TY - JOUR
T1 - Ex-Gaussian analysis of simple response time as a measure of information processing speed and the relationship with brain morphometry in multiple sclerosis
AU - Mui, Michelle
AU - Ruben, Ray M.
AU - Ricker, Timothy J.
AU - Dobryakova, Ekaterina
AU - Sandry, Joshua
N1 - Publisher Copyright:
© 2022 Elsevier B.V.
PY - 2022/7
Y1 - 2022/7
N2 - 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.
AB - 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.
KW - Cognition
KW - Demyelinating diseases
KW - Ex-Gaussian
KW - Information processing speed
KW - Multiple sclerosis
KW - Response time
UR - http://www.scopus.com/inward/record.url?scp=85130937059&partnerID=8YFLogxK
U2 - 10.1016/j.msard.2022.103890
DO - 10.1016/j.msard.2022.103890
M3 - Article
C2 - 35640465
AN - SCOPUS:85130937059
SN - 2211-0348
VL - 63
JO - Multiple Sclerosis and Related Disorders
JF - Multiple Sclerosis and Related Disorders
M1 - 103890
ER -