Abstract
Many studies suggest that the motion aftereffect (MAE) is modulated by attention: MAEs are reduced if attention is diverted from the adaptation stimulus by a demanding task at fixation (e.g. Chaudhuri, 1990; Taya et al., 2009). However, a series of null findings (Morgan, 2011, 2012, 2013) suggest that previous reports of attentional modulation may be due to response bias. Nonetheless, we previously found attentional modulation in a paradigm designed to eliminate response bias (Bartlett, Adams & Graf, 2016). To better understand the conditions under which attention modulates the MAE, we conducted a meta-analysis of the behavioural literature that included 98 effect sizes across 42 independent samples. Overall, attention significantly and substantially modulated the MAE; this was a very large effect (Cohen's d=0.99, p< .001). Various characteristics of the adaptation and test stimuli affected this modulation: Significantly larger attentional effects were found for (i) simple (translational) motion vs. complex motion, (ii) dynamic vs. static test stimuli, (iii) greater eccentricity (minimum distance from fixation) and (iv) smaller maximum diameter. Are reported effects of attention inflated by response bias? Bias should be minimised in studies that (i) used naïve observers, (ii) measured the magnitude (vs. duration) of the MAE, and (iii) employed 2AFC tasks. However, none of these factors significantly modulated the effect. In fact, there was a trend for studies with only naïve observers to report larger effects. It is unlikely, therefore, that response bias plays a substantial role in reported effects of attention. The effect of attention on the MAE is large and best explained by a multiple moderator model that includes (i) motion type (simple vs. complex), (ii) stimulus eccentricity, (iii) stimulus maximum diameter and (iv) subject naivety. This model included 39 effect sizes (the subset for which all moderators were reported) and accounted for 49% of variance in effect size.
Meeting abstract presented at VSS 2017