Toward Precision Psychiatry: Statistical Platform for the Personalized Characterization of Natural Behaviors
| Autor: | Elizabeth B. Torres, Steven M. Silverstein, Jonathan Cole, John I. Nurnberger, Thomas V. Papathomas, Caroline Whyatt, Robert W. Isenhower, Jillian Nguyen, Jacob I. Sage, Jorge V. José |
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| Rok vydání: | 2016 |
| Předmět: |
medicine.medical_specialty
stochastic analyses precision medicine autism spectrum disorders Schizophrenia (object-oriented programming) deafferentation autism Disease Behavioral neuroscience lcsh:RC346-429 050105 experimental psychology 03 medical and health sciences 0302 clinical medicine Methods medicine 0501 psychology and cognitive sciences Psychiatry lcsh:Neurology. Diseases of the nervous system Kinesiology business.industry 05 social sciences Parkinson Disease Precision medicine medicine.disease schizophrenia precision phenotyping Neurology Analytics Parkinson’s disease Autism Motor control disorders Neurology (clinical) Noise (video) Psychology business sensory–motor noise 030217 neurology & neurosurgery Neuroscience |
| Zdroj: | Frontiers in Neurology, Vol 7 (2016) Frontiers in Neurology |
| ISSN: | 1664-2295 |
| Popis: | There is a critical need for new analytics to personalize behavioral data analysis across different fields, including kinesiology, sports science and behavioral neuroscience. Specifically, to better translate and integrate basic research into patient care we need to radically transform the methods by which we describe and interpret movement data. Here we show that hidden in the ‘noise’, smoothed out by averaging movement kinematics data, lies a wealth of information that selectively differentiates neurological and mental disorders such as Parkinson’s disease (PD), deafferentation, Autism Spectrum Disorders (ASD), and Schizophrenia (SZ) from typically developing and typically aging controls. In this report we quantify the continuous forward-and-back pointing movements of participants from a large heterogeneous cohort comprising typical and pathological cases. We empirically estimate the statistical parameters of the probability distributions for each individual in the cohort and report the parameter ranges for each clinical group after characterization of healthy developing and aging groups. We coin this newly proposed platform for individualized behavioral analyses ‘precision phenotyping’ to distinguish it from the type of observational-behavioral phenotyping prevalent in clinical studies or from the ‘one-size-fits-all’ model in basic movement science. We further propose the use of this platform as a unifying statistical framework to characterize brain disorders of known etiology in relation to idiopathic neurological disorders with similar phenotypic manifestations. |
| Databáze: | OpenAIRE |
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