Introduction

In everyday life, humans are constantly observing and interpreting the movements of others in an attempt to deduce their moods and emotional states. Folk psychology advocates the existence of gender differences in a number of these socio-cognitive functions such as ‘reading’ the mental states of others or discerning subtle differences in others body language. However, from an empirical perspective, the issue of gender differences in recognizing emotions is still a topic of debate. Studies using self-report questionnaires have revealed that females have higher empathy scores than males [1]–[4]. However, it is possible that the answers of participants might have been associated with indices of social desirability, potentially leading to biased results [3], [5]. Next to self-reports, the majority of studies addressing gender differences in the socio-cognitive domain employed paradigms involving emotion recognition from facial expressions. A meta-analysis on this topic revealed that 80% of studies show a female advantage [6], [7], however with relatively small effect sizes. Other studies even showed no gender differences in the recognition of facially expressed emotions [8], [9]. Recently it has been suggested that this inconsistency across studies can be explained by differences in the nature of stimuli, such that studies using emotional expressions of high intensity show fewer differences between male and female decoders than those using subtle expressions with less intensity [10].

However, facial expressions are not the only source for conveying emotionally relevant information. In every-day situations, other sources - such as the communicator's body language or “bodily kinematics” - might be important as well, especially when facial expressions are inconsistent or unavailable to the observer.

Concerning this topic, neuroscience and social cognition research are increasingly focusing on the role of the observer's own motor system in understanding or ‘reading’ others bodily kinematics [11]–[14]. Already within the framework of the social-cognitive simulation theory [15], [16] and the ideomotor theory [17], it was posited that the ‘understanding of other's actions and behavior’ may be essentially motor, rather than sensory in nature. The ideomotor principle - as first contended by James (1890) - assumed that “every representation of a movement awakens in some degree the actual movement which is its object” [18] and that common perceptual-motor representations are formed by the correlated experience of executing and perceiving actions. Accordingly, simulating other's actions by matching perceived movements onto the observers' own motor system has been proposed to be the general mechanism by which observers can read or understand the actions, intentions or emotions of others [11]–[14].

First neurophysiological evidence for the ‘embodied simulation theory’ was provided by the discovery of mirror neurons in the macaque monkey brain. Using single neuron recordings, the group of Rizzolatti et al., identified the existence of a particular class of neurons in the ventral premotor [19] and later in parietal cortices [20], which fire when the monkey performs a specific action, and also when it observes the same action performed by another individual. First indications of the existence of a mirror neuron system (MNS) in the human brain emerged from transcranial magnetic stimulation (TMS) studies showing ‘resonating’ activity in the observer's motor system when movements of others are observed [21]–[23], and similar findings on resonant activation of the motor cortex during mere observation of actions were provided from studies using electroencephalography (EEG) [24], [25] and magneto-encephalo-graphy (MEG) [26]. To date, also a large number of brain imaging studies have explored which brain regions become increasingly activated during the observation of other's actions and both the inferior frontal gyrus (IFG) and the inferior parietal lobule (IPL) have consistently been identified to be key areas of the human mirror system [27]–[29]. Based on its remarkable properties, the human MNS is hypothesized to be the neural mechanism by which observed movements are simulated or matched onto the observer's own motor system in order to read or understand the actions, intentions or emotions of others (i.e., embodied simulation) [13], [30]. Interestingly, several neurophysiological studies addressed the issue of gender differences in the MNS, and all reported mirror activations to be generally stronger in female compared to male participants [31]–[33]. Also voxel-based morphometry studies demonstrated that female participants display larger gray matter volumes than male participants in regions of the mirror system [34], [35]. To date, however, the issue of behavioral gender differences in action or emotion understanding remains fairly unexplored.

