Alexithymia and facial emotion recognition ability: An embodied hot and cold simulation perspective

Difficulty with knowing or identifying one’s internal feeling states is considered the hallmark feature of the personality construct of alexithymia. It is currently unclear, however, whether alexithymia also involves difficulty recognising external emotion cues, such as facial expressions of emotion. Facial expressions provide salient cues about one’s feelings, intentions and motivations that allow us to navigate our social contexts. Better facial emotion recognition is associated with positive outcomes across psychological, social and physical health domains. 
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\nTypically, the ability to recognise facial emotions has been assessed using cognitive tests underpinned by the traditional cognitive science perspective which postulates that our conceptual knowledge of emotion is stored as symbolic representations within the semantic memory network. Yet, the neuroscientific discovery of sensory-motor mirror neurons has led to embodied accounts of cognition that assume motor and somatosensory systems within the brain are also involved in recognising others’ emotion, with mirror neuron activity producing a re-experiencing or simulation of the observed emotion of the other in one’s self. 
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\nThe primary aim of this dissertation was to examine facial emotion recognition and alexithymia from a broad theoretical perspective. As the small number of previous studies on facial emotion recognition and alexithymia are mostly derived from the cognitive science perspective, this thesis included the embodied cognition theoretical viewpoint. In a series of six experiments, university students were assigned to three groups based on their scores on the Toronto Alexithymia Scale (TAS-20). Participants with TAS-20 scores above the clinical cut-off were divided into two groups, a ‘High Alexithymia’ group (HA) and a ‘Moderate Alexithymia’ group (MA), using median split for a comparison of mean scores. A control group comprised students with TAS-20 scores in the normal range. To reduce the confounding of results due to variables known to impair facial emotion recognition performance, all participants with clinical range scores on the Depression and Anxiety Scales (DASS) were excluded from participation. Significant differences were found between the HA and MA groups on various measures of performance in most of these experiments, using a different sample of participants for each experiment. 
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\nExperiment 1(a) examined the ability to accurately and rapidly identify dynamic facial expressions. Performance on this task is assumed to depend upon explicit access to schematic representations of emotion, which are proposed to be impoverished or unavailable to consciousness in individuals with alexithymia. While previous studies have typically utilised static stimuli, dynamic stimuli were used to provide ecological validity and to increase the level of task difficulty. Experiment 1(a) found that the HA and MA groups combined were significantly less accurate and slower to recognise facial expressions than controls. An unexpected finding was that the HA group were faster (but as accurate) on the task than the MA group.
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\nIt was thought that addressing the question of how groups perform under dynamic and static conditions might help to clarify this unusual pattern of results. This assumption was based on prior research findings suggesting that static faces are processed using motor simulation and dynamic faces using emotion simulation. Experiment 1(b) presented the same task as Experiment 1(a) under Static and Dynamic conditions. The results of Experiment 1(a) were replicated in the Dynamic condition of Experiment 1(b), with a different group of participants. Importantly, while the HA group were significantly faster to recognise facial expressions than the MA group under Dynamic conditions, these groups performed with equivalent speed under Static conditions. It was argued that this result is consistent with the idea that the HA group relied on the recruitment of motor-simulation processes to improve their performance in Experiments 1(a) and 1(b).
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\nA difficulty in interpreting the above studies is that the task itself relies upon linguistic processes. To reduce the possibility of a verbal deficit accounting for the results, Experiment 2 (a and b) required participants to make ‘same’ or ‘different’ discriminations of two static facial expression stimuli of high or low intensity of expression. No differences were found between groups in Experiment 2(a). Experiment 2(b) then increased the level of task difficulty by employing low intensity of expression stimuli. This was done to address the potential issue of using shallow information-processing strategies to perform the discrimination task. Results showed that while the HA group was less accurate than the MA group and controls, the MA group was slower than the HA group and controls. It was argued that the difficult task conditions of Experiment 2(b) involving degraded stimuli may have prompted the use of a compensatory motor-based strategy among the HA group, resulting in the facilitation of their speed, but not accuracy, to discriminate facial expressions, relative to the MA group. 
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\nExperiment 3 (a and b) examined facial emotion recognition from an embodied cognition perspective that allowed the examination of facial mimicry, which refers to congruent ‘micro-expressions’ of facial muscle activity that putatively support the recognition of others’ emotions. In Experiment 3(a), controls produced a greater amount of facial mimicry than the groups with clinical range TAS-20 scores and the HA group produced more mimicry the MA group. In addition, while the HA group and controls produced greater amounts of mimicry in the Happy condition than the Anger condition, the MA group produced equivalently low amounts of smile and frown facial reactions in both Expression conditions. 
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\nIt has been suggested that facial mimicry may not be an exclusively automatic reaction but rather depends on a number of goal-directed or top-down factors. Experiment 3(b) thus sought to further our understanding of these factors by exploring differences in performance following manipulation of the instruction given to participants. Within group comparisons showed that while controls produced a significant increase in frown facial mimicry when asked to adopt the observed emotion (Emotion Simulation condition) than when they passively viewed dynamic faces, the HA group produced similar levels of facial mimicry across the instruction conditions, while the MA group produced less frown facial mimicry in the Emotion Simulation condition than the Passive Viewing condition. It was argued this pattern of results is also consistent with the idea that the HA group employ a compensatory strategy involving the enhanced recruitment of action relevant simulation. It was also argued that the decrease in frown facial mimicry by the MA group only in response to the instruction to simulate anger may indicate that they rely instead on context dependent implicit learning of facial mimicry responses.
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\nA potential limitation of these experiments is the allocation of participants to categorical groups based on extreme TAS-20 total scores. On-going investigation of potential subtypes in alexithymia is clearly an important issue for future research. 
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\nThis series of experiments confirm that facial emotion recognition, discrimination and facial mimicry processes are detrimentally affected in alexithymia. This thesis also demonstrates the importance and utility of integrating notions of embodied forms of emotional processing into the conceptual framework of alexithymia and acts as a basis to prompt new treatment strategies for alexithymia based on simulation principles.

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