how the eyes are connected to the brain. Parallel lines in the visual cortex become sucked together, and people see a spiral or tunnel, while checkerboard or hexagon patterns in the cortex look like spiralling squares or hexagons.

Now that he’s integrated internal brain activity such as inhibitors into his neuron-network model and found the jellyfish behavior, Cowan’s next step is to apply external stimuli, including simulated visual patterns, to the model. Of course, the scale on which brain activity occurs involves thousands of neurons, the details of which can’t be seen in functional MRI studies or even in optical images of the exposed neocortex. So Cowan must rely on his simulations (and the accompanying mathematical calculations) for insights into the brain’s inner workings—at least, that is, until technology catches up with theory.

—A.B.


 

 

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