Suppr超能文献

从皮质动力学和面部表情预测应激诱导性快感缺失的未来发展

Predicting Future Development of Stress-Induced Anhedonia From Cortical Dynamics and Facial Expression.

作者信息

Coley Austin A, Batra Kanha, Delahanty Jeremy M, Keyes Laurel R, Pamintuan Rachelle, Ramot Assaf, Hagemann Jim, Lee Christopher R, Liu Vivian, Adivikolanu Harini, Cressy Jianna, Jia Caroline, Massa Francesca, LeDuke Deryn, Gabir Moumen, Durubeh Bra'a, Linderhof Lexe, Patel Reesha, Wichmann Romy, Li Hao, Fischer Kyle B, Pereira Talmo, Tye Kay M

机构信息

The Salk Institute for Biological Studies, La Jolla, CA.

University of California, Los Angeles, Los Angeles, CA.

出版信息

bioRxiv. 2024 Dec 20:2024.12.18.629202. doi: 10.1101/2024.12.18.629202.

Abstract

The current state of mental health treatment for individuals diagnosed with major depressive disorder leaves billions of individuals with first-line therapies that are ineffective or burdened with undesirable side effects. One major obstacle is that distinct pathologies may currently be diagnosed as the same disease and prescribed the same treatments. The key to developing antidepressants with ubiquitous efficacy is to first identify a strategy to differentiate between heterogeneous conditions. Major depression is characterized by hallmark features such as anhedonia and a loss of motivation, and it has been recognized that even among inbred mice raised under identical housing conditions, we observe heterogeneity in their susceptibility and resilience to stress. Anhedonia, a condition identified in multiple neuropsychiatric disorders, is described as the inability to experience pleasure and is linked to anomalous medial prefrontal cortex (mPFC) activity. The mPFC is responsible for higher order functions, such as valence encoding; however, it remains unknown how mPFC valence-specific neuronal population activity is affected during anhedonic conditions. To test this, we implemented the unpredictable chronic mild stress (CMS) protocol in mice and examined hedonic behaviors following stress and ketamine treatment. We used unsupervised clustering to delineate individual variability in hedonic behavior in response to stress. We then performed 2-photon calcium imaging to longitudinally track mPFC valence-specific neuronal population dynamics during a Pavlovian discrimination task. Chronic mild stress mice exhibited a blunted effect in the ratio of mPFC neural population responses to rewards relative to punishments after stress that rebounds following ketamine treatment. Also, a linear classifier revealed that we can decode susceptibility to chronic mild stress based on mPFC valence-encoding properties prior to stress-exposure and behavioral expression of susceptibility. Lastly, we utilized markerless pose tracking computer vision tools to predict whether a mouse would become resilient or susceptible based on facial expressions during a Pavlovian discrimination task. These results indicate that mPFC valence encoding properties and behavior are predictive of anhedonic states. Altogether, these experiments point to the need for increased granularity in the measurement of both behavior and neural activity, as these factors can predict the predisposition to stress-induced anhedonia.

摘要

对于被诊断患有重度抑郁症的个体而言,当前心理健康治疗的现状是,数十亿人所接受的一线治疗要么无效,要么伴有不良副作用。一个主要障碍是,不同的病理状况目前可能被诊断为同一种疾病并开具相同的治疗方案。开发具有普遍疗效的抗抑郁药的关键在于首先确定一种区分异质性病症的策略。重度抑郁症的特征是诸如快感缺失和动力丧失等标志性特征,并且人们已经认识到,即使在相同饲养条件下饲养的近交小鼠中,我们也观察到它们在对压力的易感性和恢复力方面存在异质性。快感缺失是在多种神经精神疾病中都能发现的一种状况,被描述为无法体验愉悦感,并且与内侧前额叶皮质(mPFC)的异常活动有关。mPFC负责诸如效价编码等高级功能;然而,在快感缺失状态下,mPFC效价特异性神经元群体活动是如何受到影响的仍不清楚。为了对此进行测试,我们在小鼠中实施了不可预测的慢性轻度应激(CMS)方案,并在应激和氯胺酮治疗后检查了享乐行为。我们使用无监督聚类来描绘享乐行为中对应激的个体变异性。然后,我们进行了双光子钙成像,以在巴甫洛夫辨别任务期间纵向跟踪mPFC效价特异性神经元群体动态。慢性轻度应激小鼠在应激后mPFC神经群体对奖励与惩罚的反应比率方面表现出减弱的效应,而这种效应在氯胺酮治疗后会反弹。此外,一个线性分类器表明,我们可以在应激暴露和易感性的行为表现之前,根据mPFC效价编码特性来解码对慢性轻度应激的易感性。最后,我们利用无标记姿态跟踪计算机视觉工具,根据巴甫洛夫辨别任务期间的面部表情来预测小鼠是否会变得具有恢复力或易感性。这些结果表明,mPFC效价编码特性和行为能够预测快感缺失状态。总之,这些实验表明在行为和神经活动的测量中需要提高粒度,因为这些因素可以预测应激诱导的快感缺失的易感性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/04dc/11702711/59d4637db96b/nihpp-2024.12.18.629202v1-f0005.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验