Book contents
- Frontmatter
- Contents
- Contributors
- Preface
- 1 Principles and Consequences of the Initial Visual Encoding
- 2 Measuring Multisensory Integration in Selected Paradigms
- 3 Fechnerian Scaling: Dissimilarity Cumulation Theory
- 4 Mathematical Models of Human Learning
- 5 Formal Models of Memory Based on Temporally-Varying Representations
- 6 Statistical Decision Theory
- 7 Modeling Response Inhibition in the Stop-Signal Task
- 8 Approximate Bayesian Computation
- 9 Cognitive Diagnosis Models
- 10 Encoding Models in Neuroimaging
- Index
7 - Modeling Response Inhibition in the Stop-Signal Task
Published online by Cambridge University Press: 20 April 2023
- Frontmatter
- Contents
- Contributors
- Preface
- 1 Principles and Consequences of the Initial Visual Encoding
- 2 Measuring Multisensory Integration in Selected Paradigms
- 3 Fechnerian Scaling: Dissimilarity Cumulation Theory
- 4 Mathematical Models of Human Learning
- 5 Formal Models of Memory Based on Temporally-Varying Representations
- 6 Statistical Decision Theory
- 7 Modeling Response Inhibition in the Stop-Signal Task
- 8 Approximate Bayesian Computation
- 9 Cognitive Diagnosis Models
- 10 Encoding Models in Neuroimaging
- Index
Summary
Response inhibition refers to an organism’s ability to suppress unwanted impulses, or actions and responses that are no longer required or have become inappropriate.In the stop-signal task, participants perform a response time task (go task), and occasionally, the go stimulus is followed by a stop signal after a variable delay, indicating subjects to withhold their response (stop task). The main interest of modeling is in estimating the unobservable latency of the stopping process as a characterization of the response inhibition mechanism. Here we analyze and compare the underlying assumptions of different models, including parametric and non-parametric versions of the race model. New model classes based on the concept of copulas are introduced and a number of unsolved problems facing all existing models are pointed out.
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- Information
- New Handbook of Mathematical Psychology , pp. 311 - 356Publisher: Cambridge University PressPrint publication year: 2023
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