Evaluating individual differences in selection history bias for goal-directed reaching movements

Individuals vary in their cognitive abilities. For instance, they differ in their ability to engage and disengage attentional resources associated with target and distractor processing. These abilities can play a critical role in influencing visual search performance across trials. However, whether these individual differences in target and distractor processing influence selection history have not received much attention. Filling this gap, here we attempted to investigate selection history with the perspective of individual differences. Participants performed a modified version of the priming-of-popout task, while we recorded their continuous reach trajectory. Continuous trajectory provides a behavioral measure that captures the online dynamics between target and distractor competition as the target selection unfolds. To assess the relative contributions of target facilitation and distractor inhibition, in addition to conventional full-repetition (repeating target and distractor colors on subsequent trials) and full-swap conditions (swapping target and distractor colors on subsequent trials), we added the partial-repetition and partial-swap conditions. In the partial-repetition conditions, the target color remained unchanged, while the distractor was in new color, or vice versa; in the partial-swap conditions, target color was the distractor color of the preceding trial while distractor was in new color, or vice versa (Eimer et al., 2010). The maximum curvature scores from these conditions were submitted to t-SNE for dimensionality reduction and a subsequent k-means clustering. These steps resulted in three distinct clusters (sub-groups). These sub-groups demonstrated distinct patterns of attraction score profiles indicating three different strategies in processing target and distractor information: a) relying more on previous distractors, b) relying more on previous target, and c) relying on both. Participants in the third sub-group showed larger priming-of-pop effect compared to first two sub-groups. To further understand the mechanism underlying these individual differences, we aim to use the neurobiologically-inspired CoRLEGO model to simulate these results and estimate model parameters.