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Updated: Apr 30, 2026

The Attentional Set Shifting Task: A Measure of Cognitive Flexibility in Mice
Published on: February 4, 2015
People are sensitive to environmental predictability when engaging cognitive control
Kaichi Yanaoka1, Hiroyuki Tsubomi2, Félice van 't Wout3
1Osaka Kyoiku University, 4-88 Minami Kawahoricho, Osaka, Tennoji, 543-0054, Japan. makifactor@gmail.com.
Abstract:
People flexibly engage either proactive or reactive control to achieve goals in dynamic environments. However, it remains unclear how specific environmental factors determine when proactive control is most effectively used. Across two experiments, this study investigated how environmental predictability influences proactive control. We employed a self-paced task-switching paradigm in which adult participants triggered the target when they felt ready to respond to it and manipulated how reliably contextual cue information predicted the task rule. In Experiment 1, a fully predictable environment (100% cue reliability) led to longer preparation times, reflecting spontaneous proactive preparation, faster responses, and reduced switch costs compared with an unpredictable environment (50% reliability), indicating adaptive engagement of proactive control based on cue reliability. Experiment 2 further examined the relations between cue reliability and proactive control by comparing a more reliable condition (85% reliable cues) to a less reliable condition (65% reliable cues). Findings revealed that participants spent more time preparing under 85% reliability and showed larger performance differences between "matched" (cue accurately predicting the task) and "unmatched" trials. These results reinforce the view that adults can detect subtle differences in cue reliability and adjust their proactive control accordingly. Finally, an integration of the findings from Experiments 1 and 2 suggests that two thresholds of cue reliability govern both the decision to engage and the effectiveness of cognitive control when adults modulate their proactive control based on environmental predictability.
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