The term emotional dysregulation refers to an impaired ability to regulate unwanted emotional states. Scientific evidence supports the idea that emotional dysregulation underlies several psychological disorders as, for example: personality disorders, bipolar disorder type II, interpersonal trauma, anxiety disorders, mood disorders and post-traumatic stress disorder. Emotional dysregulation may derive from early interpersonal traumas in childhood. These early traumatic events create a persistent sensitization of the central nervous system in relation to early life stressing events. For this reason, some authors suggest a common endophenotypical origin across psychopathologies. In the last 20 years, cognitive behavioral therapy has increasingly adopted an interactive-ontogenetic view to explain the development of disorders associated to emotional dysregulation. Unfortunately, standard Cognitive Behavior Therapy (CBT) methods are not useful in treating emotional dysregulation. A CBT-derived new approach called Schema Therapy (ST), that integrates theory and techniques from psychodynamic and emotion focused therapy, holds the promise to fill this gap in cognitive literature. In this model, psychopathology is viewed as the interaction between the innate temperament of the child and the early experiences of deprivation or frustration of the subject’s basic needs. This deprivation may lead to develop early maladaptive schemas (EMS), and maladaptive Modes. In the present paper we point out that EMSs and Modes are associated with either dysregulated emotions or with dysregulatory strategies that produce and maintain problematic emotional responses. Thanks to a special focus on the therapeutic relationship and emotion focused-experiential techniques, this approach successfully treats severe emotional dysregulation. In this paper, we make several comparisons between the main ideas of ST and the science of emotion regulation, and we present how to conceptualize pathological phenomena in terms of failed regulation and some of the ST strategies and techniques to foster successful regulation in patients.

Several studies have suggested a correlation between heart rate variability (HRV), emotion regulation (ER), psychopathological conditions, and cognitive functions in the past two decades. Specifically, recent data seem to support the hypothesis that low-frequency heart rate variability (LF-HRV), an index of sympathetic cardiac control, correlates with worse executive performances, worse ER, and specific psychopathological dimensions. The present work aims to review the previous findings on these topics and integrate them from two main cornerstones of this perspective: Porges’ Polyvagal Theory and Thayer and Lane’s Neurovisceral Integration Model, which are necessary to understand these associations better. For this reason, based on these two approaches, we point out that low HRV is associated with emotional dysregulation, worse cognitive performance, and transversal psychopathological conditions. We report studies that underline the importance of considering the heart-brain relation in order to shed light on the necessity to implement psychophysiology into a broader perspective on emotions, mental health, and good cognitive functioning. This integration is beneficial not only as a theoretical ground from which to start for further research studies but as a starting point for new theoretical perspectives useful in clinical practice.

The aim of this article is to present recent applications of emotion regulation theory and methods to the field of psychotherapy. The term Emotion Regulation refers to the neurocognitive mechanisms by which we regulate the onset, strength, and the eventual expression of our emotions. Deficits in the regulation of emotions have been linked to most, if not all, psychiatric disorders, with patients presenting either dysregulated emotions, or dysfunctional regulatory strategies. We discuss the implications of regulating emotions from two different theoretical perspectives: the Cognitive Emotion Regulation (CER), and the Experiential-Dynamic Emotion Regulation (EDER) model. Each proposes different views on how emotions are generated, dysregulated and regulated. These perspectives directly influence the way clinicians treat such problems. The CER model views emotional dysregulation as due to a deficit in regulation mechanisms that prioritizes modifying or developing cognitive skills, whilst the EDER model posits emotional dysregulation as due to the presence of dysregulatory mechanisms that prioritizes restoring natural regulatory processes. Examples of relevant techniques for each model are presented including a range of cognitive-behavioral, and experiential (including both dynamic and cognitive) techniques. The aim of the paper is to provide a toolbox from which clinician may gain different techniques to enhance and maintain their patient’s capacity for emotional regulation. Finally, the biological mechanisms behind the two models of emotion regulation are discussed as well as a proposal of a dual route model of emotion regulation.

Borderline personality disorder (BPD) is a severe personality disorder whose neural bases are still unclear. Indeed, previous studies reported inconsistent findings concerning alterations in cortical and subcortical areas. In the present study, we applied for the first time a combination of an unsupervised machine learning approach known as multimodal canonical correlation analysis plus joint independent component analysis (mCCA+jICA), in combination with a supervised machine learning approach known as random forest, to possibly find covarying gray matter and white matter (GM-WM) circuits that separate BPD from controls and that are also predictive of this diagnosis. The first analysis was used to decompose the brain into independent circuits of covarying grey and white matter concentrations. The second method was used to develop a predictive model able to correctly classify new unobserved BPD cases based on one or more circuits derived from the first analysis. To this aim, we analyzed the structural images of patients with BPD and matched healthy controls (HCs). The results showed that two GM-WM covarying circuits, including basal ganglia, amygdala, and portions of the temporal lobes and of the orbitofrontal cortex, correctly classified BPD against HC. Notably, these circuits are affected by specific child traumatic experiences (emotional and physical neglect, and physical abuse) and predict symptoms severity in the interpersonal and impulsivity domains. These results support that BPD is characterized by anomalies in both GM and WM circuits related to early traumatic experiences and specific symptoms.

Child trauma plays an important role in the etiology of Bordeline Personality Disorder (BPD). Of all traumas, sexual trauma is the most common, severe and most associated with receiving a BPD diagnosis when adult. Etiologic models posit sexual abuse as a prognostic factor in BPD. Here we apply machine learning using Multiple Kernel Regression to the Magnetic Resonance Structural Images of 20 BPD and 13 healthy control (HC) to see whether their brain predicts five sources of traumas: sex abuse, emotion neglect, emotional abuse, physical neglect, physical abuse (Child Trauma Questionnaire; CTQ). We also applied the same analysis to predict symptom severity in five domains: affective, cognitive, impulsivity, interpersonal (Zanarini Rating Scale for Borderline Personality Disorder; Zan-BPD) for BPD patients only. Results indicate that CTQ sexual trauma is predicted by a set of areas including the amygdala, the Heschl area, the Caudate, the Putamen, and portions of the Cerebellum in BPD patients only. Importantly, interpersonal problems only in BPD patients were predicted by a set of areas including temporal lobe and cerebellar regions. Notably, sexual trauma and interpersonal problems were not predicted by structural features in matched healthy controls. This finding may help elucidate the brain circuit affected by traumatic experiences and connected with interpersonal problems BPD suffer from.

The Sexual Inhibition Scales and Sexual Excitation Scales (Janssen et al., 2002a), based on the dual control model by Bancroft and Janssen (2000), are part of a 45-item self-report questionnaire evaluating individual tendencies to sexual inhibition or excitation according to three factors: two inhibition factors, SIS1, threat of performance failure, and SIS2, threat of performance consequences, and one excitation factor, SES. In this paper, we aimed to validate and explore psychometric properties of the SIS/SES in a sample of 2260 Italian men and women aged 18 to 75 years. Confirmatory factor analyses showed that the three-factor structure proposed in the original version of the scales fit with our sample. Moreover, our data confirmed the results of the original validation sample: Women scored higher on the SIS and lower on the SES than men did, but no significant differences appeared in the factor scores by age group, except for a gender × age interaction, where younger women had higher SIS2 scores. The SIS/SES appeared to be an effective, appropriate cross-cultural measurement of human sexuality in Italian samples, also shedding light on sexual arousal differences in women and men in our country. We also discuss clinical and therapeutic aspects.