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Stopping a Continuous Movement: A Novel Approach to Investigating Inhibitory Control.

Kelsey E SchultzDominique DenningVanessa HufnagelNicole C Swann
Published in: Journal of cognitive neuroscience (2023)
Flexible, adaptive behavior is critically dependent on inhibitory control. For example, if you suddenly notice you are about to step on a tack and would prefer not to, the ability to halt your ongoing movement is critical. However, this behavior is usually not probed by current inhibitory control tasks, which often focus instead on inhibiting a movement before its initiation. To address limitations in existing approaches for studying termination of an ongoing movement, we developed a novel stop task with which we can directly observe and compare prepared and reactive termination of a continuous movement. Here, we present and evaluate our novel continuous movement stop task (CMST) and compare task performance to performance on the traditional stop signal task. Our data reveal that the CMST effectively dissociates planned and unplanned stopping behaviors. We found that participants initiated and completed stopping significantly earlier on planned compared with unplanned stop trials and that the variability for each measure was greater for planned compared with unplanned stop trials. In addition, we found that the time at which participants initiated the stopping process was more variable than the time it took participants to complete the stopping process. We also found that participants slowed before stopping significantly more on planned than unplanned stop trials. Finally, our data suggest that preparatory mechanisms may be similar between the two tasks, but the tasks were not related by any other measure. The unambiguous quantification of prepared and reactive stopping behavior provided by the CMST will help support future investigation of different kinds of stopping behavior.
Keyphrases
  • working memory
  • machine learning
  • big data
  • genome wide
  • single cell
  • deep learning
  • drug induced