A Time Series-Based Point Estimation of Stop Signal Reaction Times: More Evidence on the Role of Reactive Inhibition-Proactive Inhibition Interplay on the SSRT Estimations

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. Two asymptotically equivalent and larger indices of mixture SSRT a...

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Main Authors: Mohsen Soltanifar, Keith Knight, Annie Dupuis, Russell Schachar, Michael Escobar
Format: Article
Language:English
Published: MDPI AG 2020-08-01
Series:Brain Sciences
Subjects:
Online Access:https://www.mdpi.com/2076-3425/10/9/598
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author Mohsen Soltanifar
Keith Knight
Annie Dupuis
Russell Schachar
Michael Escobar
author_facet Mohsen Soltanifar
Keith Knight
Annie Dupuis
Russell Schachar
Michael Escobar
author_sort Mohsen Soltanifar
collection DOAJ
description 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. Two asymptotically equivalent and larger indices of mixture SSRT and weighted SSRT were proposed in 2017 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. A time series-based state space estimation of SSRT was presented and it was compared with Logan 1994 SSRT over two samples of real Stop Signal Task (SST) data and the simulated SST data. The results showed that time series-based SSRT is significantly larger than Logan’s 1994 SSRT consistent with former Longitudinal-based findings. As a conclusion, SSRT indices considering the after effects of inhibition in their estimation process are larger yielding to hypothesize a larger estimates of SSRT using information on the reactive inhibition, proactive inhibition and their interplay in the SST data.
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spelling doaj.art-fa012088ab5e4d58899b123160ee2fee2023-11-20T11:49:10ZengMDPI AGBrain Sciences2076-34252020-08-0110959810.3390/brainsci10090598A Time Series-Based Point Estimation of Stop Signal Reaction Times: More Evidence on the Role of Reactive Inhibition-Proactive Inhibition Interplay on the SSRT EstimationsMohsen Soltanifar0Keith Knight1Annie Dupuis2Russell Schachar3Michael Escobar4Biostatistics Division, Dalla Lana School of Public Health, University of Toronto, 620, 155 College Street, Toronto, ON M5T 3M7, CanadaDepartment of Statistical Sciences, University of Toronto, 6018, Sidney Smith Hall, 100 St. George Street, Toronto, ON M5S 3G3, CanadaBiostatistics Division, Dalla Lana School of Public Health, University of Toronto, 620, 155 College Street, Toronto, ON M5T 3M7, CanadaThe Hospital for Sick Children, Psychiatry Research, 4274, 4th Floor, Black Wing, 555 University Avenue, Toronto, ON M5G 1X8, CanadaBiostatistics Division, Dalla Lana School of Public Health, University of Toronto, 620, 155 College Street, Toronto, ON M5T 3M7, CanadaThe 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. Two asymptotically equivalent and larger indices of mixture SSRT and weighted SSRT were proposed in 2017 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. A time series-based state space estimation of SSRT was presented and it was compared with Logan 1994 SSRT over two samples of real Stop Signal Task (SST) data and the simulated SST data. The results showed that time series-based SSRT is significantly larger than Logan’s 1994 SSRT consistent with former Longitudinal-based findings. As a conclusion, SSRT indices considering the after effects of inhibition in their estimation process are larger yielding to hypothesize a larger estimates of SSRT using information on the reactive inhibition, proactive inhibition and their interplay in the SST data.https://www.mdpi.com/2076-3425/10/9/598stop signal reaction timesestimationafter effects of inhibitionreactive inhibitionproactive inhibition
spellingShingle Mohsen Soltanifar
Keith Knight
Annie Dupuis
Russell Schachar
Michael Escobar
A Time Series-Based Point Estimation of Stop Signal Reaction Times: More Evidence on the Role of Reactive Inhibition-Proactive Inhibition Interplay on the SSRT Estimations
Brain Sciences
stop signal reaction times
estimation
after effects of inhibition
reactive inhibition
proactive inhibition
title A Time Series-Based Point Estimation of Stop Signal Reaction Times: More Evidence on the Role of Reactive Inhibition-Proactive Inhibition Interplay on the SSRT Estimations
title_full A Time Series-Based Point Estimation of Stop Signal Reaction Times: More Evidence on the Role of Reactive Inhibition-Proactive Inhibition Interplay on the SSRT Estimations
title_fullStr A Time Series-Based Point Estimation of Stop Signal Reaction Times: More Evidence on the Role of Reactive Inhibition-Proactive Inhibition Interplay on the SSRT Estimations
title_full_unstemmed A Time Series-Based Point Estimation of Stop Signal Reaction Times: More Evidence on the Role of Reactive Inhibition-Proactive Inhibition Interplay on the SSRT Estimations
title_short A Time Series-Based Point Estimation of Stop Signal Reaction Times: More Evidence on the Role of Reactive Inhibition-Proactive Inhibition Interplay on the SSRT Estimations
title_sort time series based point estimation of stop signal reaction times more evidence on the role of reactive inhibition proactive inhibition interplay on the ssrt estimations
topic stop signal reaction times
estimation
after effects of inhibition
reactive inhibition
proactive inhibition
url https://www.mdpi.com/2076-3425/10/9/598
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