National Neuropsychological Network (NNN)

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Project Summary This proposal aims to develop a National Neuropsychology Network (NNN), starting with four clinical research sites in California, Florida, Georgia, and Wisconsin. The NNN aims to gather clinical diagnostic information following a shared protocol, collect item-level data on representative neuropsychological (NP) instruments, and deposit these data in the NIMH Data Archive (NDA; https://data-archive.nimh.nih.gov/), more specifically in the Research Domains Criteria database (RDoCdb). The infrastructure established in the network focuses on point- of-testing data acquisition, using iPads, leveraging existing technology developed by a leading test vendor (Q- interactive, from Pearson), and developing additional software to collect specific additional measures that are widely used in clinical neuropsychology laboratories and clinics but which are not available elsewhere. The NNN will collect data on more than 10,000 cases over 4 years, representing a broad range of neuropsychiatric disorders, reflecting populations seen nationwide, and then deposit all data in RDoCdb. Data analyses will specify the latent constructs underlying each test, the factors represented by larger batteries, and create proposals for new individual tests and batteries. Novel tests (short forms and adaptive tests) will be suggested based on item-response theory modeling of each test, with desired precision of measurement for evidence- based clinical decision-making. Novel battery proposals will be informed by examining the positive and negative predictive power of each test to contribute to key differential diagnostic questions that arise in NP assessment. Both battery and individual test proposals will focus on efficiency, and are expected to yield at least a doubling of efficiency. The NNN aims to serve as a nucleus and template for additional network nodes, that will in its next generation offer a national platform for co-norming novel tests, expanding to other languages, and ultimately designing new procedures that are validated with respect to both brain function and real world adaptive capacities.