Modeling perception and behavior in individuals at clinical high risk for psychosis: Support for the predictive processing framework.
Modeling perception and behavior in individuals at clinical high risk for psychosis: Support for the predictive processing framework.
复制标题
DOI：
10.1016/j.schres.2020.04.017
复制
发表时间：
2020-12
影响因子：
4.5
通讯作者：
Powers AR
中科院分区：
文献类型：
--
作者：
Kafadar E;Mittal VA;Strauss GP;Chapman HC;Ellman LM;Bansal S;Gold JM;Alderson-Day B;Evans S;Moffatt J;Silverstein SM;Walker EF;Woods SW;Corlett PR;Powers AR
精神病谱系障碍的早期干预对于最大化关键临床结果至关重要。虽然有一些证据表明在疾病的前驱阶段干预的效用，但如果没有适当的风险分层，干预的效果很难评估。这将需要生物标记物强有力地帮助识别风险水平，并且相对容易获得。最近的工作强调了基于计算机的行为任务在理解精神病症状病理生理学方面的效用。对这些任务的性能进行计算建模可能特别有用，因为它们将性能和症状表达明确而正式地联系起来。最近的几项研究已经成功地应用贝叶斯推理原理来理解幻觉的计算基础。在这个框架内，幻觉被认为是由于先验信念相对于感官证据的权重过大而产生的。最近发表的两个任务的数据支持了这一观点：条件幻觉（CH）任务，它决定了参与者在检测目标音调时使用期望的程度；以及正弦语音编码语音（SVS）任务，在该任务中，参与者可以使用先前的语音样本暴露来告知他们对退化语音刺激的理解。我们对两组临床精神病高危患者（CHR, N = 19）和健康对照组（HC, N = 17）进行了这两项任务。CHR参与者报告了更多的条件性幻觉和更多的训练前SVS检测。此外，还发现了参与者在两项任务中的表现之间的关系。在CHR任务行为的计算建模上，CHR参与者对任务波动性的识别能力明显较差，并且倾向于更高的先验权重。研究发现，后一种效应与两项任务的表现之间存在关系。综上所述，这些结果支持了这两个任务可能由感知推理中相似的潜在因素驱动的断言，并强调了基于计算的任务在识别风险方面的潜在效用。
Early intervention in psychotic spectrum disorders is critical for maximizing key clinical outcomes. While there is some evidence for the utility of intervention during the prodromal phase of the illness, efficacy of interventions is difficult to assess without appropriate risk stratification. This will require biomarkers that robustly help to identify risk level and are also relatively easy to obtain. Recent work highlights the utility of computer-based behavioral tasks for understanding the pathophysiology of psychotic symptoms. Computational modeling of performance on such tasks may be particularly useful because they explicitly and formally link performance and symptom expression. Several recent studies have successfully applied principles of Bayesian inference to understanding the computational underpinnings of hallucinations. Within this framework, hallucinations are seen as arising from an over-weighting of prior beliefs relative to sensory evidence. This view is supported by recently-published data from two tasks: the Conditioned Hallucinations (CH) task, which determines the degree to which participants use expectations in detecting a target tone; and a Sine-Vocoded Speech (SVS) task, in which participants can use prior exposure to speech samples to inform their understanding of degraded speech stimuli. We administered both of these tasks to two samples of participants at clinical high risk for psychosis (CHR; N = 19) and healthy controls (HC; N = 17). CHR participants reported both more conditioned hallucinations and more pre-training SVS detection. In addition, relationships were found between participants' performance on both tasks. On computational modeling of behavior on the CH task, CHR participants demonstrate significantly poorer recognition of task volatility as well as a trend toward higher weighting of priors. A relationship was found between this latter effect and performance on both tasks. Taken together, these results support the assertion that these two tasks may be driven by similar latent factors in perceptual inference, and highlight the potential utility of computationally-based tasks in identifying risk.
登录
查看更多内容
DOI：
10.1098/rstb.2005.1622
发表时间：
2005-04-29
影响因子：
6.3
作者：
Friston, KJ
通讯作者：
Friston, KJ
影响因子：
14.5
作者：
Alderson-Day, Ben;Lima, Cesar F.;Scott, Sophie K.
通讯作者：
Scott, Sophie K.
影响因子：
6.7
作者：
Corlett, P. R.;Taylor, J. R.;Wang, X. -J.;Fletcher, P. C.;Krystal, J. H.
通讯作者：
Krystal, J. H.
影响因子：
2.6
作者：
Corlett PR;Fletcher PC
通讯作者：
Fletcher PC
影响因子：
6.6
作者：
Carrion, Ricardo E.;Auther, Andrea M.;Cornblatt, Barbara A.
通讯作者：
Cornblatt, Barbara A.