Our goal was to identify the neural correlates of successful inhibitory control. We distinguished four trial outcomes: go success (GS), go error (GE), stop success (SS), and stop error (SE), and modeled BOLD signals by convolving the onsets of the go signal a canonical hemodynamic response function (HRF) and the temporal derivative of the canonical HRF. Realignment parameters in all 6 dimensions were entered in the model. Serial autocorrelation of the time series was corrected by a first degree autoregressive or AR(1) model. The data were high-pass filtered (1/128 Hz cutoff) to remove low-frequency signal drifts.
