Photo: Joe LaTulippe at work in his office

The Norwich Record | Winter 2018

Mathematics Professor Jocelyn “Joe” Latulippe is passionate about solving difficult biological problems. And now, he stands at the vanguard of research into a universally devastating disease.

A mathematical neuroscientist, Professor Joe Latulippe uses computational models to advance the understanding of the human nervous system and the mechanisms of neuronal activity. Such models are useful in simulating long-term conditions, as well as in vivo-like environments, and carry clear research benefits.

“Because of the limitations of experimental procedures, quantitative tools can provide critical information that human trials can’t,” Latulippe explains. “Freed from the constraints of time or bureaucracy, such simulations provide reams of data in the few short minutes—or seconds—it takes to run them.”

Latulippe recently developed one such tool himself. Called a synaptic transmission model, he originally intended it to help researchers better understand the concept of “plasticity”: what variables might strengthen or weaken a synapse over time. But he has now broadened his investigation into how neurons communicate under the influence of specific organic diseases such as Alzheimer’s.

“Alzheimer’s is the manifestation of breakdowns in memory, learning, and cognition,” Latulippe says. “In other words, patients experience a progressive loss of synaptic plasticity. We know that one of the hallmarks of the disease is the development of amyloid-beta plaques and neurofibrillary tangles; what we don’t know is what triggers their development in the first place.”

Latulippe’s model simulates exactly what happens to neural pathways and synaptic transmission at the very onset of Alzheimer’s disease—before the imminent proliferation of plaques and fibrils occurs. Now, researchers can change the conditions of an experiment by controlling for individual mechanisms—such as the effect of amyloid-beta on calcium—at will.

“Although the literature on Alzheimer’s is vast, we have yet to find a cure,” Latulippe says. “Because examining individual neurons at the molecular level is exceptionally difficult, mathematical models enable us to approximate the environmental conditions of an Alzheimer’s brain—which can then help us more clearly understand how it develops, and how we can treat it.”

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