Building a Better Leech




By Lea McLees


ASK THE AVERAGE PERSON on the street how leeches have been useful to humans, and you will probably hear about the long-lived physician's practice of bleeding patients with the slippery, segmented worms.

But times have changed, and leeches are making new contributions via a collaboration between Dr. Steve DeWeerth of the Georgia Institute of Technology and Dr. Ron Calabrese of Emory University. DeWeerth and his students are building circuit models of portions of the leech's nervous system that control swimming and circulation.


Steve De Weerth (left) and doctoral candidate Girish Patel examine a VLSI chip that contains one segment of the leech system they are modeling. The biggest challenge DeWeerth and students face is modeling complexity of the leech in swimming and circulatory systems on both the cell and system levels.

"If we can learn how to model these biological systems, we may be able to utilize that knowledge to build better pumps, better motor control systems for robots -- and further down the road, to build better prosthetics for humans," says DeWeerth, an assistant professor in the School of Electrical and Computer Engineering.

But why the leech? Two reasons, DeWeerth says. First, its swimming and circulatory systems contain a fairly large but manageable number of neurons, compared to other systems one might model -- the human retina, for example, contains millions of neurons. Having a manageable number of neurons is important if the researchers are to depict behavior on both the cell and system levels in real time.

The neurons are also part of fairly regular, repetitive structures. "The segmented nature of the animals allows us to design one basic element which models a segment and then use that element over and over again with only neighboring connections between the elements," DeWeerth explains. "That type of regularity is not typical of most motor systems."

Second, the motor systems of the leech are intricately mapped because biologists like Calabrese have observed them for years. Calabrese studies the leech circulatory system and is knowledgeable about biological research into leech locomotion. The two researchers' collaborative work -- which also includes modeling the neurosystems for swimming in the eel-like lamprey, a jawless fish -- is funded with seed money from the Emory/Georgia Tech Biomedical Technology Center.

DeWeerth and his students use neuromorphic analog VLSI circuits to model the circulatory and swimming neurosystems. Neuromorphic means the analog circuits are modeled after biology; VLSI stands for very large scale integration, meaning the researchers pack lots of transistors and functional elements onto a small area of silicon.

DeWeerth's work is unlike much current analog VLSI modeling of biological systems. "Most of the work done so far with analog VLSI in modeling neurosystems has been for sensory systems -- for example, researchers have developed VLSI models of early visual processing in the retina, which is in the back of the human eye, and early auditory processing in the cochlea, which is in the inner ear," DeWeerth explains. "However, very little has been done with VLSI in modeling motor systems."

The leech's movement is in itself quite interesting, DeWeerth notes. Each of 20 segments in the animal houses motor controllers for swimming, and the controllers work together to cause the leech body to move. The kind of oscillation they induce is called phase lag.

"If you think of the position of the body as a big sine wave, each stage is a little bit out of phase of the one behind it. It's just like a wave moving down the body," DeWeerth says. "When leeches move faster, they keep the same phase, they just increase the frequency."


THE RESEARCHERS DESIGN the computer chips they need based on their knowledge of the two neurological systems, have the chips fabricated, and then assemble and test them. They have successfully modeled several individual segments thus far.

The research involves experimentation at both the circuit and system levels, DeWeerth says.

"There is a lot of standard circuitry people know about, but there is always new circuitry involved," he explains. "A lot of what we do here is motivated by what new circuits we can come up with to perform certain functions. We take these elementary building blocks we are given and put them together in new and unique ways to build functioning systems."

The biggest challenge the researchers are finding is emulating biological functioning at both the cell and system levels. It is a difficult task. Although many mathematicians and biologists are studying biological motor systems, few research groups are modeling them with circuits. The circuit models of the leech circulatory and swimming neurosystems that have been produced link together simple oscillators that are not accurate replicas of the corresponding neural building blocks involved. Modeling biological motor systems on both the cell and system levels, as DeWeerth is doing, facilitates accurate modeling of the biological behavior. The use of analog VLSI also allows for this behavior to be replicated in real time, which is very important if these systems are ever to be used in real-world applications.

"You can't do this detailed modeling mathematically because the equations would be horrendous," DeWeerth says. "You can't do a computer simulation because there's not enough computing power to actually simulate the entire system. The challenge is to build the entire system and get it to work, and better yet, get it working in real time."

The researchers' future goals include incorporating the electrical systems they build into a larger one including sensor feedback and adaptability. They also want to learn more about motor systems and eventually apply their knowledge to other projects.

"We're learning how the systems work and we are giving feedback to biologists, but the other side of the goal is to apply what we learned to engineering systemsin areas such as signal processing, robotics, and biomedical prosthetics," DeWeerth says.

Further information is available from Dr. Steve DeWeerth, School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0250. (Telephone: 404-894-4738) (E-mail: steve.deweerth@ece.gatech.edu)

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Last updated: 26 Jan. 1996