An extended emotion-eliciting film clips set (EGEFILM): assessment of emotion ratings for 104 film clips in a Turkish sample.

The primary aim of this study was to test emotion-elicitation levels of widely used film clips in a Turkish sample and to expand existing databases by adding several new film clips with the capacity to elicit a wide range of emotions, including a rarely studied emotion category, i.e., calmness. For this purpose, we conducted a comprehensive review of prior studies and collected a large number of new suggestions from a Turkish sample to select film clips for eight emotion categories: amusement, tenderness, calmness, anger, sadness, disgust, fear, and neutrality. Furthermore, we aimed to assess emotion-eliciting levels of short video clips, mostly taken by amateur video footage. In total, 104 film clips were tested online by rating several affective dimensions. Self-reported emotional experience was assessed in terms of intensity, discreteness, valence, and arousal. It was found that at least one of the existing film clips, most of the new film clips, and the short video clips were successful at eliciting medium to high levels of target emotions. However, we also observed overlaps between certain emotions (e.g., tenderness-sadness, anger-sadness-disgust, or fear-anxiety). The current results are mostly in line with previous databases, suggesting that film clips are efficient at eliciting a wide range of emotions where cultural background might play a role in the elicitation of certain emotions (e.g., amusement, anger, etc.). We hope that this extended emotion-eliciting film clips set (EGEFILM) will provide a rich resource for future emotion research both in Turkey and the international area.

Memory error speed predicts subsequent accuracy for recognition misses but not false alarms.

The current study aims to test whether faster recognition memory errors tend to result from stronger misleading retrieval, making them harder to correct in subsequent decisions than slower errors, and whether this pattern holds for both miss and false-alarm errors. We used a paradigm in which each single-item Old/New recognition decision was followed by a two-alternative forced-choice (2AFC) test between a target and a lure. Each 2AFC trial had one item that had just been tested for an Old/New judgment and one item that had not been previously tested. Across 183 participants, the RTs for single-item recognition errors were used to predict accuracy in the 2AFC test using a hierarchical logistic regression model. The results showed a relationship between error RT and subsequent 2AFC accuracy that was qualified by an interaction with error type. Slower miss responses were more likely to be corrected than faster misses, but no accuracy differences were observed between slower and faster false alarms. The implications of these findings are discussed as they relate to assumptions about memory processes underlying inaccurate retrieval, using the diffusion model and the two-high-threshold model as examples of accounts that explain errors in terms of misleading retrieval and failed retrieval, respectively.

Does misremembering drive false alarms for emotional lures? A diffusion model investigation.

Previous evidence has shown that, in a recognition memory task, emotion leads participants to make more false alarms and decreases response times (RTs) for false alarm responses. This pattern could arise because participants adopt more liberal responding for emotional stimuli and/or because emotional lures are more likely than neutral lures to produce misleading memory retrieval. Recently, Starns et al. designed a new recognition memory paradigm and found that the speed of memory errors shows the influence of misleading information resulting in unavoidable memory errors. This study investigates the basis of false alarms to emotional lures by testing predictions of the diffusion model for a recognition paradigm similar to that by Starns et al. Participants studied lists of emotional words and then completed an old-new recognition memory test. After each old-new decision, participants were asked to make a forced-choice recognition decision that provided a chance to correct possible errors on the preceding old-new decision. Under the assumption that emotion promotes misremembering, the diffusion model predicts that forced-choice accuracy should be lower for pairs with emotional versus neutral lures and that faster old-new errors should be associated with lower forced-choice accuracy. This study tested these predictions, providing theoretical insights into how emotion affects memory retrieval and further developing a new methodology for measuring recognition performance.

A multi-lab test of the facial feedback hypothesis by the Many Smiles Collaboration.

Following theories of emotional embodiment, the facial feedback hypothesis suggests that individuals' subjective experiences of emotion are influenced by their facial expressions. However, evidence for this hypothesis has been mixed. We thus formed a global adversarial collaboration and carried out a preregistered, multicentre study designed to specify and test the conditions that should most reliably produce facial feedback effects. Data from n = 3,878 participants spanning 19 countries indicated that a facial mimicry and voluntary facial action task could both amplify and initiate feelings of happiness. However, evidence of facial feedback effects was less conclusive when facial feedback was manipulated unobtrusively via a pen-in-mouth task.

