1. on the relationship between the two, ultimately

1.   
Introduction

 

Humans infer important social
information from faces that can affect real life decisions. Emotion recognition
and trait evaluations of trust and dominance from facial cues are two automatic
processes of social information extraction. Most research has looked at
facial expression recognition and social trait inferences separately, but evidence
increasingly suggests a possible relationship between the two processes. This
idea is summarized in the emotion overgeneralization hypothesis (Montepare
& Dobish, 2003), which argues that perceptions of trait impressions are often overgeneralized in faces that
were not intentionally posing expressions (e.g. fear, surprise, etc.), yet
varied in facial features resembling those emotional cues. If the emotion overgeneralization
hypothesis is true, individuals with deficits in emotion recognition should be
impaired in evaluating both trustworthiness and dominance trait inferences from
faces, and vice versa. Though some studies provide evidence to support the
overgeneralization hypothesis, others have shown that certain neurological
damage (e.g. orbitofrontal
cortex damage) cause impairments in only one of the processes, not only
highlighting a gap in the literature, but providing evidence to argue that the
overgeneralization hypothesis may be false. This essay will assess the general
background of emotion recognition and trait inferences of trust and dominance, evaluate
the potential neural mechanisms involved in both, and investigate the present
research on the relationship between the two, ultimately arguing that the
overgeneralization hypothesis is potentially false and that the two processes may
be dissociable.

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2.   
Overview of Emotion Recognition

 

Emotion recognition background

Emotion displays in faces play a
significant role in the social interactions of humans. People
use emotional facial expressions to infer important social information and to
guide social judgements (Willis et al., 2010). Research suggests that overt
displays of emotion signal an individual’s state and intentions, as well as information
about the environment that may have caused the expression (Montepare & Dobish, 2003; Willis
et al., 2010). These
emotional inferences are fast, automatic, and driven by the stimuli (Adolphs,
2009). Failure in one’s
ability to recognize emotion can cause impairments in interpreting social signals
that guide social behavior, leading to ambiguous or inappropriate social
interactions (Adolphs, 2003).

 

Neurological mechanisms

Facial emotion recognition has been
extensively studied with both healthy subjects (Fusar-Poli et
al., 2009; Phan, Wager, Taylor, & Liberzon, 2002) and in subjects with
neurological and psychiatric impairments (Bediou et al., 2009; Kohler, Walker,
Martin, Healey, & Moberg 2010; Fernandez-Duque & Black, 2005). By
studying both groups, research has highlighted potential neural mechanisms
involved in emotion recognition and the interrelationships between different
social cognitive abilities. Evidence suggests that emotional facial features
activate a network of limbic structures including the amygdala, insula cortex,
orbitofrontal cortex (OFC), and the ventromedial prefrontal cortex (VMPC) (Adolphs, 2009; Calder,
Young, Perrett, Hodges, & Etcoff, 1996; Fernandez-Duque
& Black, 2005). The Amygdala, a subcortical brain region, is
important for emotional processing such as regulating social behavior and
recognizing facial expressions (Adolphs,
2009). Lesion studies suggest that impairment to the amygdala
results in reduced emotion recognition of fear expressions from an inability to direct
gaze and visual attention to facial features, such as the eye region, in faces
normally salient to recognize such expressions (Adolphs et al., 1994, Adolphs
et al., 2005). Activation in the amygdala and insula cortex generally
increases while viewing angry versus happy faces (Lin et al., 2016). Some have argued that this is partly due to a more abstract
function of the amygdala in general arousal and vigilance when viewing negative
emotional faces (Adolphs, 2009). Studies have also found that damage to the OFC,
a ventral region of the prefrontal cortex that is connected to the amygdala (Kringelbach
& Rolls, 2004), may be linked to impairments with explicit facial expression
recognition (Heberlein, Padon, Gillihan, Farah, & Fellows, 2008). Similarly, studies
of patients with VMPC impairments show difficulty in interpreting nonverbal
social information (e.g. facial expressions, gestures, body posture) though
they have preserved knowledge of basic social and moral norms (Adolphs, 2009;
Vandekerckhove et al., 2014). These studies highlight a wide range of potential
interconnected neural mechanisms involved in facial emotion recognition.

 

3.   
Overview of Trust & Dominance

 

Trait evaluations

Social
cognition entails more than just emotion recognition. Humans make rapid
inferences about the social traits of others from an array of cues including
their faces, voices, posture, gestures, and body shapes (Sprengelmeyer et al.,
2016). Trait impressions
from facial cues can affect real-life decisions, ranging from electoral success
(Ballew & Todorov,
2007; Little, Burriss, Jones, & Roberts, 2007; Todorov & Mandisodza, 2005) to sentencing decisions (Blair, Judd, & Chapleau,
2004; Eberhardt, Davies, Purdie-Vaughns, & Johnson, 2006). Like emotion recognition, trait
evaluations are automatic, subtle, and can be inferred accurately in less than
100 milliseconds (Willis & Todorov, 2006). Recent
research has focused on the processes involved in making social decisions inferred
from facial appearances (Bar, Neta, & Linz, 2006; Oosterhof & Todorov,
2009; Todorov, Baron, & Oosterhof, 2008; Todorov, Said, Engell, &
Oosterhof, 2008; Winston et al., 2002). In a critical study, Oosterhof and
Todorov (2008) looked at how neurologically normal individuals derive first
impressions from facial cues by using Principle Component Analysis to
understand the underlying structure of 15 traits commonly perceived in faces.

The authors found that the traits could be organized into two fundamental
dimensions, with the first principle component closely relating to perceived
trustworthiness and the second principle component corresponding to perceived dominance. 

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