RESUMEN
BACKGROUND: Alexithymia describes an abnormality of emotional experience that is commonly expressed among individuals with addiction and alcohol abuse disorders. Alexithymic individuals are characterized by difficulties in identifying and describing their emotions. This impairment is linked to the development and maintenance of addiction. Moreover, an emergent theory suggests alexithymia is itself secondary to a failure of interoception (sensitivity to internal bodily signals, including physiological arousal states). METHODS: This study tested for hypothesized contributory roles of alexithymia and dysfunctional interoception in the expression of social drinking. Alexithymia, subjective sensitivity to bodily sensations, and alcohol consumption scores were quantified using the Toronto Alexithymia Scale, the Body Perception Questionnaire, and the Alcohol Use Questionnaire, respectively, in a normative sample (N = 600). Regression and bootstrapping mediation analyses were used to test the hypothesis that alexithymia mediated the association between sensitivity to bodily sensations and alcohol consumption. RESULTS: Alexithymia was positively correlated with sensitivity to bodily sensations and with alcohol consumption. Mediation analysis revealed that alexithymia, and more precisely, difficulty in identifying feelings, mediated the relationship between sensitivity to bodily sensations and alcohol consumption, such that the predictive effect of sensitivity to bodily sensations on alcohol intake became nonsignificant when controlling for alexithymia. CONCLUSIONS: These results indicate that alexithymia is associated with subjective hypersensitivity to bodily sensations. Moreover, our findings support the theoretical proposal that alexithymia is an expression of impaired processing of bodily sensations including physiological arousal, which underpin the development of maladaptive coping strategies, including alcohol use disorders. Our observations extend a growing literature emphasizing the importance of interoception and alexithymia in addiction, which can inform the development of new therapeutic strategies.
Asunto(s)
Síntomas Afectivos/diagnóstico , Síntomas Afectivos/psicología , Consumo de Bebidas Alcohólicas/psicología , Autoevaluación (Psicología) , Sensación/fisiología , Adolescente , Adulto , Síntomas Afectivos/epidemiología , Anciano , Consumo de Bebidas Alcohólicas/epidemiología , Femenino , Humanos , Masculino , Persona de Mediana Edad , Encuestas y Cuestionarios , Adulto JovenRESUMEN
The visual system processes natural scenes in a split second. Part of this process is the extraction of "gist," a global first impression. It is unclear, however, how the human visual system computes this information. Here, we show that, when human observers categorize global information in real-world scenes, the brain exhibits strong sensitivity to low-level summary statistics. Subjects rated a specific instance of a global scene property, naturalness, for a large set of natural scenes while EEG was recorded. For each individual scene, we derived two physiologically plausible summary statistics by spatially pooling local contrast filter outputs: contrast energy (CE), indexing contrast strength, and spatial coherence (SC), indexing scene fragmentation. We show that behavioral performance is directly related to these statistics, with naturalness rating being influenced in particular by SC. At the neural level, both statistics parametrically modulated single-trial event-related potential amplitudes during an early, transient window (100-150 ms), but SC continued to influence activity levels later in time (up to 250 ms). In addition, the magnitude of neural activity that discriminated between man-made versus natural ratings of individual trials was related to SC, but not CE. These results suggest that global scene information may be computed by spatial pooling of responses from early visual areas (e.g., LGN or V1). The increased sensitivity over time to SC in particular, which reflects scene fragmentation, suggests that this statistic is actively exploited to estimate scene naturalness.