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“Computational Modeling of Task Switching Behavior”
Investigator: Prof. Joseph Orr Texas A&M University
Department of Psychological and Brain Sciences
The ability to flexibly adapt one’s behavior to changing goals and environmental information is a hallmark of the human mind. However, experimental studies have shown that people are less efficient when switching between two tasks than when they repeat the same task. It is believed that this loss in efficiency during task switching (called a “switch cost”) is caused by two components – the time it takes to prepare for the new task’s rules, and your mind being preoccupied by the old task’s rules. However, traditional behavioral measures (such as reaction time) make it hard to tease those two components apart. Instead, the study you participated in will use computational modeling to attempt to measure the two components individually.
How was this tested?
In this experiment you performed two different tasks and were asked to switch randomly between them. You may have been told which task to perform on each trial, or you may have been able to choose which task to perform. We plan to use a computational model, called the Drift Diffusion Model (Ratcliff 1978), to test different hypotheses that attempt to explain switch costs. The model constructs a timeline of your decision-making based on your responses. We aim to see if we can measure how quickly you prepare for the new task and how easily you forget the old task when you switch between tasks. By generating a testable model we can better evaluate the factors thought to influence flexible behavior.
What if I want to know more?
If you are interested in learning more about the ideas underlying this study, you may want to read the work of Dr. Orr (http://congalab.sites.tamu.edu/). You can email Dr. Joseph Orr (email@example.com) if you have additional questions. If you would like to receive a report of this research when it is completed (or a summary of the findings), please contact Dr. Orr.
Please do not disclose research procedures and hypotheses to anyone who might participate in this study as this could affect the results of the study.
IRB NUMBER: IRB2019-0036
IRB APPROVAL DATE: 02/07/2019