Prompted by findings of neurophysiological gender differences in mirror system functioning, the present study aimed to investigate whether gender differences are also quantifiable on behavioral tasks involving the understanding or reading of other's bodily kinematics. In our paradigm, point light displays (PLD) were used, in which biological motions are depicted solely by the kinematics of light points placed on the joints of an actor [36]. We employed these highly simplified versions of biological motion to exclude that the results were influenced by differences in stimulus intensity as reported for complex and more natural stimuli such as facial expressions [10]. Although PLDs lack visual properties such as color, shading, and contours, they are easily recognized as depicting biological motion [37] and have repeatedly been shown to activate the human MNS [38]–[41]. Using fMRI, Saygin et al. (2004) reported point-light biological motion animations to yield activity in frontal areas of the action observation network [38]. Similar patterns of results were found using EEG during the perception of PLDs depicting bodily actions [41], intentions or emotions [40]. In both studies, mu rhythm suppression – indicative of resonant mirror activity - was found during the perception of point-light induced biological motion but not during observation of non-biological motion displays. Also recent data from a lesion study showed that the ability to recognize PL biological motion directly relies upon and requires neuronal resources that are part of the action observation or mirror neuron system (MNS) [39].

Biological motion as depicted by PLDs, has been shown to contain all sorts of socially relevant information about human agents such as the kind of action they are executing [42], their gender [43], [44], their intentions and even their emotional state [45], [46]. In a series of experiments, we explored whether gender differences exist for the recognition of several ‘social’ features from PLDs. In a first experiment, we explored potential gender differences in the recognition of some basic aspects, such as (i) the ‘displayed actions’ or (ii) the point light figures' ‘gender’. In a second experiment, recognition of more subtle socially relevant cues, such as the ‘emotional state’ of the displayed point light figures was explored. An additional aim of the second experiment was to investigate whether potential gender differences in discerning socially relevant information from PLDs pertained to tasks involving the basic discrimination of ‘biological motion’ from ‘non-biological’ motion. In this task, subjects were required to indicate whether or not they recognized ‘a person’ in a series of human PLDs (‘biological motion’) or phase scrambled versions of the same PLD (‘non-biological motion’).

Based on the previously described stronger mirror system activation in females compared to males, we hypothesized the existence of behavioral gender differences (better performance in females) for (i) discerning subtle cues on the emotional state of the point light figure, and (potentially to a lesser extent) for (ii) recognizing the displayed actions and (ii) gender of the PLDs. Moreover, we additionally hypothesized that gender differences would pertain to the basic discrimination of ‘biological’ from ‘non-biological’ motion. No group differences were expected for a control PLD perception task, involving the identification of color changes in the moving point-light dots.

In experiment 2, we additionally tested whether the ability to recognize emotions from bodily PLD kinematics is correlated to the ability to recognize emotions from facial cues, as assessed by the ‘Reading the Mind in the Eyes Test’ (revised version) [47]. This test was previously developed as a measure of adult ‘mentalizing’ and has been shown to be a standardized and sensitive test to reveal subtle individual differences in emotion recognition from the eye region of different faces.

Materials and Methods

Point light displays - Motion Capturing

One male and one female actor were selected to create the point light displays (PLD). Each actor was asked to perform 5 actions, each carried out in 4 different ‘emotional states’. The 5 actions were: (i) walking; (ii) jumping on the spot; (iii) kicking a ball using the right leg; (iv) drinking from a bottle of water, and (v) wiping the table. The 4 emotional states were: (i) neutral; (ii) happy; (iii) sad, and (iv) angry. After two or more practice trials, all actions/emotions were recorded three times for each actor. One of the three recordings was selected based on the visibility of the reflective markers, leaving a grand total of 40 recorded motion scenes (‘2 actors’ב5 actions’ב4 emotions’).

To obtain the captured motion data, an eight-camera VICON system was used (capturing system measuring at 100 Hz, Oxford Metrics, Oxford, UK). Twelve reflective markers were attached to the joints of the ankles, the knees, the hips, the wrists, the elbows, and the shoulders of the actor (Figure 1A, 1B). After the capture session, the 2-D data from all camera units (8) were processed off line to calculate the 3-D coordinates of the markers (Vicon Motion Systems, Oxford, UK). To create the actual movie files, in house made scripts were used, created with Matlab software (MathWorks, Massachusetts, U.S.A.). For each time point, 3-D coordinates of the 12 marker dots were converted as white spheres on a black background. Frames of the captured scene were rendered as audio-video interleaved (avi) movie files at a frame rate of 20 Hz. For each recorded scene, movie files with a duration of 3 s were created from three different viewpoints (front view (0°), side view (90°), intermediate view (45°) (Figure 1C) resulting in 120 PLDs in total (‘2 actors’ב5 actions’ב4 emotions’, ‘3 perspectives’).

