Emotion Based Attentional Priority for Storage in Visual Short-Term Memory

Abstract

A plethora of research demonstrates that the processing of emotional faces is prioritised over non-emotive stimuli when cognitive resources are limited (this is known as ‘emotional superiority’). However, there is debate as to whether competition for processing resources results in emotional superiority per se, or more specifically, threat superiority. Therefore, to investigate prioritisation of emotional stimuli for storage in visual short-term memory (VSTM), we devised an original VSTM report procedure using schematic (angry, happy, neutral) faces in which processing competition was manipulated. In Experiment 1, display exposure time was manipulated to create competition between stimuli. Participants (n = 20) had to recall a probed stimulus from a set size of four under high (150 ms array exposure duration) and low (400 ms array exposure duration) perceptual processing competition. For the high competition condition (i.e. 150 ms exposure), results revealed an emotional superiority effect per se. In Experiment 2 (n = 20), we increased competition by manipulating set size (three versus five stimuli), whilst maintaining a constrained array exposure duration of 150 ms. Here, for the five-stimulus set size (i.e. maximal competition) only threat superiority emerged. These findings demonstrate attentional prioritisation for storage in VSTM for emotional faces. We argue that task demands modulated the availability of processing resources and consequently the relative magnitude of the emotional/threat superiority effect, with only threatening stimuli prioritised for storage in VSTM under more demanding processing conditions. Our results are discussed in light of models and theories of visual selection, and not only combine the two strands of research (i.e. visual selection and emotion), but highlight a critical factor in the processing of emotional stimuli is availability of processing resources, which is further constrained by task demands.

Neural measures of the causal role of observers’ facial mimicry on visual working memory for facial expressions

“…In the present study, we have replicated these results with angry faces compared to neutral faces; we observed that facial expressions of intense anger elicited an SPCN of greater amplitude than neutral and subtle facial expressions and, moreover, were associated with greater accuracy in the change detection task when compared to the other two levels of intensity of facial expressions (neutral and subtle). This overall pattern of findings is very well in line with the benefit observed for negative and angry facial expressions in previous studies in terms of behavioral indices of sensitivity (Jackson et al , 2008 ; Langeslag et al , 2009 ; Jackson et al , 2014 ; Simione et al , 2014 ; Xie and Shang, 2016 ). An unexpected result refers to the observation that the faces with expression of subtle anger elicited not only an SPCN of lower amplitude than the faces with full expressions of anger but also an SPCN of lower amplitude than the faces with neutral expressions.…”

Attentional biases towards familiar and unfamiliar foods in children. The role of food neophobia

“…Thus there appears to be a natural bias to prioritise attention and processing resources toward threatening rather than positive or rewarding stimuli (e.g. Simione et al, 2014;Maratos, 2011;LeDoux, 2003;Ohman, Lundqvist & Esteves, 2001). …”

Negative and Positive Bias for Emotional Faces: Evidence from the Attention and Working Memory Paradigms

“…For example, they have been found that high perceptual processing competition (e.g., 150 ms exposure time for encoding) revealed an emotional face advantage (i.e., both happy and angry faces had an advantage over neutral faces). Meanwhile, an angry face advantage emerged when the competition between stimuli was further increased by increasing the stimulus set size (Simione et al, 2014). Furthermore, with the same set size of five, a previous study found a VWM cost for fearful faces compared to neutral faces only with a longer encoding duration (4,000 ms), but it showed no differences with a shorter encoding duration (1,000 ms; Curby et al, 2019: Experiment 1 & Experiment 2).…”

“…However, to the best of our knowledge, no study has summarized the positive and negative face advantages in VWM. Therefore, we have summarized and listed these advantages in the Supplementary Table 1 (including 18 papers), especially on the adoption of the change detection paradigm (Jackson et al, 2008(Jackson et al, , 2009(Jackson et al, , 2012(Jackson et al, , 2014Langeslag et al, 2009;Sessa et al, 2011Sessa et al, , 2018Linden et al, 2011;Becker et al, 2014;Brenner et al, 2014;Simione et al, 2014;Thomas et al, 2014;Maran et al, 2015;Xie et al, 2017;Spotorno et al, 2018;Curby et al, 2019;Lee & Cho, 2019;Liu et al, 2020). We have found that, on the one hand, as we mentioned earlier in introduction, the experimental settings of the change detection and visual search paradigms have much in common.…”

“…Their results consistently showed enhanced VWM performance with different set sizes, durations, and face sets. With schematic faces, other researchers limited the cognitive resources by manipulating the encoding time and set size, and they found better memory performance for angry faces with short exposure time (150 ms) and a large set size of five stimuli (Simione et al, 2014). Similarly, researchers also found that participants could better maintain fearful faces in VWM than neutral faces (Sessa et al, 2011;Lee and Cho, 2019).…”