Literature DB >> 26100657

Neuroimaging as a biomarker in symptom validity and performance validity testing.

Erin D Bigler1.   

Abstract

How neuropsychological assessment findings are deemed valid has been a topic of numerous articles but few have addressed any role that neuroimaging studies could provide. Within military and various clinical samples of individuals undergoing neuropsychological evaluations, high levels of failure on measures of symptom validity testing (SVT) and/or performance validity testing (PVT) have been reported. Where 'failure' is defined as a below cut-score performance on some pre-determined set-point on a SVT/PVT measure, are such failures always indicative of invalid test findings or are there other explanations, especially based on informative neuroimaging findings? This review starts with the premise that even though the SVT/PVT task is designed to be simple and easy to perform, it nonetheless requires intact frontoparietal attention, working memory and task engagement (motivation) networks. If there is damage or pathology within any aspect of these networks as demonstrated by neuroimaging findings, the patient may perform below the cut-point as a result of the underlying damage or pathophysiology. The argument is made that neuroimaging findings should be considered as to where SVT/PVT cut-points are established and there should be much greater flexibility in SVT/PVT measures based on other personal, demographic and neuroimaging information. Several case studies are used to demonstrate these points.

Entities:  

Keywords:  Cognitive neuroscience of effort; Effort; Neuroimaging; Performance validity testing; Symptom validity testing

Mesh:

Year:  2015        PMID: 26100657     DOI: 10.1007/s11682-015-9409-1

Source DB:  PubMed          Journal:  Brain Imaging Behav        ISSN: 1931-7557            Impact factor:   3.978


  2 in total

1.  Failed Performance on the Test of Memory Malingering and Misdiagnosis in Individuals with Early-Onset Dysexecutive Alzheimer's Disease.

Authors:  Nick Corriveau-Lecavalier; Eva C Alden; Nikki H Stricker; Mary M Machulda; David T Jones
Journal:  Arch Clin Neuropsychol       Date:  2022-08-23       Impact factor: 3.448

2.  Application of Medical Imaging Based on Deep Learning in the Treatment of Lumbar Degenerative Diseases and Osteoporosis with Bone Cement Screws.

Authors:  Shengkai Mu; Jingxu Wang; Shuyi Gong
Journal:  Comput Math Methods Med       Date:  2021-10-11       Impact factor: 2.238

  2 in total

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