Institute for Drug and Alcohol Studies, Virginia Commonwealth University, Richmond, Virginia; Department of Radiology, Virginia Commonwealth University, Richmond, Virginia.
Department of Psychiatry, Virginia Commonwealth University, Richmond, Virginia; Department of Psychiatry, Texas A&M University Health Science Center, Bryan, Texas.
Biol Psychiatry Cogn Neurosci Neuroimaging. 2021 May;6(5):545-555. doi: 10.1016/j.bpsc.2020.09.015. Epub 2020 Oct 7.
Anxiety and depression symptoms are common among cannabis users and could be a risk factor for cannabis use (CU) disorder. Thus, it is critical to understand the neuronal circuits underlying the associations between CU and these symptoms. Alterations in resting-state functional connectivity within and/or between the default mode network and salience network have been reported in CU, anxiety, and depressive disorders and thus could be a mechanism underlying the associations between CU disorder and anxiety/depression symptoms.
Using resting-state functional magnetic resonance imaging, effective connectivities (ECs) among 9 major nodes from the default mode network and salience network were measured using dynamic causal modeling in 2 datasets: the Human Connectome Project (28 CU participants and 28 matched non-drug-using control participants) and a local CU study (21 CU participants and 21 matched non-drug-using control participants) in separate and parallel analyses.
Relative to the control participants, right amygdala to left amygdala, anterior cingulate cortex to left amygdala, and medial prefrontal cortex to right insula ECs were greater, and left insula to left amygdala EC was smaller in the CU group. Each of these ECs showed a reliable linear relationship with at least one of the anxiety/depression measures. Most findings on the right amygdala to left amygdala EC were common to both datasets.
Right amygdala to left amygdala and anterior cingulate cortex to left amygdala ECs may be related to the close associations between CU and anxiety/depression symptoms. The findings on the medial prefrontal cortex to right insula and left insula to left amygdala ECs may reflect a compensatory mechanism.
焦虑和抑郁症状在大麻使用者中很常见,可能是大麻使用障碍(CU 障碍)的一个风险因素。因此,了解 CU 与这些症状之间关联的神经回路是至关重要的。在 CU、焦虑和抑郁障碍中,已经报道了静息态功能连接在内侧默认模式网络和突显网络之间和/或之内的改变,因此可能是 CU 障碍与焦虑/抑郁症状之间关联的一种机制。
使用静息态功能磁共振成像,通过动态因果建模在两个数据集(人类连接组计划(28 名 CU 参与者和 28 名匹配的非药物使用对照参与者)和一个当地 CU 研究(21 名 CU 参与者和 21 名匹配的非药物使用对照参与者))中测量 9 个主要节点的默认模式网络和突显网络之间的有效连接(ECs)。
与对照组相比,CU 组的右侧杏仁核到左侧杏仁核、前扣带皮层到左侧杏仁核和内侧前额叶皮层到右侧岛叶的 EC 更大,左侧岛叶到左侧杏仁核的 EC 更小。这些 EC 中的每一个都与至少一个焦虑/抑郁测量值显示出可靠的线性关系。两个数据集之间的右杏仁核到左杏仁核 EC 的大部分发现都是共同的。
右侧杏仁核到左侧杏仁核和前扣带皮层到左侧杏仁核的 EC 可能与 CU 和焦虑/抑郁症状之间的密切关联有关。内侧前额叶皮层到右侧岛叶和左侧岛叶到左侧杏仁核的 EC 发现可能反映了一种代偿机制。