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Figure 1. To create the point light displays, twelve reflective markers were attached to an actor's shoulders, elbows, wrists, hips, knees and ankles, and were tracked using a Vicon motion-capture-system.

(A) An exemplary photograph of the male actor with the 12 markers attached to the body. (B) The corresponding point light figure. (C) Examples of point light figures, viewed from different perspectives i.e., the front, the side, and the 45° view.

https://doi.org/10.1371/journal.pone.0020989.g001

In addition, for each of the PLDs, a scrambled version was created which consisted of the same individual dots, undergoing the same local trajectories as in the normal PLDs, however with the position permutated between the 12 individual trajectories. This ‘scrambling’ resulted in 120 PLDs showing non-biological ‘scrambled’ motions.

In all the presented PLDs; the dots appeared white against a black background subtending 11×12 degrees visual angle at an approximate viewing distance of 50 cm (note that subjects were free to make small trunk movements). Each dot subtended 0.25 degrees (for example movies, see Video S1, S2 and S3).

Results

Female versus male differences in recognizing bodily kinematics

Potential gender differences in recognition performance were assessed for all tests.

‘Action Recognition Test’ (Experiment 1).

A Kolmogorov-Smirnov test on the % correct answers revealed a significant effect of gender [p<.05], indicating better action recognition for the female compared to the male participants (Figure 2A). Reaction times were comparable for both genders [F(1, 26) = .32, p = .58] (Figure 2F).

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Figure 2. Gender differences in test performance.

Accuracy (% correct scores) (A–E) and Reaction times (F–J) are displayed as a function of participant group (male, female) separately for each test of experiment 1 [Action Recognition Test (A, F); Gender Recognition Test (B, G)] and experiment 2 [Biological motion Recognition Test (C, H); Emotion Recognition Test (D, I); Control Color Test (E, J)]. Vertical lines denote ±standard error. [(*) p = .05; * p<.05; ** p<.01].

https://doi.org/10.1371/journal.pone.0020989.g002

‘Gender Recognition Test’ (Experiment 1).

Gender recognition from the PLDs was shown to be comparable for female and male participants, both in terms of % correct answers [F(1, 26) = .96, p = .34] (Figure 2B) and reaction times [F(1, 26) = .07, p = .78] (Figure 2G).

‘Biological Motion Recognition Test’ (Experiment 2).

As a group, females were shown to be tentatively faster compared to males in recognizing a ‘biological actor’ or ‘person’ from the PLDs. This was revealed by a significant effect of gender from the one-way ANOVA analysis on the RT data [F(1, 35) = 3.8, p = .05] (Figure 2H). Percentage correct answers were shown to be comparable for both groups [F(1, 26) = .007, p = .93] (Figure 2C).

‘Emotion Recognition Test’ (Experiment 2).

Similar to findings from the ‘Biological Motion Recognition Test’, females were shown to be significantly faster compared to males in recognizing the displayed emotions from the presented PLDs. This was revealed by a significant effect of gender from the one-way ANOVA analysis on the RT data [F(1, 30) = 6.2, p = .017] (Figure 2I). Percentage correct answers were shown to be comparable for both groups [F(1, 30) = .14, p = .72] (Figure 2D). We additionally explored the potential interaction between ‘Emotion’ and ‘Subjects' gender’ with a repeated measures ANOVA on the % correct answers and RT data (with the within factor ‘Emotion’ and the between factor ‘Subjects' gender’). However, no significant interaction effects were revealed [Acc: F(3,90) = .09, p = .96] [RT: F(3,90) = .4, p = .76], indicating that gender effects were similar for all types of emotion.

‘Control Color Test’ (Experiment 2).

Reaction times to indicate the color change of the dot, as well as % correct answers were shown to be comparable for both genders [RT: F(1, 35) = .29, p = .59] (Figure 2J) [Acc: p>.1] (Figure 2E).

‘Reading the Mind in the Eyes Test’ (Experiment 2).

One-way ANOVA analysis on the % correct answers revealed a significant effect of gender [F(1, 35) = 6.3, p = .016], replicating previous findings of a female superiority on the ‘Reading the Mind in the Eyes Test’ [47], [49].

