Pitt, Berkeley Researchers Reconstruct Seashells to Model Nervous System Function

Issue Date: 
April 13, 2009
G. Bard ErmentroutG. Bard Ermentrout


G. Bard Ermentrout, a University Professor of Mathematics at Pitt, worked with the paper’s lead author, Berkeley graduate student Alistair Boettiger, and Berkeley biophysicist George Oster to model the neural network of mollusks and design a computer program that can generate the complex patterns and shapes of most mollusk shells. The researchers traced the trail of brain activity that begins with a mollusk’s tongue-like organ called a mantle and leads to the cells that produce the shell and pigmentation. They supposed that as mollusks build their shells, they retrace their previous work with the mantle and use those “memories” to continue the pattern. At the same time, the new pigment and shell growth are influenced by external factors resulting in the varied patterns and shell structure seen in nature.

Boettiger, Ermentrout, and Oster simulated the neural network with integral equations that, like the mollusk, retrace the previous pattern, but can be manipulated to accurately predict how a shell will form under specific conditions. The resulting models help illustrate how neural networks—including mammalian cortices—function in response to a combination of sensory information and past experience, the team reported in PNAS. The project was supported by the National Science Foundation.

“These models demonstrate the combined influence of sensory input and memories on brain activity,” Ermentrout said. “Brains convert sensory information into action. If a ball is thrown at you, you duck or catch it because you know that the ball could hit you. That knowledge and the sight of the ball coming at you dictate your action. A mollusk collects sensory information from its previous pigmentation and converts it into motor action by producing more pigmentation and continuing the pattern.”

To construct its model, the team studied electron microscope images of mollusk mantles to understand the neurons connecting the sensing cells in the mantle with the secretory cells that produce calcium carbonate and pigmented proteins. The team found that the excitatory and inhibitory synapses—which promote or diminish cell activity—surrounding the secretory cells and the cells’ firing thresholds act as a neural network that determines how much calcium and pigment the mollusk secretes. Different rates of calcium carbonate secretion determine the shape of the shell, while different amounts of pigment result in a pattern unique to each species.

For instance, shell ridges result from one cell increasing calcium carbonate secretion while depressing secretion from surrounding cells. The researchers also found three basic patterns of shell pigmentation determined by excitatory and inhibitory activity: stripes perpendicular to the growing edge, bands parallel to the growing edge, and more complex “traveling wave” patterns such as zigzags and chevrons.

With striped shells, a pigment-secreting cell inhibits secretion of pigment by neighboring cells but not itself, so that the same pattern is repeated day after day, yielding a stripe. Bands parallel to the growing edge form when pigment secreted on one day inhibit secreting cells for a few days, resulting in an on/off pattern. “Traveling wave” patterns of diamonds, zigzags, arrowheads, and other shapes come about when a pigment inhibits future secretion at that site but excites secretion in surrounding cells, so that pigment moves laterally on successive days like a wave.

“Our real contribution was not reproducing the patterns, but showing that the nervous system can do it with one equation,” said Oster, a professor of environmental science, policy and management, and molecular and cell biology. “The pattern on a seashell is the mollusk’s memories. The shell is laid down in layers, so the mantle is sensing the history of the mollusk’s ‘thoughts’ and extrapolating to the next layer, just like our brains project into the future.”

The full paper can be found on the PNAS Web site at www.pnas.org/content/early/2009/04/07/0810311106.abstract.