Rentzsch Johannes, Shen Christina, Jockers-Scherübl Maria C, Gallinat Jürgen, Neuhaus Andres H
Department of Psychiatry, Charité University Medicine, Berlin, Germany.
Department of Psychiatry, Charité University Medicine, Berlin, Germany; Department of Psychiatry, Oberhavel Hospital, Hennigsdorf, Germany.
PLoS One. 2015 May 8;10(5):e0126775. doi: 10.1371/journal.pone.0126775. eCollection 2015.
The predictive coding model is rapidly gaining attention in schizophrenia research. It posits the neuronal computation of residual variance ('prediction error') between sensory information and top-down expectation through multiple hierarchical levels. Event-related potentials (ERP) reflect cortical processing stages that are increasingly interpreted in the light of the predictive coding hypothesis. Both mismatch negativity (MMN) and repetition suppression (RS) measures are considered a prediction error correlates based on error detection and error minimization, respectively.
Twenty-five schizophrenia patients and 25 healthy controls completed auditory tasks designed to elicit MMN and RS responses that were investigated using repeated measures models and strong spatio-temporal a priori hypothesis based on previous research. Separate correlations were performed for controls and schizophrenia patients, using age and clinical variables as covariates.
MMN and RS deficits were largely replicated in our sample of schizophrenia patients. Moreover, MMN and RS measures were strongly correlated in healthy controls, while no correlation was found in schizophrenia patients. Single-trial analyses indicated significantly lower signal-to-noise ratio during prediction error computation in schizophrenia.
This study provides evidence that auditory ERP components relevant for schizophrenia research can be reconciled in the light of the predictive coding framework. The lack of any correlation between the investigated measures in schizophrenia patients suggests a disruption of predictive coding mechanisms in general. More specifically, these results suggest that schizophrenia is associated with an irregular computation of residual variance between sensory input and top-down models, i.e. prediction error.
预测编码模型在精神分裂症研究中迅速受到关注。它假定通过多个层次水平对感觉信息与自上而下的期望之间的残余方差(“预测误差”)进行神经元计算。事件相关电位(ERP)反映了皮质处理阶段,越来越多地根据预测编码假说来解释这些阶段。失配负波(MMN)和重复抑制(RS)测量分别基于错误检测和错误最小化被认为是预测误差的相关指标。
25名精神分裂症患者和25名健康对照完成了旨在引发MMN和RS反应的听觉任务,这些反应使用重复测量模型以及基于先前研究的强大时空先验假设进行研究。分别对对照和精神分裂症患者进行相关性分析,将年龄和临床变量作为协变量。
在我们的精神分裂症患者样本中,MMN和RS缺陷在很大程度上得到了重复验证。此外,MMN和RS测量在健康对照中高度相关,而在精神分裂症患者中未发现相关性。单次试验分析表明,精神分裂症患者在预测误差计算期间的信噪比显著降低。
本研究提供了证据,表明与精神分裂症研究相关的听觉ERP成分可以根据预测编码框架进行协调。精神分裂症患者中所研究测量指标之间缺乏任何相关性表明总体上预测编码机制受到破坏。更具体地说,这些结果表明精神分裂症与感觉输入和自上而下模型之间残余方差的不规则计算有关,即预测误差。