Exploring a Dynamic Template Matching Algorithm for the Automatic Extraction of P3 Latencies.

ABSTRACT: In this study, we explore a novel template matching algorithm using the grand average as a dynamic template to extract P3 latencies. This new algorithm outperforms peak latency and fractional area latency algorithms in both empirical as well as simulated data. A modified fractional area latency algorithm proposed by Liesefeld (2016, 2018) performed best among all previously employed approaches. It matched the performance of the template matching algorithms in the empirical data, but performed worse in the simulation. Template matching algorithms showed high agreement (ICC = 0.89) with latencies extracted by expert researchers and the most accurate recovery of simulated latency shifts (ICC = 0.91). Our results highlight the robustness of template matching algorithms across various tasks, pr

SUBMITTER: Lesche S 

PROVIDER: S-EPMC12728138 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature