Ekman 60 Faces Test Software
Sofia Gilcrease
The Ekman 60-Faces (EK-60F) Test is a well-known neuropsychological tool assessing emotion recognition from facial expressions. It is the most employed task for research purposes in psychiatric and neurological disorders, including neurodegenerative diseases, such as the behavioral variant of Frontotemporal Dementia (bvFTD). Despite its remarkable usefulness in the social cognition research field, to date, there are still no normative data for the Italian population, thus limiting its application in a clinical context. In this study, we report procedures and normative data for the Italian version of the test. A hundred and thirty-two healthy Italian participants aged between 20 and 79 years with at least 5 years of education were recruited on a voluntary basis. They were administered the EK-60F Test from the Ekman and Friesen series of Pictures of Facial Affect after a preliminary semantic recognition test of the six basic emotions (i.e., anger, fear, sadness, happiness, disgust, surprise). Data were analyzed according to the Capitani procedure [1]. The regression analysis revealed significant effects of demographic variables, with younger, more educated, female subjects showing higher scores. Normative data were then applied to a sample of 15 bvFTD patients which showed global impaired performance in the task, consistently with the clinical condition. We provided EK-60F Test normative data for the Italian population allowing the investigation of global emotion recognition ability as well as selective impairment of basic emotions recognition, both for clinical and research purposes.
First, we wanted tests of both matching (specifically, an odd-expression-out task) and of explicit labelling of the facial emotion. Theoretically, these tap potentially different processes, in that matching requires expression perception but does not require verbal labelling of the facial emotions, while labelling requires initial expression perception (as with matching) but additionally requires later processes involved with assigning a verbal label to the emotion.
Second, we wanted the matching and labelling tests to use equivalent face items (specifically, all faces from one database, in this case the Karolinska Directed Emotional Faces database [KDEF [20]]; plus the target faces for the labelling task were the targets of the 3AFC odd-man-out task). This has the advantage that differences in experimental results between the tasks can then be most clearly assigned to an origin in different theoretical components tapped by the two tasks (purely perceptual, versus perceptual-plus-labelling) rather than to face-appearance differences. Many of the labelling tests in Table 1 do not have equivalent-item matching tasks available.
The existence of Stage A is also supported by other findings in the literature. A correlation between emotion-labelling and face identity perception (as opposed to our memory task) has been reported in previous studies (e.g., [12], [13]; both using the Benton Facial Recognition Test). Also, recent fMRI evidence indicates that some areas in the ventral temporal cortex that are responsive to faces are responsive to both changeable (e.g., expression) and unchangeable (e.g., identity) dimensions, while some subregions are specialised for either changeable or unchangeable dimensions [59]. Behaviourally, results also suggest at least one candidate perceptual mechanism might be common to both face identity and face emotion, namely holistic processing, in which the features of a face are perceptually integrated (e.g., [60], [61]). In individuals with congenital or developmental prosopagnosia, who have difficulty recognising the identity of familiar faces in everyday life, holistic coding is impaired for both face identity [62], [63] and face expression [63].
Finally, we turn to Stage C in Figure 5, and the proposal that the labelling stage is multimodal. Evidence for Stage C is that vocal labelling correlated with face emotion labelling, both our newly developed task and the Emotion Hexagon (arguing for shared processes involved in labelling) but did not significantly correlate with face emotion matching (arguing for separation from Stage B). Our proposed separation between Stages B and C fits with current models of face and voice perception. For instance, Belin, Bestelmeyer, Latinus, and Watson [72] propose that structural information from voices and faces is initially processed independently (c.f., our Stage A), and then the affective components are processed both independently (c.f., our Stage B) and interactively in a multi-modal emotion processing system (c.f., our Stage C).
For faces, consistent with most previous studies, there was no significant association between IQ and facial emotion matching, facial emotion labelling, or facial identity recognition. This makes a strong case that face processing is a specific ability. For face identity, we also know from previous individual-differences studies of twins that this specificity extends to heritability; that is, face identity abilities are heritable independent of the heritability of IQ [7], [8]. Interesting open questions concern (a) whether face emotion ability is also heritable independent of IQ (a recent twin study of face emotion labelling found a heritable contribution to performance but did not measure IQ, plus the reliability of their expression recognition task was not reported [18]), and (b) whether face emotion and face identity abilities are heritable independently from each other, or whether the independence of heritability is only from IQ. Our new facial emotion-recognition tasks developed in this study provide suitable measures for future examination of these questions.
Facial expressions have a communicatory function and the ability to read them is a prerequisite for understanding feelings and thoughts of other individuals. Impairments in recognition of facial emotional expressions are frequently found in patients with neurological conditions (e.g. stroke, traumatic brain injury, frontotemporal dementia). Hence, a standard neuropsychological assessment should include measurement of emotion recognition. However, there is debate regarding which tests are most suitable. The current study evaluates and compares three different emotion recognition tests. 84 healthy participants were included and assessed with three tests, in varying order: a. Ekman 60 Faces Test (FEEST) b. Emotion Recognition Task (ERT) c. Emotion Evaluation Test (EET). The tests differ in type of stimuli from static photographs (FEEST) to more dynamic stimuli in the form of morphed photographs (ERT) to videos (EET). Comparing performances on the three tests, the lowest total scores (67.3% correct answers) were found for the ERT. Significant, but moderate correlations were found between the total scores of the three tests, but nearly all correlations between the same emotions across different tests were not significant. Furthermore, we found cross-over effects of the FEEST and EET to the ERT; participants attained higher total scores on the ERT when another emotion recognition test had been administered beforehand. Moreover, the ERT proved to be sensitive to the effects of age and education. The present findings indicate that despite some overlap, each emotion recognition test measures a unique part of the construct. The ERT seemed to be the most difficult test: performances were lowest and influenced by differences in age and education and it was the only test that showed a learning effect after practice with other tests. This highlights the importance of appropriate norms.
This study aimed to compare performance on three different emotion recognition tests in a sample of healthy subjects. We used (a) the Ekman 60 Faces Test, a subtest of the Facial Expression of Emotion Stimuli and Test (FEEST) that makes use of static photographs [45], (b) the Emotion Recognition Task (ERT), which consists of morphed facial stimuli that gradually increase in intensity [46], and (c) The Emotion Evaluation Task (EET), a subtest of The Awareness of Social Inference Test (TASIT), which comprises audiovisual portrayals of emotion [47]. Although the three tests differ in stimuli type, they all make use of the same six basic emotions: anger, fear, disgust, happiness, sadness, and surprise [48].
Second, we aimed to examine the extent to which demographic variables (i.e. gender, age, educational level) and neuropsychological functions (i.e. working memory, attention, information processing speed) influenced the ability to correctly recognize facial emotions, and whether this differed between the three tests. Lastly, we investigated the extent to which each test would be susceptible to practice effects. We expect that our findings will contribute to a better understanding of the usefulness of these tests in clinical practice.
Participants were tested individually at their home or (if not feasible) at the University Medical Centre Groningen, the Netherlands. The administration time of the complete test battery was approximately 1.5 hours. Ethical approval for this study was given by the Ethical Committee of Psychology (ECP) of the University of Groningen. All participants were treated in accordance with the Helsinki Declaration and gave written informed consent prior to testing.
The Ekman 60 faces test of the Facial Expressions of Emotion Stimuli and Tests (FEEST) [45]. Participants are shown sixty photographs of faces, depicting the following six basic emotions: anger, disgust, fear, happiness, sadness, and surprise (ten of each). Each photograph is presented for 5 seconds on a computer screen and participants are asked to choose which emotion label best describes the emotion shown. There is no time restriction for answering. Total score ranges from 0 to 60, the separate emotion scores range from 0 to 10The FEEST has shown to have good reliability and validity and has proven to be sensitive in various patient groups, such as acquired brain injury patients [10, 51] and patients with FTD [14].
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