Correlated performance

Performance on the ‘Emotion Recognition Test’ was shown to correlate significantly with performance on the ‘Biological Motion Recognition Test’, both in terms of accuracy [r = .66; p<.001] (Figure 3A) and reaction times [r = .56; p<.001] (not shown in figure). These correlations indicate that a subject's ability to discern emotional information from PLDs was related to the subject's ability to basically discriminate ‘biological’ from ‘non-biological’ motion.

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Figure 3. Performance on the ‘Emotion Recognition Test’ correlates with performance on the ‘Biological Motion Recognition Test’ and the ‘Reading the Mind in the Eyes Test’.

Figure 3 shows linear fits for correlated performance (% correct answers) on the ‘Emotion Recognition Test’ and respectively the ‘Biological Motion Recognition Test’ (A) and the ‘Reading the Mind in the Eyes Test’ (B) of experiment 2. Dotted lines denote 0.95 confidence intervals.

https://doi.org/10.1371/journal.pone.0020989.g003

A significant correlation was also obtained between performance on the ‘Emotion Recognition Test’ and the ‘Reading the Mind in the Eyes’ Test [r = .38; p = .03] (Figure 3B), i.e., indicating that subjects scoring high on the ‘Reading the Mind in the Eyes Test’ were also good at recognizing bodily emotions from PLDs. No correlations were found between performance on the ‘Control Color Test’ and all other tests [all, r<.2; p>.1].

Discussion

The aim of the present study was to provide an objective quantification of potential gender differences in a set of socio-cognitive tasks involving the recognition of distinct features from point light displays (PLDs). Females were shown to perform better than male participants on PLD perception tasks involving bodily action recognition (experiment 1) and bodily emotion recognition (experiment 2). Interestingly, gender differences even pertained to tasks involving the basic recognition of ‘biological’ from ‘non-biological’ PLD motion (experiment 2). Moreover, previous findings of a female superiority on the ‘Reading the Mind in the Eyes test’ were replicated in the present study. No gender differences were revealed for the control test (indicate color change in one of the moving dots) and for recognizing the gender of the PLD figure. Interestingly, accuracy scores on the ‘Reading the Mind in the Eyes test’ were shown to predict the subjects' accuracy in recognizing emotions from bodily kinematics depicted by PLDs.

In experiment 1, gender differences were revealed for the ‘Action Recognition Test’ in terms of accuracy scores, such that females produced more correct answers compared to males, with comparable or even tentatively faster reaction times. The finding that performance was comparable for males and females on the ‘Gender Recognition Test’ suggests that the observed gender effect in action recognition is not related to general gender differences in reaction times or response selection abilities (i.e., selecting the correct finger to the correct response button). Overall, the lack of differences between male and female participants on the ‘Gender Recognition Test’ accords to some previous studies also showing no gender differences in gender recognition from PLDs [50], [51]. Moreover, overall gender recognition accuracy was only slightly above chance, potentially because the actors shown in the PLDs provided only subtle gender specific cues. A recent study exploring gaze patterns during gender recognition from PLDs suggested that the primary cues to gender are found in the shoulder and pelvis or ‘hip-shoulder ratio’ of a point light walker [52]. Results from our and previous studies suggest that the processing of these gender-specific cues (i.e., relating to body structure, and in particular to the relative width of shoulders and hips) may be comparable between genders.

In experiment 2, male participants appeared to adopt a more ‘time consuming’ strategy to accomplish the task compared to females both in the ‘Biological Motion’, and ‘Emotion Recognition Tests’, (as revealed by higher reaction times for males compared to females). Also here, this male-female difference seems task-specific, since reaction times on the ‘Control Color Test’ were comparable for the same male and female participants. It should be noted that the control task was relatively easy such that, theoretically, there might have been a ceiling effect in reaction times. However, even this relatively simple choice reaction time task is sufficient to control for potential gender differences in generating fast motor responses. Moreover, in light of the data from experiment 1 that revealed no gender differences on the (rather demanding) Gender recognition test, it seems unlikely that the gender effects observed in experiment 2 are solely driven by differences in response time or response selection abilities.

