Department of Bioengineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA, 19104, USA.
Department of Neuroscience, Perelman School of Medicine, University of Pennsylvania, Pennsylvania, PA, 19104, USA.
Mol Psychiatry. 2023 Aug;28(8):3314-3323. doi: 10.1038/s41380-023-02121-z. Epub 2023 Jun 23.
Schizophrenia is marked by deficits in facial affect processing associated with abnormalities in GABAergic circuitry, deficits also found in first-degree relatives. Facial affect processing involves a distributed network of brain regions including limbic regions like amygdala and visual processing areas like fusiform cortex. Pharmacological modulation of GABAergic circuitry using benzodiazepines like alprazolam can be useful for studying this facial affect processing network and associated GABAergic abnormalities in schizophrenia. Here, we use pharmacological modulation and computational modeling to study the contribution of GABAergic abnormalities toward emotion processing deficits in schizophrenia. Specifically, we apply principles from network control theory to model persistence energy - the control energy required to maintain brain activation states - during emotion identification and recall tasks, with and without administration of alprazolam, in a sample of first-degree relatives and healthy controls. Here, persistence energy quantifies the magnitude of theoretical external inputs during the task. We find that alprazolam increases persistence energy in relatives but not in controls during threatening face processing, suggesting a compensatory mechanism given the relative absence of behavioral abnormalities in this sample of unaffected relatives. Further, we demonstrate that regions in the fusiform and occipital cortices are important for facilitating state transitions during facial affect processing. Finally, we uncover spatial relationships (i) between regional variation in differential control energy (alprazolam versus placebo) and (ii) both serotonin and dopamine neurotransmitter systems, indicating that alprazolam may exert its effects by altering neuromodulatory systems. Together, these findings provide a new perspective on the distributed emotion processing network and the effect of GABAergic modulation on this network, in addition to identifying an association between schizophrenia risk and abnormal GABAergic effects on persistence energy during threat processing.
精神分裂症的特征是面部情感处理缺陷，与 GABA 能回路异常有关，也存在于一级亲属中。面部情感处理涉及包括杏仁核在内的边缘区域和梭状回在内的视觉处理区域等大脑区域的分布式网络。使用苯二氮䓬类药物（如阿普唑仑）对 GABA 能回路进行药理学调节，对于研究面部情感处理网络和精神分裂症中相关的 GABA 能异常非常有用。在这里，我们使用药理学调节和计算模型来研究 GABA 能异常对精神分裂症情感处理缺陷的贡献。具体来说，我们应用网络控制理论的原理来模拟情绪识别和回忆任务期间的持续能量——维持大脑激活状态所需的控制能量，在服用阿普唑仑和未服用阿普唑仑的情况下，在一级亲属和健康对照组中进行模拟。在这里，持续能量量化了任务期间理论外部输入的大小。我们发现，阿普唑仑在亲属中增加了威胁面孔处理过程中的持续能量，但在对照组中没有增加，这表明在这个未受影响的亲属样本中，存在相对缺乏行为异常的代偿机制。此外，我们证明了梭状回和枕叶区域在促进面部情感处理期间的状态转换方面很重要。最后，我们揭示了区域间差异控制能量（阿普唑仑与安慰剂）之间的空间关系 (i)，以及两者之间的关系 (ii) 都与 5-羟色胺和多巴胺神经递质系统有关，表明阿普唑仑可能通过改变神经调制系统来发挥作用。总的来说，这些发现为分布式情感处理网络以及 GABA 能调节对该网络的影响提供了新的视角，并确定了精神分裂症风险与威胁处理过程中 GABA 能异常对持续能量的影响之间的关联。
