Mood instability and risk-taking are hallmarks of borderline personality disorder (BPD). Schema modes are combinations of self-reflective evaluations, negative emotional states, and destructive coping strategies common in BPD. When activated, they can push patients with BPD into emotional turmoil and a dissociative state of mind. Our knowledge of the underlying neurocognitive mechanisms driving these changes is incomplete. We hypothesized that in patients with BPD, affective instability is more influenced by reward expectation, outcomes, and reward prediction errors (RPEs) during risky decision-making than in healthy controls. Additionally, we expected that these alterations would be related to schema modes.

Thirty-two patients with BPD and thirty-one healthy controls were recruited. We used an established behavioral paradigm to measure mood fluctuations during risky decision-making. The impact of expectations and RPEs on momentary mood was quantified by a computational model, and its parameters were estimated with hierarchical Bayesian analysis. Model parameters were compared using High-Density Intervals.

We found that model parameters capturing the influence of RPE and Certain Rewards on mood were significantly higher in patients with BPD than in controls. These model parameters correlated significantly with schema modes, but not with depression severity.

BPD is coupled with altered associations between mood fluctuation and reward processing under uncertainty. Our findings seem to be BPD-specific, as they stand in contrast with the correlates of depressive symptoms. Future studies should establish the clinical utility of these alterations, such as predicting or assessing therapeutic response in BPD.

It is known that female reproductive events and hormonal treatments can impact the course of bipolar disorder (BD) in women, some of whom are more vulnerable to the development of mood instability under periods of hormonal fluctuation. The mechanisms involved are, however, largely unknown. The aim of this work is to review the impact of sexual hormones on the course of BD, regarding a clinical case.

To explore the role of sexual hormones in BD.

Literature review using Medline database.

This is a case of a 36-year-old woman with type 1 BD who develops a manic episode after starting oral contraception (OC). This episode remitted with suspension of the pill. Estrogen and progesterone are involved in various aspects of brain function, such as brain development, synaptic plasticity, and modulation of neurotransmitter systems. Studies indicate that there is a relationship between ovarian hormones and intracellular signaling systems involved in the pathophysiology of BD. However, research on OC use in patients with mood disorders is limited. Recent studies state that OC aren’t associated with a worse clinical course and don’t negatively influence BD, while other studies show there is a subgroup of bipolar women that improve with hormonal stability, while others get worse.

Further studies are needed to determine possible relationships between sexual hormones and BD, and it is essential to identify patients vulnerable to these risks by measuring baseline hormone levels, assessing hormone sensitivity through a history of mood changes during menstrual cycle and a history of previous mental health problems.

No significant relationships.

BackgroundThe aim of this study was to characterize mood instability (MI) in Bipolar Disorder (BD) and to investigate potential differences between subtype I and II.

MethodsLife-charts from weekly mood ratings of 90 patients were used to compute: weeks spent with symptoms, number of episodes, and MI. Regression analyses were conducted to assess the relationship between BD subtype and MI adjusting by all potential confounding factors. Hierarchical cluster analysis was performed to determine the appropriate number of clusters that described the data and to assign subjects to a specific cluster based on their MI. We then compared clusters on clinical and psychosocial outcomes.

ResultsMedian follow-up was 5 years (IQR: 3.6–7.9). Patients spent 15.2%, 5%, and 3% of follow-up with depressive, manic, and mixed symptoms, respectively. BD type II presented higher MI (β = 1.83, 95% CI: 0.66–3.00) and subsydromal symptoms than BD type I patients. No differences in functioning or recurrences were found between subtypes. Differences in MI between the two clusters mimicked those between type I and II but enhanced (β = 3.86, 95%CI -4.72, -2.66). High MI (n = 43) patients presented poorer functioning and higher recurrences compared to Low MI patients (n = 43).

ConclusionBD type II presented higher MI and subsyndromal symptoms than BD type I patients. However, these differences did not translate into clinically relevant outcomes. A classification based on MI may provide useful clinical insights.

Aberrant emotional biases have been reported in bipolar disorder (BD), but results are inconsistent. Despite the clinical relevance of chronic mood variability in BD, there is no previous research investigating how the extent of symptom fluctuations in bipolar disorder might relate to emotional biases. This exploratory study investigated, in a large cohort of bipolar patients, whether instability in weekly mood episode symptoms and other clinical and demographic factors were related to emotional bias as measured in a simple laboratory task.

Participants (N = 271, BDI = 206, BDII = 121) completed an ‘emotional categorization and memory’ task. Weekly self-reported symptoms of depression and mania were collected prospectively. In linear regression analyses, associations between cognitive bias and mood variability were explored together with the influence of demographic and clinical factors, including current medication.

Greater accuracy in the classification of negative words relative to positive words was associated with greater instability in depressive symptoms. Furthermore, greater negative bias in free recall was associated with higher instability in manic symptoms. Participants diagnosed with BDII, compared with BDI, showed overall better word recognition and recall. Current antipsychotic use was associated with reduced instability in manic symptoms but this did not impact on emotional processing performance.

Emotional processing biases in bipolar disorder are related to instability in mood. These findings prompt further investigation into the underpinnings as well as clinical significance of mood instability.

Emotional lability (EL), characterized by negative emotional traits and emotional instability, is frequently reported in children and adults with attention deficit hyperactivity disorder (ADHD). However, EL is primarily assessed using retrospective self-report, which is subject to reporting bias and does not consider the potential influence of positive and negative everyday experiences.

Ambulatory assessment was carried out in 41 men with ADHD without co-morbidity, current medication or substance abuse, and 47 healthy control participants. Reports of negative and positive emotions (irritability, frustration, anger, happiness, excitement) and the occurrence of bad and good events were completed eight times daily during a working week. Group differences in emotional intensity and instability were investigated using multilevel models, and explored in relation to bad and good events and the Affective Lability Scale – Short Form (ALS-SF), an EL questionnaire.

The ADHD group reported significantly more frequent bad events, heightened intensity and instability of irritability and frustration, and greater intensity of anger. The results for positive emotions were equivocal or negative. Bad events significantly contributed to the intensity and instability of negative emotions, and showed a stronger influence in the ADHD group. However, covariation for their effect did not eliminate group differences. Small-to-moderate correlations were seen between intensity and instability of negative emotions and the ALS-SF.

Adults with ADHD report heightened intensity and instability of negative emotions in daily life. The results suggest two components of EL in ADHD: a reactive component responsive to bad events and an endogenous component, independent of negative everyday events.