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Schizophr Bull. 2017 Jul 1;43(4):814-823. doi: 10.1093/schbul/sbw168.

The Processing-Speed Impairment in Psychosis Is More Than Just Accelerated Aging.

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Neurocognition, Neurocomputation and Neurogenetics (n3) Division, Department of Psychiatry, Yale University School of Medicine, 40 Temple Street, Room 694, New Haven, CT 06511.
Olin Neuropsychiatry Research Center, Institute of Living, Hartford, CT.
South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, Brownsville, TX.
Department of Psychology, Stanford University, Stanford, CA.


Processing speed is impaired in patients with psychosis, and deteriorates as a function of normal aging. These observations, in combination with other lines of research, suggest that psychosis may be a syndrome of accelerated aging. But do patients with psychosis perform poorly on tasks of processing speed for the same reasons as older adults? Fifty-one patients with psychotic illnesses and 90 controls with similar mean IQ (aged 19-69 years, all African American) completed a computerized processing-speed task, reminiscent of the classic digit-symbol coding task. The data were analyzed using the drift-diffusion model (DDM), and Bayesian inference was used to determine whether psychosis and aging had similar or divergent effects on the DDM parameters. Psychosis and aging were both associated with poor performance, but had divergent effects on the DDM parameters. Patients had lower information-processing efficiency ("drift rate") and longer nondecision time than controls, and psychosis per se did not influence response caution. By contrast, the primary effect of aging was to increase response caution, and had inconsistent effects on drift rate and nondecision time across patients and controls. The results reveal that psychosis and aging influenced performance in different ways, suggesting that the processing-speed impairment in psychosis is more than just accelerated aging. This study also demonstrates the potential utility of computational models and Bayesian inference for finely mapping the contributions of cognitive functions on simple neurocognitive tests.


Bayesian inference; aging; computational psychiatry; digit–symbol; processing speed; psychosis

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