Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany.
Department of Psychiatry and Psychotherapy, Jena University Hospital, Jena, Germany; Department of Neurology, Jena University Hospital, Jena, Germany.
Neuropsychologia. 2019 Aug;131:139-147. doi: 10.1016/j.neuropsychologia.2019.04.021. Epub 2019 May 7.
Impulsivity as a trait modulates a range of cognitive functions, e.g. planning, decision-making, or response inhibition. Recent behavioural and psychometric findings challenge both the neurobiological models as well as the conceptualisation of psychometric measures of impulsivity. In the present study, we aimed to test the association of brain structure with the Barratt Impulsiveness Scale (BIS-11), a commonly applied self-rating instrument for impulsivity, using both the classical three-factor-model for impulsive behaviour (motor (IM), attentional (IA) and non-planning impulsivity (INP)), as well as the recently proposed alternative model contrasting inability to wait for reward (IWR) as an index of impulsive choice and rapid response style (RRS) as an index of impulsive action. We analysed brain structural data in a community sample of 85 healthy individuals, who completed the BIS-11, using voxel-based morphometry (CAT12: Computational Anatomy Toolbox 12). Regional volumes were correlated with the three traditional BIS-11 subscales, as well as IWR and RRS. BIS-11 total score was positively correlated with right inferior parietal, postcentral, and supramarginal grey matter (p < 0.05, FWE cluster-level corrected). Attentional impulsivity (IA) was also positively correlated with right inferior and superior parietal and supramarginal gyri. Comparison of the other scales did show some divergence, but most correlations did not survive correction for multiple comparisons. Our findings suggest that difference facets of trait impulsivity might be related to different brain areas, and might thus dissociate along distinct but overlapping neural networks. In contrast to lesion or patient studies, these analyses delineate physiological variance, and can thus help to conceptualise network models in the absence of pathology.
冲动性作为一种特质,调节着一系列认知功能,例如计划、决策或反应抑制。最近的行为和心理测量学发现,对神经生物学模型以及心理测量学冲动性测量的概念化都提出了挑战。在本研究中,我们旨在使用经典的冲动行为三因素模型(运动(IM)、注意力(IA)和非计划冲动性(INP))以及最近提出的对比无法等待奖励(IWR)作为冲动选择指标和快速反应风格(RRS)作为冲动行为指标的替代模型,测试大脑结构与巴瑞特冲动量表(BIS-11)之间的关联,BIS-11 是一种常用的冲动自评量表。我们对 85 名健康个体的大脑结构数据进行了分析,这些个体完成了 BIS-11,并使用了基于体素的形态测量学(CAT12:计算解剖工具箱 12)。区域体积与传统的 BIS-11 三个分量表以及 IWR 和 RRS 进行了相关分析。BIS-11 总分与右侧顶下小叶、中央后小叶和缘上回灰质呈正相关(p < 0.05,FWE 簇水平校正)。注意力冲动性(IA)也与右侧顶下小叶和顶上小叶以及缘上回呈正相关。比较其他量表确实显示出一些差异,但大多数相关性在进行多次比较校正后并未保留。我们的研究结果表明,特质冲动性的不同方面可能与不同的大脑区域相关,并且可能沿着不同但重叠的神经网络分离。与病变或患者研究不同,这些分析描绘了生理变异性,因此可以帮助在没有病理学的情况下概念化网络模型。