Superior performance by two new methods in identifying the online reaction time of reaching movements.

Reaching movements can be redirected during their progress to handle unexpected visual changes, such as a change in target location. It is important to know when these redirections start, i.e., the online reaction time (oRT), but this information is not readily evident since redirections are embedded within a time-varying baseline movement that differs from trial to trial. The one previous study that evaluated the performance of different oRT identification methods utilized simulated redirections with the exact same onset, rather than a range of onsets as would be typically encountered. We addressed this gap by utilizing batches of "hybrid" trials with temporal spread in their oRTs. Each hybrid trial combined a sampled baseline movement with an idealized corrective response. Two new methods had the most accurate identification of online reaction times: ) a threshold-aligned grand mean regression, and ) a template-based approach we term the canonical correction search. The threshold-aligned grand mean regression is simple to implement and effective. The canonical correction search is a more complex procedure but arguably better linked to the underlying response. Applying the two methods to a published dataset revealed more delayed oRTs than was previously reported along with new information such as the width of oRT distributions. Taken together, our results demonstrate the utility of two new methods for dissecting corrective action from ongoing movement. Advancing our understanding of visual feedback control requires methods that accurately identify the onset of corrective action. We developed a modified regression approach and a template-based approach to identify the online reaction time of single-reaching movements. Both outperform previous methods when challenged by temporal jitter in the response onset and increased background noise.