Abstract
Dual-task paradigms typically impair performance relative single-task paradigms. However, research on the attentional boost effect (ABE) suggests that dual-task performance is improved to that of single-task performance on critical trials (when a response is required). The response leads to improved memory for the simultaneously presented scene, relative to a single-task. Research suggests that responding to a subset of stimuli results in increased attention, leading the to better memory for the associated memory items. In an attempt to better understand the role of attention in the ABE, we measured eye movements during a typical ABE task. Therefore, the current study sought to replicate the ABE and document the pattern of eye movements associated with critical and non-critical trials. In three experiments, participants encoded real-world scenes with a circle in the center. Divided attention (DA) participants pressed a button when the circle was a non-prevalent color, and full attention (FA) participants ignored the circles. All participants completed a recognition memory test after a delay. Replicating previous ABE studies, Experiment 1 used a 1000ms encoding time and a two-alternative-forced-choice recognition test, Experiment 2 used 1000ms encoding time and a single-item recognition test, and Experiment 3 used a 500ms encoding time and a single-item recognition test. Behavioral results revealed no differences between FA and DA in the first two experiments and a DA impairment in Experiment 3. No ABE was observed in any of the three experiments. Across three experiments, dwell times during test were longer for the FA condition compared to DA condition. There were no differences during encoding, and no differences for critical versus non-critical trials. Overall, these experiments suggest that the ABE is not robust. The lack of an ABE is consistent with the lack of allocation of attention differences, as measured by eye movements, on critical versus non-critical trials.
Meeting abstract presented at VSS 2017