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Alexithymia is a subclinical condition characterized by impaired awareness of one’s emotional states, which has profound effects on mental health and social interaction. Despite the clinical significance of this condition, the neurocognitive impairment(s) that lead to alexithymia remain unclear. Recent theoretical models suggest that impaired anterior insula (AI) functioning might be involved in alexithymia, but conclusive evidence for this hypothesis is lacking. We measured alexithymia levels in a large sample of brain-injured patients (N=129) and non-brain-injured control participants (N=33), to determine whether alexithymia can be acquired after pronounced damage to the AI. Alexithymia levels were first analyzed as a function of group, with patients separated into four groups based on AI damage: patients with >15% damage to AI, patients with <15% damage to AI, patients with no damage to AI, and healthy controls. An ANOVA revealed that alexithymia levels varied across groups (p=0.009), with >15% AI damage causing higher alexithymia relative to all other groups (all p<0.01). Next, a multiple linear regression model was fit with the degree of damage to AI, the degree of damage to a related region (the anterior cingulate cortex, ACC), and the degree of damage to the whole brain as predictor variables, and alexithymia as the dependent variable. Critically, increased AI damage predicted increased alexithymia after controlling for the other two regressors (ACC damage; total lesion volume). Collectively, our results suggest that pronounced AI damage causes increased levels of alexithymia, providing critical evidence that this region supports emotional awareness.

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Traumatic brain injury (TBI) is a major public health concern in both civilian and military populations. Recently, genetics studies have begun to identify individual differences in polymorphisms that could affect recovery and outcome of cognitive and social processes following TBI. This review considers the potential for polymorphisms to influence six specific cognitive and social functions, which represent the most prominent domains of impairment following TBI: working memory, executive function, decision making, inhibition and impulsivity, aggression, and social and emotional function. Examining the influence of polymorphisms on TBI outcome has the potential to contribute to an understanding of variations in TBI outcome, aid in the triaging and treatment of TBI patients, and ultimately lead to targeted interventions based on genetic profiles.

Accumulating neuroscience evidence indicates that human intelligence is supported by a distributed network of frontal and parietal regions that enable complex, goal-directed behaviour. However, the contributions of this network to social aspects of intellectual function remain to be well characterized. Here, we report a human lesion study (n = 144) that investigates the neural bases of social problem solving (measured by the Everyday Problem Solving Inventory) and examine the degree to which individual differences in performance are predicted by a broad spectrum of psychological variables, including psychometric intelligence (measured by the Wechsler Adult Intelligence Scale), emotional intelligence (measured by the Mayer, Salovey, Caruso Emotional Intelligence Test), and personality traits (measured by the Neuroticism-Extraversion-Openness Personality Inventory). Scores for each variable were obtained, followed by voxel-based lesion-symptom mapping. Stepwise regression analyses revealed that working memory, processing speed, and emotional intelligence predict individual differences in everyday problem solving. A targeted analysis of specific everyday problem solving domains (involving friends, home management, consumerism, work, information management, and family) revealed psychological variables that selectively contribute to each. Lesion mapping results indicated that social problem solving, psychometric intelligence, and emotional intelligence are supported by a shared network of frontal, temporal, and parietal regions, including white matter association tracts that bind these areas into a coordinated system. The results support an integrative framework for understanding social intelligence and make specific recommendations for the application of the Everyday Problem Solving Inventory to the study of social problem solving in health and disease.