192 – Contributed Poster Presentations: SSC
A Time Series-Based Point Estimation of Stop Signal Reaction Times
Annie Dupuis
The Hospital for Sick Children
Michael Escobar
University of Toronto
Keith Knight
University of Toronto
Russell Schacher
The Hospital for Sick Children
Mohsen Soltanifar
University of Toronto
The Stop Signal Reaction Time (SSRT) is a latency measurement for the unobservable human brain stopping process, and was formulated by Logan (1994) without consideration of the nature (go/stop) of trials that precede the stop trials. In 2017, the authors proposed asymptotically equivalent and larger indexes of mixture SSRT and weighted SSRT to address this issue from time in task longitudinal perspective, but estimation based on the time series perspective has still been missing in the literature. To test the hypothesis of no difference between time series based state space estimation of SSRT and Logan 1994 SSRT, two samples of SST data including real dat and the simulated data were considered, and State-space missing data EM algorithm was applied for each subject‘s SST data, encompassing trial order. Using Logan‘s 1994 formulae on ordered SST data, the new state-space SSRT index was calculated. The results for both the real and the simulated data showed that state-space SSRT is significantly larger than Logan‘s 1994 SSRT, mixture SSRT, and weighted SSRT. As a conclusion, SSRT indexes based on the information of the preceding trial type are significantly larger than others.