Overall, the finding of sex differences on bodily emotion recognition from point light animations is consistent with previous studies reporting gender differences in emotion recognition from facial expressions [6], [7], [53], [54]. A standardized and sensitive test that has been developed in this context is the ‘Reading the Mind in the Eyes Test’, in which subjects are presented with a series of photographs of the eye region of the face of different persons, and are asked to indicate which of four words best describes what the person in the photograph is thinking or feeling [47]. In the present study we were able to replicate previous findings of a female superiority in facial emotion recognition [47], [49]. Moreover, performance on this ‘facial’ emotion recognition test was shown to correlate significantly with performance on our newly developed ‘bodily’ emotion recognition test. Together, these findings indicate that gender differences in visually recognizing emotions are relatively generalized across facial and bodily emotion perception (i.e., irrespective of whether the task involves the ‘reading’ of fine movements in facial muscles, or the ‘embodiment’ of whole body emotional states). In addition, results from our Action and Biological Motion Recognition Tests provide indications that these gender differences are not restricted to the emotional domain, but are also manifest in tasks involving more ‘general’ biological motion processing.

Although substantially different in methodological approach, some recent studies explored differences between males and females in understanding actions and intentions from a visual event arrangement task. In this task, participants have to organize a set of cards depicting an event as a series of snapshots in a comic-strip fashion (i.e., requiring the understanding of the intentions and dispositions of the characters involved in the events) [55], [56]. In contrast to our results, these studies found no difference in action and intention understanding between female and male participants. However, the neural mechanisms of action and intention understanding from such reconstruction tasks (using static frames) might substantially differ from our dynamic PLD perception paradigms.

Our findings are consistent with previous studies reporting gender differences at the neurophysiological level for areas that are part of the action observation system and that respond to biological motion perception from PLDs [31]–[35]. In this respect, the presently reported differences between males and females in PLD recognition tasks may provide first indications that these neurophysiological differences are also relevant and quantifiable at the behavioral level. Interestingly, abundant reports exist on gender-related differences on empathy scores as indexed by standard questionnaires [1], [1]–[4], [57]–[60], [60,61] and also MNS activity has been shown to correlate to empathy indices [35], [62], [63]. In this respect, although rather speculative, it can be envisaged that inter-individual or gender-dependent differences in emotional processing may - at least to some degree – be related to more basic differences in processing biological motion per se. Results from our correlation analyses speak in favor of this notion by showing a tight relationship between a subject's ability to discern subtle emotional cues from PLDs and the subject's ability to basically discriminate biological from non-biological motion. Similar findings were revealed from a previous study examining a link between explicit detection of human gait from PLDs and emotion recognition [64]. Here however, only significant correlations with gait detection performance were observed for detecting ‘angry’ emotional states but not for ‘happiness’ detection.

Contrary to the notion of gender differences in the ‘biological motion processing network’, a recent magneto-encephalography study showed that gender-dependent differences in acquiring social information are related to differences in regions of the perceptual decision making network, namely, when the presence of social interactions had to be judged based on animated motions of geometric shapes [65]. Overall, it is not surprising that these non-biological stimuli produced effects outside the MNS, namely within the left prefrontal cortex, a region implicated in perceptual decision making. In addition, results indicated that females judged the presence of social interaction more rapidly than males who seemed to require more sensory evidence for social decisions [65]. Despite the apparent difference in adopted stimuli between this and our study, it should be interesting for future research to address whether the presently reported gender differences on PLD perception tasks are related to differences in the biological motion processing network, the perceptual decision making network, or in both systems. In general, such investigations may also shed light on gender-related vulnerabilities to neuropsychiatric disorders that are characterized by social cognition problems, such as autism spectrum disorders (ASD). Impairments in PLD biological motion perception have been reported in ASD [66]–[69] and males are known to be more commonly affected by the disorder than females with a ratio of about 4∶1 [70]. In this respect, it should be interesting to explore whether the normal gender difference in response to our point light action, biological motion and emotion recognition tasks is even more pronounced in ASD.

Supporting Information

Acknowledgments

We are grateful to all the subjects who participated in this research, and to Pieter Van Noten, Thomas Van Gemert, Marieke Durnez and Annelien Mestdagh, for their help in the development of the point light animations and the assessment process. We would also like to thank Johan Wagemans for his insightful feedback on the design of the distinct point light recognition tests.