Ex-Gaussian analysis of simple response time as a measure of information processing speed and the relationship with brain morphometry in multiple sclerosis

被引:4
|
作者
Mui, Michelle [1 ]
Ruben, Ray M. [2 ]
Ricker, Timothy J. [3 ]
Dobryakova, Ekaterina [4 ,5 ]
Sandry, Joshua [1 ]
机构
[1] Montclair State Univ, Dept Psychol, 1 Normal Ave, Montclair, NJ 07043 USA
[2] Kessler Fdn, Ctr Neuropsychol & Neurosci Res, 120 Eagle Rock Ave,Suite 100, E Hanover, NJ 07936 USA
[3] Univ South Dakota, Dept Psychol, 414 Clark St, Vermillion, SD 57069 USA
[4] Kessler Fdn, Ctr Traumat Brain Injury Res, E Hanover, NJ USA
[5] Rutgers New Jersey Med Sch Newark, Dept Phys Med & Rehabil, Newark, NJ USA
关键词
Multiple sclerosis; Cognition; Information processing speed; Demyelinating diseases; Response time; Ex-Gaussian; DIGIT MODALITIES TEST; INTRAINDIVIDUAL VARIABILITY; FUNCTIONAL COMPOSITE; PASAT; PERFORMANCE; DISTRIBUTIONS; SEGMENTATION; DYSFUNCTION; DEMENTIA;
D O I
10.1016/j.msard.2022.103890
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
Background: The polyfactorial nature of the widely used symbol digit modalities test (SDMT) introduces significant measurement challenges in characterizing information processing speed (IPS) deficits in multiple sclerosis (MS). Measures with high psychometric IPS-specificity and less contamination from other cognitive domains are necessary to fully understand IPS changes. Objective: Investigate how three mathematical modeling ex-Gaussian parameter estimates (mu, sigma, tau) derived from a simple response time (RT) task (1) differentiate MS from healthy control participants and (2) correspond to structural brain changes, to evaluate a novel IPS measurement approach. Methods: Persons with and without MS completed a two-minute behavioral simple RT task, structural MRI and the MS functional composite. RT distributions were deconvolved into ex-Gaussian parameter estimates using mathematical modeling. Group differences and brain-behavior relationships were statistically evaluated. Results: Persons with MS experienced a general pattern of slowing as evidenced by a shift in the Gaussian (mu) component of the distribution. This correlated with whole brain volume and white matter specifically. Additionally, persons with MS had larger values of tau (elongated positively skewed tail) that may reflect attentional lapses. Conclusion: The ex-Gaussian approach is sensitive to disease-related IPS changes and provides nuanced information about IPS slowing in MS.
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页数:7
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