Optimal performance in a countermanding saccade task

Kong Fatt Wong-Lin, Philip Eckhoff, Philip Holmes, Jonathan D. Cohen

Research output: Contribution to journalArticlepeer-review

25 Scopus citations


Countermanding an action is a fundamental form of cognitive control. In a saccade-countermanding task, subjects are instructed that, if a stop signal appears shortly after a target, they are to maintain fixation rather than to make a saccade to the target. In recent years, recordings in the frontal eye fields and superior colliculus of behaving non-human primates have found correlates of such countermanding behavior in movement and fixation neurons. In this work, we extend a previous neural network model of countermanding to account for the high pre-target activity of fixation neurons. We propose that this activity reflects the functioning of control mechanisms responsible for optimizing performance. We demonstrate, using computer simulations and mathematical analysis, that pre-target fixation neuronal activity supports countermanding behavior that maximizes reward rate as a function of the stop signal delay, fraction of stop signal trials, intertrial interval, duration of timeout, and relative reward value. We propose experiments to test these predictions regarding optimal behavior.

Original languageEnglish (US)
Pages (from-to)178-187
Number of pages10
JournalBrain Research
StatePublished - Mar 8 2010

All Science Journal Classification (ASJC) codes

  • Clinical Neurology
  • Molecular Biology
  • General Neuroscience
  • Developmental Biology


  • Cognitive control
  • Computational modeling
  • Frontal eye fields
  • Optimal performance
  • Reward rate
  • Saccade-countermanding task


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