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UCSF, Stanford Study Reveals Neural Networks Targeted in Brain Diseases
Date:4/15/2009

emporal dementia, semantic dementia, progressive nonfluent aphasia, and corticobasal syndrome - as well as two groups of healthy controls, showed that each disease targets a different neural network.

"The study suggests that these diseases don't spread across the brain like a plaque but instead travel along established neural network pathways," says the lead author of the study, William W. Seeley, MD, assistant professor of neurology at the UCSF Memory and Aging Center.

Earlier work performed by Michael Greicius, MD, senior author and assistant professor of neurology and neurological sciences at Stanford, provided Seeley with the inspiration for the present study, which extended Greicius' work on Alzheimer's disease to a host of additional dementias. The findings suggest that network degeneration represents a class-wide neurodegenerative disease phenomenon.

"Something about a network's architecture or biology is either bringing the disease to networked regions or propagating disease between network nodes," says Seeley.

At this point, the scientists have shown that the diseases cause atrophy in networked regions. "We still need to determine how the diseases impact connectivity, and we don't yet know how, at the molecular level, disease spreads between networked areas," says Seeley.

Greicius further commented, "These results suggest that brain imaging measures of network strength should be sensitive enough to detect these diseases at an early stage and, as importantly, specific enough to reliably distinguish one disease from the others."

If all forms of neurodegenerative disease are propagated along synaptic connections, says Seeley, "the framework would have major mechanistic significance, predicting that the spatial patterning of disease relate
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