A systematic analysis of Event-Related brain Potential parameterisations for Individual Differences Research (ERP4IDR)

• Applicant: Cassie Short, Ph.D.
• Subject Area: Biological Psychology and Cognitive Neuroscience ; Personality Psychology, Clinical and Medical Psychology, Methodology
• Term: since 2026
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 571787605

The precise temporal resolution of event-related brain potentials (ERPs) enables analysis of specific neural processes associated with individual differences in cognition, emotion and behaviour. However, the field of electroencephalogram (EEG) individual differences research suffers from a replicability crisis, and efforts to remedy this unsatisfactory situation often neglect a core methodological limitation that substantially undermines the validity and replicability of inferences. The conventional one-size-fits-all approach to defining the temporal and spatial domains in which ERPs are measured across trials fails to account for well-documented between- and within-person variability of the cognitive processes that are associated with time-locked events. Failure to capture these between- and within-person variations in ERPs is particularly troubling in a scientific field committed to unravelling between-person differences and threatens to compromise the validity and replicability of inferences. The overarching objective of the proposed project is to improve the validity and replicability of EEG estimates through comprehensive evaluation and development of single trial and person specific parameterisation algorithms. This will be achieved through the completion of three work packages on an existing large and multivariate EEG dataset that I collected together with the CoScience team previously, two open access datasets, and simulated datasets: (1) systematically analyse prominent single trial EEG parameterisation algorithms, assessing reliability, bias and theoretical plausibility, in comparison to each other, to individual non-single-trial approaches, and to one-size-fits-all approaches; (2) assess the robustness of the reliability, bias and theoretical plausibility of EEG signal estimates across algorithms to variation in data preprocessing and analysis strategies; and (3) develop and validate a novel single trial EEG parameterisation algorithm, and assess generalisation across components and tasks. This work can make significant advances in the field of EEG individual differences research through advancement in algorithmic precision and will lay novel methodological foundations for future advances in the field.

• DFG Programme: Research Grants
• International Connection: China (Hong Kong)
• Co-Investigators: Professor Dr. Martin Bleichner; Professor Dr. Stefan Debener; Professorin Dr. Andrea Hildebrandt
• Cooperation Partner: Dr. Guang Ouyang