在跨诊断样本中评估社会无情:从计算精神病学镜头的洞察力
Katia M Harlé1,2,3, Danielle N Dun1,2, Andrea D Spadoni1,2,3
1VA San Diego Healthcare System, San Diego, CA, United States.
Journal of mood and anxiety disorders
|July 14, 2025
概括
在创伤幸存者中常见的社会无情症被用一个新的任务来研究. 研究结果将社会联系和焦虑与寻求奖励的行为联系起来,并确定与社会奖励处理相关的大脑机制.
科学领域:
- 神经科学是一个神经科学.
- 精神病学是一个精神病学.
- 计算精神病学是一种计算精神病学.
背景情况:
- 无情,以减少积极影响和寻求奖励为特征,在精神疾病中普遍存在,特别是在有创伤史的人群中.
- 社会无情感,表现为社会归属性受损和孤立度增加,与不良的临床结果有关,但其潜在机制仍然不太了解.
研究的目的:
- 在受创伤影响的个体中研究社会无情的神经认知机制.
- 开发和利用一种新的社会奖励探索任务,结合功能磁共振成像 (fMRI) 和计算建模.
主要方法:
- 33名遭受创伤的退伍军人的跨诊断样本在fMRI期间完成了社会奖励探索任务.
- 参与者旨在最大限度地获得未知的合作伙伴的赞美,并使用贝叶斯强化学习模型分析任务行为.
- 提取了奖励探索的认知和神经标志物.
主要成果:
- 更高的社会联系和焦虑水平独立地与更多基于模型的选择有关,有利于合作伙伴预计会给予更多的赞美.
- 在背部前带带皮层 (ACC) 和左下叶中,对奖励预测错误 (RPE) 的神经反应对赞美比非赞美更为积极.
- 在ACC中增加的正RPE激活与较低的焦虑水平相关.
结论:
- 对社会强化学习的计算方法可以在复杂的情感特征中揭示社会奖励敏感性的神经认知区别,例如在受创暴露的人群中看到的.
- 了解这些计算和神经差异对于开发针对社会无情的新型预测和治疗工具至关重要.
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