False (or biased) memory: Emotion and working memory capacity effects in the DRM paradigm.

This study aimed to investigate the role of emotion and working memory capacity (WMC) on false memory by measuring memory sensitivity independently of response bias. We used the Deese-Roediger-McDermott (DRM) paradigm in which arousal levels were kept constant across positive, negative, and neutral word lists associated with unstudied critical lures. Participants' WMC was measured by the Operation Span Task. Although negative critical lures generated significantly more false recognition (i.e., false-alarm rates) compared to positive or neutral ones, Receiver operating characteristic (ROC) analysis based on signal detection theory showed that this effect could be ascribed to shifts in bias rather than actual memory sensitivity. Data revealed that the DRM effect is a robust illusion influenced by neither emotion nor WMC in terms of memory sensitivity. However, negative words led to a prominent increase in liberal bias to say "old" for both critical and noncritical lures. Furthermore, reaction time (RT) data suggested that mentally activated but actually unstudied critical lures were monitored as old words and that participants were faster to accept negative critical lures than positive or neutral ones, suggesting that the DRM illusion was clearly reflected on the RT data as well. These results were discussed emphasizing the role of negative emotion on response bias in recognition memory.

The effects of emotion on working memory: Valence versus motivation.

It is unclear whether the effects of emotional state on working memory (WM) are valence-based or motivation-based since the type of emotions used in previous research differed on both dimensions of emotion. Especially, effects of anger, which is a negative but approach-related emotional state, were mostly overlooked. To distinguish between valence vs. motivation accounts, two experiments were conducted in which participants were induced one of four emotional states to create approach-positive (happiness), avoidance-negative (fear), approach-negative (anger), and control (neutral) conditions, followed by Self-ordered Pointing Task (Experiment 1) or N-Back task (Experiment 2) as WM measures. The main effect of emotion on WM accuracy was not significant in neither experiment. In the second experiment, however, reaction times (RTs) in the avoidance-related emotion condition were significantly faster compared to those in approach-related conditions, without compromising accuracy. Together the two experiments suggest that the motivational dimension of emotional state is more effective on WM than the valence dimension, especially on the RTs, indicating working memory updating efficiency.

How are faces with increased and decreased lower facial height perceived visually?

OBJECTIVE: The aim of this study was to assess how faces with different lower facial height (LFH) were visually perceived by laypersons using eye-tracking technology. MATERIALS AND METHOD: A total of 48 facial images of volunteers with different LFH (normodivergent, hypodivergent, hyperdivergent) were randomly viewed by 50 participants (25 male, 25 female) using Tobii Eye Tracker (Tobii T60, Tobii Technology AB, Sweden). Facial images with normal lower anterior facial height (LAFH) were used as the control group. All images were divided into three areas of interest (AOI): eyes, nose, and lower face. Eye movements of participants were analyzed with Tobii Studio software (version 3.3.1, Tobii Technology). Time to first fixation (TFF), fixation before (FB) (initial attentional capture), fixation duration (FD), and fixation count (FC) (sustained attention) parameters were measured and compared between image groups. Repeated measures ANOVA, independent samples t test, and intraclass correlation coefficient (ICC) were used for statistical analysis. RESULTS: In all image groups, the eyes were the most remarkable area that was looked at most and longest. A significant main effect was revealed for TFF on the lower face area between image groups: F (2.98) = 9.61, P = 0.00, η2 = 0.164. The lower face area of the hyperdivergent images was found to capture initial attention faster than that of the other images. A significant main effect was revealed for FD on the lower face area between image groups: F (2.98) = 22.98, P = 0.00, η2 = 0.319. CONCLUSIONS: Increased and decreased LFH affected visual perception. The difference in LFH did not alter the hierarchy of visual perception.