Previous morphometric studies of Borderline Personality Disorder (BPD) reported inconsistent alterations in cortical and subcortical areas. However, these studies have investigated the brain at the voxel level using mass univariate methods or region of interest approaches, which are subject to several artifacts and do not enable detection of more complex patterns of structural alterations that may separate BPD from other clinical populations and healthy controls (HC). Multiple Kernel Learning (MKL) is a whole-brain multivariate supervised machine learning method able to classify individuals and predict an objective diagnosis based on structural features. As such, this method can help identifying objective biomarkers related to BPD pathophysiology and predict new cases. To this aim, we applied MKL to structural images of patients with BPD and matched HCs. Moreover, to ensure that results are specific for BPD and not for general psychological disorders, we also applied MKL to BPD against a group of patients with bipolar disorder, for their similarities in affective instability. Results showed that a circuit, including basal ganglia, amygdala, and portions of the temporal lobes and of the orbitofrontal cortex, correctly classified BPD against HC (80%). Notably, this circuit positively correlates with the affective sector of the Zanarini questionnaire, thus indicating an involvement of this circuit with affective disturbances. Moreover, by contrasting BPD with BD, the spurious regions were excluded, and a specific circuit for BPD was outlined. These results support that BPD is characterized by anomalies in a cortico-subcortical circuit related to affective instability and that this circuit discriminates BPD from controls and from other clinical populations.

Recent studies have shown that sympathetic nervous system (SNS) activity can be heavily impacted not only by basic threats to survival but also by threats to social bonds. In this study we explored the behavioral and physiological consequences of social exclusion/inclusion in patients with psoriasis, a disease frequently associated with the experience of being ostracized and with deficient emotion regulation skills. We employed a virtual ball-tossing game (Cyberball) to induce the experience of social exclusion/inclusion. We then used a Trust Game to measure the effects of this social modulation on trust. During Cyberball, infrared thermal imaging was used to record participants’ facial temperature and thus obtain an online measure of SNS activation. Behavioral data showed that social exclusion shifted participants’ trust toward unfamiliar players who had not previously excluded them. Physiological data indicated that in control participants, social exclusion triggered higher SNS activation than inclusion. No such effect was found in patients with psoriasis, whose SNS activity was the same during inclusion as it was during exclusion, suggesting that they benefit less from inclusive experiences than control participants. In addition, in patients but not in controls, higher SNS activation during social exclusion was linked to higher monetary investment toward unfamiliar players, a result in keeping with the social reconnection hypothesis, according to which emotions triggered by social rejection can be regulated by investing in new social interactions. We also found that an increase in periorbital temperature is accompanied by a decrease in happiness ratings after social exclusion was experienced during the Cyberball game. NEW & NOTEWORTHY Previous research on emotional processes in psoriasis has mainly employed self-report measures. In this study we used thermal imaging to obtain an online measure of the sympathetic nervous system (SNS) activity during social exclusion and tested how this experience influenced subsequent trust. We found that being included was a less positive experience for patients compared with controls and that SNS activity during exclusion had a stronger influence on subsequent trust in patients than in controls.

Objectives: Psoriasis is a chronic dermatologic disease which is frequently associated with psychological distress. Although studies suggest a relationship between this condition and difficulties in emotion regulation, behavioral and physiological evidence about this link is scarce. Methods:We measured implicit emotion regulation abilities of psoriasis patients and a healthy control group by examining the impact of distracting emotional (positive, negative or neutral) images on a working memory task ("Emotional N-Back") which could present high (2-back) or low (1-back) cognitive workload. Moreover, we used Functional Infrared Thermal Imaging to record participants' facial temperature and obtain a measure of the activation of the autonomic system. Rising of temperature over the peri-orbital areas and the nose tip are believed to reflect the activation and the de-activation of the sympathetic system, respectively.Results: Patients scored higher than controls on the "Lack of emotional clarity" subscale of the Difficulties in Emotion Regulation Scale. Compared to controls, who performed much better in the low vs. high cognitive load condition, patients showed a smaller accuracy difference between the two conditions. Moreover, patients showed less sympathetic (lower peri-orbital and higher nasal tip temperature) activity (especially in the negative and neutral blocks) during the high vs. low cognitive load condition, suggesting that the former condition might be less emotionally demanding for them. Conclusions: Patients benefit more than controls from the load-dependent interference effect when dealing with emotional information, thus therapeutic techniques aiming at teaching how to use cognitive strategies to downregulate emotions might be particularly appropriated for them.