Get access

Expectations and violations: Delineating the neural network of proactive inhibitory control

Authors

  • Bram B. Zandbelt,

    Corresponding author
    1. Center for Integrative and Cognitive Neuroscience, Department of Psychology, Vanderbilt University, Nashville, Tennessee
    • Rudolf Magnus Magnus Institute of Neuroscience, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
    Search for more papers by this author
  • Mirjam Bloemendaal,

    1. Rudolf Magnus Magnus Institute of Neuroscience, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
    2. Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition, and Behaviour, Radboud University, Nijmegen, The Netherlands
    Search for more papers by this author
  • Sebastiaan F.W. Neggers,

    1. Rudolf Magnus Magnus Institute of Neuroscience, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
    Search for more papers by this author
  • René S. Kahn,

    1. Rudolf Magnus Magnus Institute of Neuroscience, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
    Search for more papers by this author
  • Matthijs Vink

    1. Rudolf Magnus Magnus Institute of Neuroscience, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
    Search for more papers by this author

Correspondence to: Bram B. Zandbelt, Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, Room A.01.126, P.O. Box 85500, 3508 GA Utrecht, The Netherlands. E-mail: bramzandbelt@gmail.com

Abstract

The ability to stop a prepared response (reactive inhibition) appears to depend on the degree to which stopping is expected (proactive inhibition). Functional MRI studies have shown that activation during proactive and reactive inhibition overlaps, suggesting that the whole neural network for reactive inhibition becomes already activated in anticipation of stopping. However, these studies measured proactive inhibition as the effect of stop-signal probability on activation during go trials. Therefore, activation could reflect expectation of a stop-signal (evoked by the stop-signal probability cue), but also violation of this expectation because stop-signals do not occur on go trials. We addressed this problem, using a stop-signal task in which the stop-signal probability cue and the go-signal were separated in time. Hence, we could separate activation during the cue, reflecting expectation of the stop-signal, from activation during the go-signal, reflecting expectation of the stop-signal or violation of that expectation. During the cue, the striatum, the supplementary motor complex (SMC), and the midbrain activated. During the go-signal, the right inferior parietal cortex (IPC) and the right inferior frontal cortex (IFC) activated. These findings suggest that the neural network previously associated with proactive inhibition can be subdivided into two components. One component, including the striatum, the SMC, and the midbrain, activated during the cue, implicating this network in proactive inhibition. Another component, consisting of the right IPC and the right IFC, activated during the go-signal. Rather than being involved in proactive inhibition, this network appears to be involved in processes associated with violation of expectations. Hum Brain Mapp 34:2015–2024, 2013. © 2011 Wiley Periodicals, Inc.

Ancillary