Originating in computer science in the 1950’s, executive function is now an important concept in behavioral sciences. This Tool paper examines the core definitions of executive function, and how that relates to free, willed choices in human behavior. We contrast this with cognitive assessment methods that tend to push test takers into convergent thinking. We show how a common form of cognitive test used in behavioral sciences to measure executive functioning, the Trail Making Test, can be altered so that it requires divergent thinking. To analyze and summarize performance of multiple, individual, free choices we apply statistical methods taken from computer science to test for randomness. The tool presented, the Choice Trails Test, and the proposed analysis method, allow for novel ways to investigate top-down, executive, cognitive control using a simple paper-and-pencil test. The benefit of this approach is that it produces indices of performance that are closely aligned with the essential meaning of executive functions. Additionally, this method provides a denser data set than traditional methods that examine total performance metrics. Denser data allows for analysis that is consistent with traditional approaches to examining task performance in cognitive science that stress continuous analysis of processes across tasks.

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Executive Cognitive Control of Free Choices

  • Graham Pluck,
  • Fei Gu,
  • Natasha Asawanuchit,
  • Suphasiree Chantavarin

摘要

Originating in computer science in the 1950’s, executive function is now an important concept in behavioral sciences. This Tool paper examines the core definitions of executive function, and how that relates to free, willed choices in human behavior. We contrast this with cognitive assessment methods that tend to push test takers into convergent thinking. We show how a common form of cognitive test used in behavioral sciences to measure executive functioning, the Trail Making Test, can be altered so that it requires divergent thinking. To analyze and summarize performance of multiple, individual, free choices we apply statistical methods taken from computer science to test for randomness. The tool presented, the Choice Trails Test, and the proposed analysis method, allow for novel ways to investigate top-down, executive, cognitive control using a simple paper-and-pencil test. The benefit of this approach is that it produces indices of performance that are closely aligned with the essential meaning of executive functions. Additionally, this method provides a denser data set than traditional methods that examine total performance metrics. Denser data allows for analysis that is consistent with traditional approaches to examining task performance in cognitive science that stress continuous analysis of processes across tasks.