6533b7dafe1ef96bd126e24f
RESEARCH PRODUCT
Cognitive variability in bipolar I disorder: A cluster-analytic approach informed by resting-state data
Bianca KollmannKenneth S. L. YuenMichèle WessaVanessa ScholzVanessa Scholzsubject
AdultMale0301 basic medicineBipolar DisorderBipolar I disorderNeuropsychological TestsImpulsivityExecutive Function03 medical and health sciencesCellular and Molecular NeuroscienceCognition0302 clinical medicineNeural PathwaysmedicineCluster AnalysisHumansBipolar disorderPharmacologyBrain MappingResting state fMRIAction intention and motor controlCognitive flexibilityBrainCognitionmedicine.diseaseExecutive functionsMagnetic Resonance ImagingCognitive test030104 developmental biologyImpulsive BehaviorFemalemedicine.symptomPsychology030217 neurology & neurosurgeryCognitive psychologydescription
Abstract Background While the presence of cognitive performance deficits in bipolar disorder I (BD-I) is well established, there is no consensus about which cognitive abilities are affected. Heterogeneous phenotypes displayed in BD-I further suggest the existence of subgroups among the disorder. The present study sought to identify different cognitive profiles among BD-I patients as well as potentially underlying neuronal network changes. Methods 54 euthymic BD-I patients underwent cognitive testing and resting state neuroimaging. Hierarchical cluster-analysis was performed on executive function scores of bipolar patients. The derived clusters were compared against 54 age-, gender- and IQ-matched healthy controls (HC) to facilitate the interpretation of results. Further, resting state network properties were compared to identify differences probably underlying cognitive profiles. Results A three-cluster solution emerged. Cluster 1 (n = 22) was characterized by deficits in cognitive flexibility and motor inhibition, cluster 2 (n = 12) displayed impulsive decision-making, while cluster 3 (n = 20) showed good visuospatial planning. Weaker connections in cluster 1 compared to cluster 2 were found between regions activated during tasks cluster 1 showed deficits on. Cluster 3 had a higher modularity than cluster 2, which correlated positively with problem solving performance and risk-taking in this cluster. Conclusion Obtained clusters showed distinct cognitive profiles, characterized by deficits and strengths, most of which remained precluded in a general comparison. Weaker interregional connections and separated subnetworks might underly behavioral deficits and strengths, respectively. The findings help explain the phenotypic heterogeneity observed in BD-I. This article is part of the Special Issue entitled ‘Current status of the neurobiology of aggression and impulsivity’.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2019-01-01 |