Long-term stability of computational parameters during approach-avoidance conflict in a transdiagnostic psychiatric patient sample.
Long-term stability of computational parameters during approach-avoidance conflict in a transdiagnostic psychiatric patient sample.
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DOI：
10.1038/s41598-021-91308-x
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发表时间：
2021-06-03
影响因子：
4.6
通讯作者：
Aupperle RL
中科院分区：
文献类型：
--
作者：
Smith R;Kirlic N;Stewart JL;Touthang J;Kuplicki R;McDermott TJ;Taylor S;Khalsa SS;Paulus MP;Aupperle RL
趋近-回避冲突（AAC）中的适应不良行为在多种精神疾病中很常见。使用计算模型，我们之前报道了抑郁、焦虑和物质使用障碍（DEP/ANX; SUDs）个体在决策不确定性和对负面结果与奖励（情绪冲突）的敏感性方面与健康对照组（hc）的差异。然而，随着时间的推移，这些计算参数和群体差异是否稳定仍然未知。我们分析了来自同一参与者子集（N = 325）的1年随访数据，以评估参数稳定性及其与其他临床和任务测量的关系。我们评估了整个样本的组差异，以及在hc （N = 48）、sud （N = 29）和DEP/ANX （N = 121）中匹配年龄和智商的子集。我们还评估了30例hcc单独样本的2-3周可靠性。情绪冲突与决策不确定性参数在1年内呈中等相关性（p < 0.05）。52和。46，分别)和中等至极好的相关性在较短的时间内(。84和。分别为54)。与先前的基线结果相似，参数与多项反应时间测量（ps < 0.001）和自我报告的焦虑(r =。30、p <。001)和决策难度(r =。44, p < 0.001)。线性混合效应分析显示，患者的决策不确定性仍然较高(sud, p =。009)，情绪冲突更低(sud, p =。[4], p =；02)相对于hc。因此，这种计算建模方法可能提供相对稳定的跨诊断精神病理学标记。
Maladaptive behavior during approach-avoidance conflict (AAC) is common to multiple psychiatric disorders. Using computational modeling, we previously reported that individuals with depression, anxiety, and substance use disorders (DEP/ANX; SUDs) exhibited differences in decision uncertainty and sensitivity to negative outcomes versus reward (emotional conflict) relative to healthy controls (HCs). However, it remains unknown whether these computational parameters and group differences are stable over time. We analyzed 1-year follow-up data from a subset of the same participants (N = 325) to assess parameter stability and relationships to other clinical and task measures. We assessed group differences in the entire sample as well as a subset matched for age and IQ across HCs (N = 48), SUDs (N = 29), and DEP/ANX (N = 121). We also assessed 2–3 week reliability in a separate sample of 30 HCs. Emotional conflict and decision uncertainty parameters showed moderate 1-year intra-class correlations (.52 and .46, respectively) and moderate to excellent correlations over the shorter period (.84 and .54, respectively). Similar to previous baseline findings, parameters correlated with multiple response time measures (ps < .001) and self-reported anxiety (r = .30, p < .001) and decision difficulty (r = .44, p < .001). Linear mixed effects analyses revealed that patients remained higher in decision uncertainty (SUDs, p = .009) and lower in emotional conflict (SUDs, p = .004, DEP/ANX, p = .02) relative to HCs. This computational modelling approach may therefore offer relatively stable markers of transdiagnostic psychopathology.
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影响因子：
2.7
作者：
Aupperle, Robin L.;Sullivan, Sarah;Melrose, Andrew J.;Paulus, Martin P.;Stein, Murray B.
通讯作者：
Stein, Murray B.
影响因子：
2.9
作者：
Friston, Karl;FitzGerald, Thomas;Pezzulo, Giovanni
通讯作者：
Pezzulo, Giovanni
影响因子：
5.2
作者：
Aupperle, Robin Leora;Paulus, Martin P.;Khalsa, Sahib S.
通讯作者：
Khalsa, Sahib S.
影响因子：
5.7
作者：
Friston, Karl J.;Mattout, Jeremie;Penny, Will
通讯作者：
Penny, Will
焦虑中的计算功能障碍：无法区分信号与噪声。
影响因子：
10.6
作者：
Huang H;Thompson W;Paulus MP
通讯作者：
Paulus MP