A computational approach to the N-back task

The N -back task is one of the most popular paradigms for studying thecognitive mechanisms of working memory (WM). The task requires the observer to viewa sequence of stimuli and judge whether the current stimulus (probe) matches the onepresented N stimuli ago (target). A key phenomenon is that the intervening stimuli (distractors) interfere with task performance. Unfortunately, the classic N -back task usescomplex categorical stimuli, making it unfit to quantify the effect of feature similarity oninterference strength. Here, we introduce the “analog N -back task", which utilizes stimuli varying continuously in orientation or color. This task variant enables us to measureinterference strength on a continuum, providing data suitable for identifying the sourcesof interference using computational models. In the analog 2-back task, we found thatinterference increased with feature similarity between the probe and both task-relevant(1-back) and task-irrelevant (3-back) distractors. We next developed and evaluated threemain models that each incorporated a Bayesian decision step and differed from an optimal non-interference model in one component only: an early-pooling model, a late-poolingmodel, and a substitution model. Model comparison suggests that interference emerges late in processing, most likely due to confusion between stimuli during WM retrieval. Ourwork puts the study of interference in the N -back task on a firmer computational footing and provides a unified framework for examining the sources of interference acrossdomains.