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The Journal of Neuroscience, January 25, 2006, 26(4):1211-1218; doi:10.1523/JNEUROSCI.3887-05.2006

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Behavioral/Systems/Cognitive
Prefrontal Set Activity Predicts Rule-Specific Neural Processing during Subsequent Cognitive Performance

Katsuyuki Sakai^1,2 and Richard E. Passingham^2,3

¹Department of Cognitive Neuroscience, Graduate School of Medicine, The University of Tokyo, Bunkyo-ku, Tokyo 113-0033, Japan, ²Wellcome Department of Imaging Neuroscience, Institute of Neurology, London WC1N 3BG, United Kingdom, and ³Department of Experimental Psychology, University of Oxford, Oxford OX1 3UD, United Kingdom

Correspondence should be addressed to Katsuyuki Sakai, Department of Cognitive Neuroscience, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan. Email: ksakai{at}m.u-tokyo.ac.jp

Prefrontal neurons have been shown to represent task rules. Here we show the mechanisms by which the rule-selective activity in the prefrontal cortex influences subsequent cognitive performance based on that rule. Using functional magnetic resonance imaging, we found that the frontopolar cortex interacted with posterior areas differently depending on whether subjects were going to perform a phonological or semantic task. Moreover, we found that the sustained "set" activity in this region predicted the activity that could be recorded in the posterior areas during the performance, as well as the speed of that performance. We argue that the prefrontal set activity does not reflect simple maintenance of the task rules but the process of implementing the rule for subsequent cognitive performance and that this is done through rule-selective interactions with areas involved in execution of the tasks.

Key words: prefrontal cortex; fMRI; cognition; connectivity; human; behavior

---

Received Sept. 14, 2005; revised Nov. 30, 2005; accepted Dec. 12, 2005.

Correspondence should be addressed to Katsuyuki Sakai, Department of Cognitive Neuroscience, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan. Email: ksakai{at}m.u-tokyo.ac.jp

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