Brain event-related potentials predict individual differences in inhibitory control

L.M. Rueda-Delgado, L. O'Halloran, N. Enz, K.L. Ruddy, H. Kiiski, M. Bennett, F. Farina, L. Jollans, N. Vahey, R. Whelan

Research output: Contribution to journalArticlepeer-review

15 Citations (Scopus)


Stop-signal reaction time (SSRT), the time needed to cancel an already-initiated motor response, quantifies individual differences in inhibitory control. Electrophysiological correlates of SSRT have primarily focused on late event-related potential (ERP) components over midline scalp regions from successfully inhibited stop trials. SSRT is robustly associated with the P300, there is mixed evidence for N200 involvement, and there is little information on the role of early ERP components. Here, machine learning was first used to interrogate ERPs during both successful and failed stop trials from 64 scalp electrodes at 4 ms resolution (n = 148). The most predictive model included data from both successful and failed stop trials, with a cross-validated Pearson's r of 0.32 between measured and predicted SSRT, significantly higher than null models. From successful stop trials, spatio-temporal features overlapping the N200 in right frontal areas and the P300 in frontocentral areas predicted SSRT, as did early ERP activity (
Original languageEnglish
Pages (from-to)22-34
Early online date21 Apr 2019
Publication statusPublished - May 2021
Externally publishedYes


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