J Vincent Filoteo1, W Todd Maddox2, F Gregory Ashby3. 1. Veterans Administration San Diego Healthcare System. 2. Insight Data Solutions, Inc. 3. Department of Psychological & Brain Sciences, University of California Santa Barbara.
Abstract
OBJECTIVE: To provide a select review of our applications of quantitative modeling to highlight the utility of such approaches to better understand the neuropsychological deficits associated with various neurologic and psychiatric diseases. METHOD: We review our work examining category learning in various patient populations, including individuals with basal ganglia disorders (Huntington's Disease and Parkinson's disease), amnesia and Eating Disorders. RESULTS: Our review suggests that the use of quantitative models has enabled a better understanding of the learning deficits often observed in these conditions and has allowed us to form novel hypotheses about the neurobiological bases of their deficits. CONCLUSIONS: We feel that the use of neurobiologically inspired quantitative modeling holds great promise in neuropsychological assessment and that future clinical measures should incorporate the use of such models as part of their standard scoring. Appropriate studies need to be completed, however, to determine whether such modeling techniques adhere to the rigorous psychometric properties necessary for a valid and reliable application in a clinical setting. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
OBJECTIVE: To provide a select review of our applications of quantitative modeling to highlight the utility of such approaches to better understand the neuropsychological deficits associated with various neurologic and psychiatric diseases. METHOD: We review our work examining category learning in various patient populations, including individuals with basal ganglia disorders (Huntington's Disease and Parkinson's disease), amnesia and Eating Disorders. RESULTS: Our review suggests that the use of quantitative models has enabled a better understanding of the learning deficits often observed in these conditions and has allowed us to form novel hypotheses about the neurobiological bases of their deficits. CONCLUSIONS: We feel that the use of neurobiologically inspired quantitative modeling holds great promise in neuropsychological assessment and that future clinical measures should incorporate the use of such models as part of their standard scoring. Appropriate studies need to be completed, however, to determine whether such modeling techniques adhere to the rigorous psychometric properties necessary for a valid and reliable application in a clinical setting. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
Authors: J Vincent Filoteo; W Todd Maddox; Alan N Simmons; A David Ing; Xavier E Cagigas; Scott Matthews; Martin P Paulus Journal: Neuroreport Date: 2005-02-08 Impact factor: 1.837
Authors: Megan E Shott; J Vincent Filoteo; Kelly A C Bhatnagar; Nicole J Peak; Jennifer O Hagman; Roxanne Rockwell; Walter H Kaye; Guido K W Frank Journal: Eur Eat Disord Rev Date: 2012-04-10
Authors: Ursula F Bailer; Guido K Frank; Julie C Price; Carolyn C Meltzer; Carl Becker; Chester A Mathis; Angela Wagner; Nicole C Barbarich-Marsteller; Cinnamon S Bloss; Karen Putnam; Nicholas J Schork; Anthony Gamst; Walter H Kaye Journal: Psychiatry Res Date: 2012-11-13 Impact factor: 3.222