Objectives: Impulsivity is a core feature in bipolar disorder. Although mood symptoms exacerbate impulsivity, self-reports of impulsivity are elevated, even during euthymia. Neurocognitive processes linked to impulsivity (e.g., attention, inhibition) are also impaired in patients with bipolar disorder, and a high frequency of comorbidities associated with impulsivity, such as substance use disorders, further highlights the clinical relevance of this dimension of the illness. Our objective was to assess the relationship between impulsivity and cognition in bipolar disorder.
Methods: We evaluated impulsivity in 98 patients with bipolar disorder and its relationship with symptoms, cognition, and substance use history. We assessed self-reports of trait impulsivity [Barrett Impulsiveness Scale (BIS)] and impulsive behaviors on the Iowa Gambling Task (IGT). A comprehensive clinical and neurocognitive battery was also completed. Patients were compared with 95 healthy controls.
Results: Patients with bipolar disorder had higher scores versus healthy controls on all BIS scales. Performance on the IGT was significantly impaired and patients showed a tendency toward more erratic choices. Depressive symptoms were positively correlated with trait impulsivity and with an increased tendency to attend more readily to losses versus gains on the IGT. We found no significant associations between impulsivity and neurocognition in the full bipolar sample; however, when sub-grouped based on substance abuse history, significant relationships were revealed only in subjects without a substance abuse history.
Conclusions: Our data support prior reports of increased trait impulsivity and impairment on behavioral tasks of impulsiveness in bipolar disorder and suggest a differential relationship between these illness features that is dependent upon history of substance abuse.
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http://dx.doi.org/10.1111/bdi.12124 | DOI Listing |
Neuroradiology
January 2025
Department of Radiology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, 400016, China.
Introduction: Bipolar disorder (BD) and major depressive disorder (MDD) have overlapping clinical presentations which may make it difficult for clinicians to distinguish them potentially resulting in misdiagnosis. This study combined structural MRI and machine learning techniques to determine whether regional morphological differences could distinguish patients with BD and MDD.
Methods: A total of 123 participants, including BD (n = 31), MDD (n = 48), and healthy controls (HC, n = 44), underwent high-resolution 3D T1-weighted imaging.
Transl Psychiatry
January 2025
Department of Psychology, Goldsmiths University of London, London, UK.
Bipolar disorder (BD) involves altered reward processing and decision-making, with inconsistencies across studies. Here, we integrated hierarchical Bayesian modelling with magnetoencephalography (MEG) to characterise maladaptive belief updating in this condition. First, we determined if previously reported increased learning rates in BD stem from a heightened expectation of environmental changes.
View Article and Find Full Text PDFNeuropharmacology
January 2025
Department of Psychiatry and Center for Circadian Biology, University of California San Diego, La Jolla, CA, USA; VA San Diego Healthcare System, San Diego, CA, USA. Electronic address:
Bipolar disorder (BD) is a severe mental illness characterized by recurrent episodes of depression and mania. Lithium is the gold standard pharmacotherapy for BD, but outcomes are variable, and the relevant therapeutic mechanisms underlying successful treatment response remain uncertain. To identify synaptic markers of BD and lithium response, we measured the effects of lithium on induced pluripotent stem cell-derived neurons from BD patients and controls.
View Article and Find Full Text PDFFront Psychiatry
January 2025
Department of Psychiatry, Amsterdam UMC location Vrije Universiteit Amsterdam, Amsterdam, Netherlands.
Introduction: Unipolar and bipolar mood disorders in older adults are accompanied by cognitive impairment, including executive dysfunction, with a severe impact on daily life. Up and till now, strategies to improve cognitive functioning in late-life mood disorders (LLMD) are sparse. Therefore, we aimed to assess the efficacy of adaptive, computerized cognitive training (CT) on executive and subjective cognitive functioning in LLMD.
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