Emotion regulation in bipolar disorder type-I: multivariate analysis of fMRI data.

BACKGROUND: Bipolar disorder type-I (BD-I) patients are known to show emotion regulation abnormalities. In a previous fMRI study using an explicit emotion regulation paradigm, we compared responses from 19 BD-I patients and 17 matched healthy controls (HC). A standard general linear model-based univariate analysis revealed that BD patients showed increased activations in inferior frontal gyrus when instructed to decrease their emotional response as elicited by neutral images. We implemented multivariate pattern recognition analyses on the same data to examine if we could classify conditions within-group as well as HC versus BD. METHODS: We reanalyzed explicit emotion regulation data using a multivariate pattern recognition approach, as implemented in PRONTO software. The original experimental paradigm consisted of a full 2 × 2 factorial design, with valence (Negative/Neutral) and instruction (Look/Decrease) as within subject factors. RESULTS: The multivariate models were able to accurately classify different task conditions when HC and BD were analyzed separately (63.24%-75.00%, p = 0.001-0.012). In addition, the models were able to correctly classify HC versus BD with significant accuracy in conditions where subjects were instructed to downregulate their felt emotion (59.60%-60.84%, p = 0.014-0.018). The results for HC versus BD classification demonstrated contributions from the salience network, several occipital and frontal regions, inferior parietal lobes, as well as other cortical regions, to achieve above-chance classifications. CONCLUSIONS: Our multivariate analysis successfully reproduced some of the main results obtained in the previous univariate analysis, confirming that these findings are not dependent on the analysis approach. In particular, both types of analyses suggest that there is a significant difference of neural patterns between conditions within each subject group. The multivariate approach also revealed that reappraisal conditions provide the most informative activity for differentiating HC versus BD, irrespective of emotional valence (negative or neutral). The current results illustrate the importance of investigating the cognitive control of emotion in BD. We also propose a set of candidate regions for further study of emotional control in BD.

Differential diagnosis of bipolar affective disorder type II and borderline personality disorder: analysis of the affective dimension.

BACKGROUND: Differential diagnosis between bipolar affective disorder type II and borderline personality disorder can be problematic yet a priority for effective treatment planning. Diagnosis is problematic when symptoms do not present enough intensity or duration to clear the issue but also when there is a relative overlap of criteria between both disorders. If for many patients, the diagnosis is more easily differentiated, confounding conditions are found in 20% of cases for which it becomes a significant issue. METHOD: A research with the key words affective instability, borderline personality disorder, and bipolar disorder on Medline and Psych-Info was done. Other references were found through this review in related articles. Comparison of data about the affective dimensions concerning bipolar disorder and borderline personality disorder was noted. RESULTS: Affective instability is a confounding factor: quality and intensity of affects, speed of fluctuations, affective response to social stress, and its modulation are core elements of affective instability that need to be analyzed to clarify a proper diagnosis. LIMITATIONS: There is further necessity for research about affective instability in the 2 diagnoses. CONCLUSIONS: Making a valid differential diagnosis has an important clinical value in order for the clinician to plan proper treatment. Analysis of the affective experience and its qualitative and quantitative facets can help establish it.

Rapid screening for cognitive deficits in attention deficit and hyperactivity disorders with the screen for cognitive impairment in psychiatry.

Cognitive impairments constitute a core feature of attention deficit and hyperactivity disorders (ADHD), but are infrequently assessed in the clinical setting. We have previously demonstrated the ability of an objective cognitive battery, the Screen for Cognitive Impairment in Psychiatry (SCIP), to differentiate adult ADHD patients from healthy controls in five cognitive domains. Here, we further characterize these subtle cognitive deficits by conducting additional univariate analyses on our ADHD dataset to assess the contributions of various demographic characteristics on SCIP performance and to determine correlations between SCIP scores and scores on other measures evaluating illness severity, perceived cognitive deficits, and overall functioning. Age and years of education were moderately associated with performance on the SCIP and/or its subscales in our ADHD cohort. The SCIP global index score was moderately correlated with clinician-rated measures of illness severity and weakly associated with clinician-rated overall functional status. Intriguingly, overall SCIP performance was only weakly associated with patient self-reported measures of cognitive functioning. Of practical importance, small-to-moderate associations were consistently observed between performances on two subscales of the SCIP and the other measures evaluating illness severity, overall functioning, and patient self-reported cognitive functioning (the working memory and visuomotor tracking subscales). Thus, these data demonstrate that the SCIP, particularly the working memory and visuomotor tracking subscales, is sensitive enough to detect cognitive deficits in adult patients with ADHD, and that these deficits are correlated with functional impairments. Furthermore, these data highlight the importance of integrating both objective and subjective evaluations of cognition in adult ADHD.