Cost Evaluation During Decision-Making in Patients at Early Stages of Psychosis.
Cost Evaluation During Decision-Making in Patients at Early Stages of Psychosis.
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DOI：
10.1162/cpsy_a_00020
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发表时间：
2019-02-01
期刊：
影响因子：
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通讯作者：
Murray, Graham K
中科院分区：
文献类型：
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作者：
Ermakova, Anna O;Gileadi, Nimrod;Murray, Graham K
在概率推理过程中仓促下结论是一种在精神病中可靠观察到的认知偏差，并且与妄想的形成有关。尽管这种认知偏差的原因尚不清楚，但一个建议是精神病患者可能认为采样信息的成本更高。然而，之前的计算模型提供的证据表明，慢性精神分裂症患者由于做出嘈杂的决策而草率下结论。我们开发了经典珠子任务的新颖版本，系统地操纵四个区块中信息收集的成本。对于 31 名患有早期精神病症状的个体和 31 名健康志愿者，我们检查了当信息抽样没有成本、固定成本或不断增加的成本时“做出决定”的数量。计算建模涉及估计信息采样参数和认知噪声参数的成本。总体而言，患者采样的信息少于对照组。然而，在成本较高、抽样信息较少的试验中，抽签次数的组间差异变得不那么明显。组差异的衰减并不是由于底线效应，因为在成本最高的区块中，参与者比理想的贝叶斯代理采样了更多的信息。计算模型表明，在信息采样没有客观成本的情况下，患者将比对照组更高的信息采样成本归咎于信息采样，Mann-Whitney U = 289，p = 0.007，噪声参数估计差异的边缘证据，t(60) = 1.86，p = 0.07。在患者中，精神病症状严重程度的个体差异与较高的信息采样成本有统计学显着相关性，rho = 0.6，p = 0.001，但与更多的认知噪声无关，rho = 0.27，p = 0.14；在对照组中，认知噪音可以预测精神分裂症的各个方面（与彼得斯妄想量表上的妄想样想法相关的专注和痛苦）。通过心理操纵和计算模型，我们提供的证据表明，早期精神病患者之所以急于得出结论，是因为采样信息的成本较高，而不是因为他们主要是吵闹的决策者。
Jumping to conclusions during probabilistic reasoning is a cognitive bias reliably observed in psychosis and linked to delusion formation. Although the reasons for this cognitive bias are unknown, one suggestion is that psychosis patients may view sampling information as more costly. However, previous computational modeling has provided evidence that patients with chronic schizophrenia jump to conclusions because of noisy decision-making. We developed a novel version of the classical beads task, systematically manipulating the cost of information gathering in four blocks. For 31 individuals with early symptoms of psychosis and 31 healthy volunteers, we examined the numbers of "draws to decision" when information sampling had no, a fixed, or an escalating cost. Computational modeling involved estimating a cost of information sampling parameter and a cognitive noise parameter. Overall, patients sampled less information than controls. However, group differences in numbers of draws became less prominent at higher cost trials, where less information was sampled. The attenuation of group difference was not due to floor effects, as in the most costly block, participants sampled more information than an ideal Bayesian agent. Computational modeling showed that, in the condition with no objective cost to information sampling, patients attributed higher costs to information sampling than controls did, Mann-Whitney U = 289, p = 0.007, with marginal evidence of differences in noise parameter estimates, t(60) = 1.86, p = 0.07. In patients, individual differences in severity of psychotic symptoms were statistically significantly associated with higher cost of information sampling, rho = 0.6, p = 0.001, but not with more cognitive noise, rho = 0.27, p = 0.14; in controls, cognitive noise predicted aspects of schizotypy (preoccupation and distress associated with delusion-like ideation on the Peters Delusion Inventory). Using a psychological manipulation and computational modeling, we provide evidence that early-psychosis patients jump to conclusions because of attributing higher costs to sampling information, not because of being primarily noisy decision makers.