Dataset Information

Feature-based representations of emotional facial expressions in the human amygdala.

ABSTRACT: The amygdala plays a central role in processing facial affect, responding to diverse expressions and features shared between expressions. Although speculation exists regarding the nature of relationships between expression- and feature-specific amygdala reactivity, this matter has not been fully explored. We used functional magnetic resonance imaging and principal component analysis (PCA) in a sample of 300 young adults, to investigate patterns related to expression- and feature-specific amygdala reactivity to faces displaying neutral, fearful, angry or surprised expressions. The PCA revealed a two-dimensional correlation structure that distinguished emotional categories. The first principal component separated neutral and surprised from fearful and angry expressions, whereas the second principal component separated neutral and angry from fearful and surprised expressions. This two-dimensional correlation structure of amygdala reactivity may represent specific feature-based cues conserved across discrete expressions. To delineate which feature-based cues characterized this pattern, face stimuli were averaged and then subtracted according to their principal component loadings. The first principal component corresponded to displacement of the eyebrows, whereas the second principal component corresponded to increased exposure of eye whites together with movement of the brow. Our results suggest a convergent representation of facial affect in the amygdala reflecting feature-based processing of discrete expressions.

SUBMITTER: Ahs F

PROVIDER: S-EPMC4158364 | biostudies-literature | 2014 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Feature-based representations of emotional facial expressions in the human amygdala.

Ahs Fredrik F Davis Caroline F CF Gorka Adam X AX Hariri Ahmad R AR

Social cognitive and affective neuroscience 20130724 9

The amygdala plays a central role in processing facial affect, responding to diverse expressions and features shared between expressions. Although speculation exists regarding the nature of relationships between expression- and feature-specific amygdala reactivity, this matter has not been fully explored. We used functional magnetic resonance imaging and principal component analysis (PCA) in a sample of 300 young adults, to investigate patterns related to expression- and feature-specific amygdal ...[more]

PMID: 23887817

Similar Datasets

Project description:It is commonly assumed that a person's emotional state can be readily inferred from his or her facial movements, typically called emotional expressions or facial expressions. This assumption influences legal judgments, policy decisions, national security protocols, and educational practices; guides the diagnosis and treatment of psychiatric illness, as well as the development of commercial applications; and pervades everyday social interactions as well as research in other scientific fields such as artificial intelligence, neuroscience, and computer vision. In this article, we survey examples of this widespread assumption, which we refer to as the common view, and we then examine the scientific evidence that tests this view, focusing on the six most popular emotion categories used by consumers of emotion research: anger, disgust, fear, happiness, sadness, and surprise. The available scientific evidence suggests that people do sometimes smile when happy, frown when sad, scowl when angry, and so on, as proposed by the common view, more than what would be expected by chance. Yet how people communicate anger, disgust, fear, happiness, sadness, and surprise varies substantially across cultures, situations, and even across people within a single situation. Furthermore, similar configurations of facial movements variably express instances of more than one emotion category. In fact, a given configuration of facial movements, such as a scowl, often communicates something other than an emotional state. Scientists agree that facial movements convey a range of information and are important for social communication, emotional or otherwise. But our review suggests an urgent need for research that examines how people actually move their faces to express emotions and other social information in the variety of contexts that make up everyday life, as well as careful study of the mechanisms by which people perceive instances of emotion in one another. We make specific research recommendations that will yield a more valid picture of how people move their faces to express emotions and how they infer emotional meaning from facial movements in situations of everyday life. This research is crucial to provide consumers of emotion research with the translational information they require.

Dataset Information

Feature-based representations of emotional facial expressions in the human amygdala.

Publications

Feature-based representations of emotional facial expressions in the human amygdala.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets