Brain Responses to Dynamic Facial Expressions: A Normative Meta-Analysis

Abstract

Identifying facial expressions is crucial for social interactions. Functional neuroimaging studies show that a set of brain areas, such as the fusiform gyrus and amygdala, become active when viewing emotional facial expressions. The majority of functional magnetic resonance imaging (fMRI) studies investigating face perception typically employ static images of faces. However, studies that use dynamic facial expressions (e.g., videos) are accumulating and suggest that a dynamic presentation may be more sensitive and ecologically valid for investigating faces. By using quantitative fMRI meta-analysis the present study examined concordance of brain regions associated with viewing dynamic facial expressions. We analyzed data from 216 participants that participated in 14 studies, which reported coordinates for 28 experiments. Our analysis revealed bilateral fusiform and middle temporal gyri, left amygdala, left declive of the cerebellum and the right inferior frontal gyrus. These regions are discussed in terms of their relation to models of face processing.

Widespread and lateralized social brain activity for processing dynamic facial expressions

“…In addition to these posterior cortical regions, 11 studies reported activation in limbic system regions, such as the amygdala (e.g., LaBar et al, 2003;Pelphrey et al, 2007;, and 11 reported activation in the inferior frontal gyrus (IFG) (e.g., LaBar et al, 2003;van der Gaag et al, 2007), which contains motor-related parts (Binkofski & Buccino, 2006). The activation of these regions in response to dynamic facial expressions was also demonstrated in a recent meta-analysis that analyzed the coordinates reported by 14 articles (Zinchenko et al, 2018). Substantial neuroimaging and neuropsychological evidence suggested that activation of these brain regions was consistent with their information-processing functions, such as visual analysis of the dynamic aspects of faces involving the STS region (Allison et al, 2000), emotional processing involving the amygdala (Calder, Lawrence, & Young, 2001), and motor mimicry as a form of social interaction involving the IFG (Iacoboni, 2005).…”

“…A number of neuroimaging studies using functional magnetic resonance imaging (fMRI) and positron emission tomography have been performed to gain insight into the neural mechanisms underlying the processing of dynamic facial expressions (Arnold, Iaria, & Goghari, ; Arsalidou, Morris, & Taylor, ; Badzakova‐Trajkov, Haberling, Roberts, & Corballis, ; De Winter et al, ; Faivre, Charron, Roux, Lehéricy, & Kouider, ; Foley, Rippon, Thai, Longe, & Senior, ; Fox, Iaria, & Barton, ; Furl, Henson, Friston, & Calder, ; Grosbras & Paus, ; Johnston, Mayes, Hughes, & Young, ; Kessler et al, ; Kilts, Egan, Gideon, Ely, & Hoffman, ; Kret, Pichon, Grezes, & de Gelder, ; LaBar, Crupain, Voyvodic, & McCarthy, ; Pelphrey, Morris, McCarthy, & Labar, ; Pentón et al, ; Polosecki et al, ; Rahko et al, ; Reinl & Bartles, ; Rymarczyk, Zurawski, Jankowiak‐Siuda, & Szatkowska, ; Sato, Kochiyama, Uono, & Yoshikawa, ; Sato, Kochiyama, Yoshikawa, Naito, & Matsumura, ; Sato, Toichi, Uono, & Kochiyama, ; Schobert, Corradi‐Dell'Acqua, Frühholz, van der Zwaag, & Vuilleumier, ; Schultz, Brockhaus, Bülthoff, & Pilz, ; Schultz & Pilz, ; Trautmann, Fehr, & Herrmann, ; van der Gaag, Minderaa, & Keysers, ; for reviews, see Arsalidou et al, ; Zinchenko, Yaple, & Arsalidou, ). These studies contrasted brain activation during observation of dynamic emotional facial expressions with that during observation of control stimuli matched for visual motion or form with the dynamic expressions, such as dynamic mosaics, dynamic objects, nonemotional facial movements, and static emotional facial expressions.…”

“…One possible reason for these inconsistent findings is sample size, which was less than 30 in all previous individual experiments with only a few exceptions (Badzakova‐Trajkov et al, ; Kessler et al, ; Rymarczyk et al, ), because studies involving small sample sizes may have low statistical power and a reduced chance of detecting effects (Button et al, ). This issue could be relevant even to meta‐analyses (Arsalidou et al, ; Zinchenko et al, ) because these studies employed coordinate‐based meta‐analytical methods, which assess the convergence of the locations of activation foci reported in individual studies and have difficulty detecting small effects with underpowered individual studies (Acar, Seurinck, Eickhoff, & Moerkerke, ). Another possible reason for these inconsistencies is that a majority of previous studies have compared dynamic with static facial expressions.…”

“…including the bilateral FG and STS regions, limbic regions, including the bilateral amygdalae, and motor regions, including the right IFG, compared with dynamic mosaic images. The present findings of activation in these regions are consistent with those of at least 11 previous studies (e.g.,LaBar et al 2003; for a review, seeZinchenko et al, 2018). However, a similar number of previous studies have also reported null findings regarding activities in these brain regions, probably due to a lack of statistical power and/or a relatively less clear-cut contrast (e.g., the contrast between dynamic and static facial expressions).…”

Visual Behavior, Pupil Dilation, and Ability to Identify Emotions From Facial Expressions After Stroke

“…Both verbal and non-verbal forms of communication during social interaction are intertwined and reinforced to enable an interpretation of the social context. Body posture (3) and movements (4) and, especially, facial expressions (5,6) are common sources of non-verbal information that allow us to identify, and discriminate between, to a certain degree, the emotional states of others. Specifically, the ability to recognize emotional expressions on faces has been repeatedly investigated in the literature, evidencing certain universal patterns across cultures (7), ages (8), and sex (9).…”