Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, Section of Psychiatry, University of Genoa, Genoa, Italy.
IRCCS Ospedale Policlinico San Martino, Genoa, Italy.
Hum Brain Mapp. 2019 Mar;40(4):1344-1352. doi: 10.1002/hbm.24453. Epub 2018 Oct 27.
Affective temperaments have been described since the early 20th century and may play a central role in psychiatric illnesses, such as bipolar disorder (BD). However, the neuronal basis of temperament is still unclear. We investigated the relationship of temperament with neuronal variability in the resting state signal-measured by fractional standard deviation (fSD) of Blood-Oxygen-Level Dependent signal-of the different large-scale networks, that is, sensorimotor network (SMN), along with default-mode, salience and central executive networks, in standard frequency band (SFB) and its sub-frequencies slow4 and slow5, in a large sample of healthy subject (HC, n = 109), as well as in the various temperamental subgroups (i.e., cyclothymic, hyperthymic, depressive, and irritable). A replication study on an independent dataset of 121 HC was then performed. SMN fSD positively correlated with cyclothymic z-score and was significantly increased in the cyclothymic temperament compared to the depressive temperament subgroups, in both SFB and slow4. We replicated our findings in the independent dataset. A relationship between cyclothymic temperament and neuronal variability, an index of intrinsic neuronal activity, in the SMN was found. Cyclothymic and depressive temperaments were associated with opposite changes in the SMN variability, resembling changes previously described in manic and depressive phases of BD. These findings shed a novel light on the neural basis of affective temperament and also carry important implications for the understanding of a potential dimensional continuum between affective temperaments and BD, on both psychological and neuronal levels.
情感气质自 20 世纪初以来就有描述,可能在精神疾病中发挥核心作用,如双相情感障碍(BD)。然而,气质的神经基础仍不清楚。我们研究了不同大尺度网络(即感觉运动网络(SMN),以及默认模式、突显和中央执行网络)静息状态信号的分数标准偏差(fSD)与气质之间的关系,该信号由血氧水平依赖信号测量,在标准频带(SFB)及其子频带 slow4 和 slow5 中,在一个大样本的健康受试者(HC,n=109)中,以及在各种气质亚组(即环性、高躁狂、抑郁和易怒)中。然后在一个独立的 121 名 HC 的数据集上进行了复制研究。SMN 的 fSD 与环性 z 分数呈正相关,并且在环性气质与抑郁气质亚组相比,在 SFB 和 slow4 中,SMN 的 fSD 明显增加。我们在独立数据集上复制了我们的发现。发现环性气质与 SMN 中的神经元变异性(内在神经元活动的指标)之间存在关系。环性和抑郁气质与 SMN 变异性的相反变化相关,类似于在 BD 的躁狂和抑郁阶段之前描述的变化。这些发现为情感气质的神经基础提供了新的认识,并且对理解情感气质和 BD 之间在心理和神经水平上的潜在维度连续性具有重要意义。