Camacho M Catalina, Schwarzlose Rebecca F, Perino Michael T, Labonte Alyssa K, Koirala Sanju, Barch Deanna M, Sylvester Chad M
Department of Psychiatry, Washington University in St Louis School of Medicine, St Louis, Missouri.
Division of Biology and Biomedical Sciences, Washington University in St Louis School of Medicine, St Louis, Missouri.
JAMA Psychiatry. 2025 Mar 1;82(3):264-273. doi: 10.1001/jamapsychiatry.2024.4105.
The brain enters distinct activation states to support differential cognitive and emotional processes, but little is known about how brain activation states differ in youths with clinical anxiety.
To characterize brain activation states during socioemotional processing (movie stimuli) and assess associations between state characteristics and movie features and anxiety symptoms.
DESIGN, SETTING, AND PARTICIPANTS: The Healthy Brain Network is an ongoing cross-sectional study of individuals aged 5 to 21 years experiencing difficulties in school, of whom approximately 45% met criteria for a lifetime anxiety disorder diagnosis. Data used in this study are from the first 9 releases (collected in a nonclinical research setting in the New York City metropolitan area from 2015 to 2020) and include 620 youths aged 5 to 15 years (53% of whom met criteria for a lifetime anxiety disorder diagnosis) who watched an emotional video during functional magnetic resonance imaging and completed questionnaires and clinical evaluation. Of those with functional magnetic resonance imaging data, 432 youths aged 7 to 15 years also self-reported on anxiety symptoms. Data were processed and analyzed between February 2020 and August 2024.
A hidden Markov model was trained to identify brain activation states across participants during video watching. Time spent in each state and the moment-to-moment probability of being in each state were extracted. Videos were annotated for emotion-specific and nonspecific information using the EmoCodes system. Self-reported anxiety symptoms were assessed using the Screen for Child Anxiety Related Disorders. Time spent in each state across the video and during and outside of peaks in negative content correlated with generalized and social anxiety scores.
Among the 620 youths in the overall analysis, 369 were male and the mean (SD) age was 10.4 (2.8) years. In the anxiety symptom analysis, 263 of 432 youths were male and the mean (SD) age was 11.5 (2.2) years. Three brain activation states were identified: a high somatomotor activation state (state 1), a high cingulo-opercular network activation state (state 2), and a high ventral attention and default mode state (state 3). The probability of being in state 3 was correlated with video content that was more negative, quieter, and with less visual motion (ρ < 0.08; P < .001). Increased generalized anxiety was associated with greater time in state 3 (B, 0.10; 95% CI, 0.01 to 0.20; false discovery rate [FDR]-corrected P = .048) and less time in state 2 (B, -0.11; 95% CI, -0.21 to -0.02; FDR-corrected P = .048) when negative social cues were present.
Youths entered 3 distinct brain activation states during movie watching, and youths with anxiety spent more time in a state with high ventral attention and default activation during negative socioemotional processing. Youths high in generalized anxiety may be more engaged in deeply processing negative emotional content, which may influence self-regulation. Interventions that focus on changing physiological and psychological state during negative social interactions in youths with anxiety should be considered.
大脑会进入不同的激活状态以支持不同的认知和情感过程,但对于临床焦虑的青少年的大脑激活状态如何不同,我们知之甚少。
描述社会情感加工(电影刺激)过程中的大脑激活状态,并评估状态特征与电影特征及焦虑症状之间的关联。
设计、背景和参与者:健康大脑网络是一项正在进行的针对5至21岁在学校遇到困难的个体的横断面研究,其中约45%符合终生焦虑症诊断标准。本研究中使用的数据来自前9次发布(于2015年至2020年在纽约市大都市区的非临床研究环境中收集),包括620名5至15岁的青少年(其中53%符合终生焦虑症诊断标准),他们在功能磁共振成像期间观看了一段情感视频,并完成了问卷调查和临床评估。在有功能磁共振成像数据的青少年中,432名7至15岁的青少年还自我报告了焦虑症状。数据于2020年2月至2024年8月进行处理和分析。
训练一个隐马尔可夫模型以识别视频观看过程中参与者的大脑激活状态。提取在每个状态下花费的时间以及处于每个状态的瞬间概率。使用EmoCodes系统对视频进行情绪特异性和非特异性信息标注。使用儿童焦虑相关障碍筛查量表评估自我报告的焦虑症状。视频中在每个状态下花费的时间以及负面内容高峰期间和之外的时间与广泛性焦虑和社交焦虑得分相关。
在总体分析的620名青少年中,369名是男性,平均(标准差)年龄为10.4(2.8)岁。在焦虑症状分析中,432名青少年中有263名是男性,平均(标准差)年龄为11.5(2.2)岁。确定了三种大脑激活状态:高躯体运动激活状态(状态1)、高扣带回-脑岛网络激活状态(状态2)和高腹侧注意和默认模式状态(状态3)。处于状态3的概率与更负面、更安静且视觉运动较少的视频内容相关(ρ < 0.08;P <.001)。当存在负面社会线索时,广泛性焦虑增加与在状态3中花费更多时间相关(B,0.10;95%置信区间,0.01至0.20;错误发现率[FDR]校正后P =.048),而与在状态2中花费更少时间相关(B,-0.11;95%置信区间,-0.21至-0.02;FDR校正后P =.048)。
青少年在观看电影期间进入三种不同的大脑激活状态,患有焦虑症的青少年在负面社会情感加工过程中在高腹侧注意和默认激活状态下花费更多时间。广泛性焦虑程度高的青少年可能更专注于深入处理负面情绪内容,这可能会影响自我调节。应考虑针对改变患有焦虑症的青少年在负面社会互动期间的生理和心理状态的干预措施。