Research in the news: Model reconciles theories of schizophrenia

Schizophrenia has puzzled researchers for years, with imaging of large brain networks and cellular data seemingly pointing to different culprits in the origins of the devastating neurodevelopmental disease. Alan Anticevic and Yale colleagues Gen Yang and John Murray have refined a new mathematical model they hope will unify contradictory concepts by factoring in a fundamental neurological principle.

Schizophrenia has puzzled researchers for years, with imaging of large brain networks and cellular data seemingly pointing to different culprits in the origins of the devastating neurodevelopmental disease.  Alan Anticevic and Yale colleagues Gen Yang and John Murray have refined a new mathematical model they hope will unify contradictory concepts by factoring in a fundamental neurological principle.

Signals from neurons involved in vision, for instance, decay more quickly than neurons in other areas of the cortex for obvious reasons — sensory information needs to be quickly updated to prevent distortions in how the environment is perceived.  The new model incorporates data about relative rates of neuronal signal decay. This added information helps to explain how seemingly different abnormalities found in brain networks and at the neuronal level might be reconciled. The work is described the week of Dec. 21 in the Proceedings of the National Academy of Sciences.

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Bill Hathaway: william.hathaway@yale.edu, 203-432-1322