ABSTRACT
Emotional material is commonly reported to be more accurately recognised; however, there is substantial evidence of increased false alarm rates (FAR) for emotional material and several reports of stronger influences on response bias than accuracy. This pattern is more frequently reported for words than pictures. Research on the mechanisms underlying bias differences has mostly focused on word lists under short retention intervals. This article presents four series of experiments examining recognition memory for emotional pictures while varying arousal and the control over the content of the pictures at two retention intervals, and one study measuring the relatedness of the series picture sets. Under the shorter retention interval, emotion increased false alarms and reduced accuracy. Under the longer retention interval emotion increased hit rates and FAR, resulting in reduced accuracy and/or bias. At both retention intervals, the pattern of valence effects differed based on the arousal associated with the picture sets. Emotional pictures were found to be more related than neutral pictures in each set; however, the influence of relatedness alone does not provide an adequate explanation for all emotional differences. The results demonstrate substantial emotional differences in picture recognition that vary based on valence, arousal and retention interval.
Acknowledgements
I thank Marc Howard for his helpful comments on earlier versions of this article. I also thank Youssef Amin, Meredith Atwater, Adam Chafee, Meghan Chasse-Perry, Marissa Cutter, Scott Halpern, Ella Kaiser, Casey Lauser, Isabella Moreno-King, Lindsay Osgood, Laurie Pochette, Erin Strahley and Hannah Trad for their vital help with participant recruitment and testing. Finally, I thank the two reviewers of this manuscript for their insightful comments and suggestions.
Disclosure statement
No potential conflict of interest was reported by the authors.
Notes
1 d′ = z(HR) − z(FAR).
2 c′ = −0.5 [z(HR) + z(FAR)].
3 Participants’ data were excluded based on the same criteria in every series.
4 Ag = ½ ∑(Fi + 1 − Fi)( Hi + 1 − Hi); where the index i tracks the ROC points so that (F1, H1) equals (0,0), (F2,H2) is the first point to the right and the last point is (1,1) (Macmillan & Creelman, Citation2005).
5 Theoretical interpretations and discussion is reserved for the General discussion section.