A cognitive neuroscience based computerized battery for efficient measurement of individual differences: Standardization and initial construct validation
“A cognitive neuroscience based computerized battery for efficient measurement of individual differences: Standardization and initial construct validation” Ruben C. Gur, et. al. J Neurosci Methods. 2010 March 30; 187(2): 254–262. doi:10.1016/j.jneumeth.2009.11.017.
There is increased need for efficient computerized methods to collect reliable data on a range of cognitive domains that can be linked to specific brain systems. Such need arises in functional neuroimaging studies, where individual differences in cognitive performance are variables of interest or serve as confounds. In genetic studies of complex behavior, which require particularly large samples, such trait measures can serve as endophenotypes. Traditional neuropsychological tests, based on clinical pathological correlations, are protracted, require extensive training in administration and scoring, and leave lengthy paper trails (double-entry for analysis). We present a computerized battery that takes an average of 1 hour and provides measures of accuracy and speed on 9 neurocognitive domains. They are cognitive neuroscience-based in that have been linked experimentally to specific brain systems with functional neuroimaging studies. We describe the process of translating tasks used in functional neuroimaging to tests for assessing individual differences. Data are presented on each test with samples ranging from 139 (81 female) to 536 (311 female) of carefully screened healthy individuals ranging in age from 18 to 84. Item consistency was established with acceptable to high Cronbach alpha coefficients. Inter-item correlations were moderate to high within domain and low to nil across domains, indicating construct validity. Initial criterion validity was demonstrated by sensitivity to sex differences and the effects of age, education and parental education. These results encourage the use of this battery in studies needing an efficient assessment of major neurocognitive domains such as multisite genetic studies and clinical trials.