Recent application of theories of embodied or grounded cognition to the recognition and interpretation of facial expression of emotion has led to an explosion of research in psychology and the neurosciences. However, despite the accelerating number of reported findings, it remains unclear how the many component processes of emotion and their neural mechanisms actually support embodied simulation. Equally unclear is what triggers the use of embodied simulation versus perceptual or conceptual strategies in determining meaning. The present article integrates behavioral research from social psychology with recent research in neurosciences in order to provide coherence to the extant and future research on this topic. The roles of several of the brain's reward systems, and the amygdala, somatosensory cortices, and motor centers are examined. These are then linked to behavioral and brain research on facial mimicry and eye gaze. Articulation of the mediators and moderators of facial mimicry and gaze are particularly useful in guiding interpretation of relevant findings from neurosciences. Finally, a model of the processing of the smile, the most complex of the facial expressions, is presented as a means to illustrate how to advance the application of theories of embodied cognition in the study of facial expression of emotion.

/pdf/the-simulation-of-smiles-sims-model-embodied-simulation-and-4sph1nro7c.pdf

The Simulation of Smiles (SIMS) model: Embodied simulation and the meaning of facial expression

Manipulations of cognitive strategies and intergroup relationships reduce the racial bias in empathic neural responses

We use a hidden Markov model (HMM) based approach to analyze eye movement data in face recognition. HMMs are statistical models that are specialized in handling time-series data. We conducted a face recognition task with Asian participants, and model each participant's eye movement pattern with an HMM, which summarized the participant's scan paths in face recognition with both regions of interest and the transition probabilities among them. By clustering these HMMs, we showed that participants' eye movements could be categorized into holistic or analytic patterns, demonstrating significant individual differences even within the same culture. Participants with the analytic pattern had longer response times, but did not differ significantly in recognition accuracy from those with the holistic pattern. We also found that correct and wrong recognitions were associated with distinctive eye movement patterns; the difference between the two patterns lies in the transitions rather than locations of the fixations alone.

/pdf/understanding-eye-movements-in-face-recognition-using-hidden-8dtffhzhs0.pdf

Understanding eye movements in face recognition using hidden Markov models

Participants are more accurate at remembering faces of their own relative to another ethnic group (own-race bias, ORB). This phenomenon has been explained by reduced perceptual expertise, or alternatively, by the categorization of other-race faces into social out-groups and reduced effort to individuate such faces. We examined event-related potential (ERP) correlates of the ORB, testing recognition memory for Asian and Caucasian faces in Caucasian and Asian participants. Both groups demonstrated a significant ORB in recognition memory. ERPs revealed more negative N170 amplitudes for other-race faces in both groups, probably reflecting more effortful structural encoding. Importantly, the ethnicity effect in left-hemispheric N170 during learning correlated significantly with the behavioral ORB. Similarly, in the subsequent N250, both groups demonstrated more negative amplitudes for other-race faces, and during test phases, this effect correlated significantly with the ORB. We suggest that ethnicity effects in the N170 reflect an early categorization of other-race faces into a social out-group, resulting in less efficient encoding and thus decreased memory. Moreover, ethnicity effects in the N250 may represent the "tagging" of other-race faces as perceptually salient, which hampers the recognition of these faces.

The Neural Signature of the Own-Race Bias: Evidence from Event-Related Potentials

In the last decades, desert ants have become model organisms for the study of insect navigation. In finding their way, they use two major navigational routines: path integration using a celestial compass and landmark guidance based on sets of panoramic views of the terrestrial environment. It has been claimed that this information would enable the insect to acquire and use a centralized cognitive map of its foraging terrain. Here, we present a decentralized architecture, in which the concurrently operating path integration and landmark guidance routines contribute optimally to the directions to be steered, with "optimal" meaning maximizing the certainty (reliability) of the combined information. At any one time during its journey, the animal computes a path integration (global) vector and landmark guidance (local) vector, in which the length of each vector is proportional to the certainty of the individual estimates. Hence, these vectors represent the limited knowledge that the navigator has at any one place about the direction of the goal. The sum of the global and local vectors indicates the navigator's optimal directional estimate. Wherever applied, this decentralized model architecture is sufficient to simulate the results of quite a number of diverse cue-conflict experiments, which have recently been performed in various behavioral contexts by different authors in both desert ants and honeybees. They include even those experiments that have deliberately been designed by former authors to strengthen the evidence for a metric cognitive map in bees.

https://www.pnas.org/content/pnas/115/11/2824.full.pdf

Optimal multiguidance integration in insect navigation.

Human beings are natural experts at processing faces, with some notable exceptions. Same-race faces are better recognized than other-race faces: the so-called other-race effect (ORE). Inverting faces impairs recognition more than for any other inverted visual object: the so-called face inversion effect (FIE). Interestingly, the FIE is stronger for same- compared to other-race faces. At the electrophysiological level, inverted faces elicit consistently delayed and often larger N170 compared to upright faces. However, whether the N170 component is sensitive to race is still a matter of ongoing debate. Here we investigated the N170 sensitivity to race in the framework of the FIE. We recorded EEG from Western Caucasian and East Asian observers while presented with Western Caucasian, East Asian and African American faces in upright and inverted orientations. To control for potential confounds in the EEG signal that might be evoked by the intrinsic and salient differences in the low-level properties of faces from different races, we normalized their amplitude-spectra, luminance and contrast. No differences on the N170 were observed for upright faces. Critically, inverted same-race faces lead to greater recognition impairment and elicited larger N170 amplitudes compared to inverted other-race faces. Our results indicate a finer-grained neural tuning for same-race faces at early stages of processing in both groups of observers.

Inverting faces elicits sensitivity to race on the N170 component: A cross-cultural study

Other-race faces all look alike to me and my N170

Social experience does not abolish cultural diversity in eye movements for faces

Social judgments from faces are universal

Adults from Eastern (e.g., China) and Western (e.g., USA) cultural groups display pronounced differences in a range of visual processing tasks. For example, the eye movement strategies used for information extraction during a variety of face processing tasks (e.g., identification and facial expressions of emotion categorization) differs across cultural groups. Currently, many of the differences reported in previous studies have asserted that culture itself is responsible for shaping the way we process visual information, yet this has never been directly investigated. In the current study, we assessed the relative contribution of genetic and cultural factors by testing face processing in a population of British Born Chinese adults using face recognition and expression classification tasks. Contrary to predictions made by the cultural differences framework, the majority of British Born Chinese adults deployed “Eastern” eye movement strategies, while approximately 25% of participants displayed “Western” strategies. Furthermore, the cultural eye movement strategies used by individuals were consistent across recognition and expression tasks. These findings suggest that “culture” alone cannot straightforwardly account for diversity in eye movement patterns. Instead a more complex understanding of how the environment and individual experiences can influence the mechanisms that govern visual processing is required.

/pdf/social-experience-does-not-abolish-cultural-diversity-in-eye-26u2gds29a.pdf

Social Experience Does Not Abolish Cultural Diversity in Eye Movements

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