Melbourne School of Psychological Sciences, University of Melbourne, Parkville 3010, Victoria, Australia
Queensland Brain Institute, University of Queensland, Brisbane 4072, Queensland, Australia.
J Neurosci. 2020 Aug 26;40(35):6759-6769. doi: 10.1523/JNEUROSCI.0315-20.2020. Epub 2020 Jul 20.
Our perceptions result from the brain's ability to make inferences, or predictive models, of sensory information. Recently, it has been proposed that psychotic traits may be linked to impaired predictive processes. Here, we examine the brain dynamics underlying statistical learning and inference in stable and volatile environments, in a population of healthy human individuals ( = 75; 36 males, 39 females) with a range of psychotic-like experiences. We measured prediction error responses to sound sequences with electroencephalography, gauged sensory inference explicitly by behaviorally recording sensory statistical learning errors, and used dynamic causal modeling to tap into the underlying neural circuitry. We discuss the findings that were robust to replication across the two experiments (Discovery dataset, = 31; Validation dataset, = 44). First, we found that during stable conditions, participants demonstrated greater precision in their predictive model, reflected in a larger prediction error response to unexpected sounds, and decreased statistical learning errors. Moreover, individuals with attenuated prediction errors in stable conditions were found to make greater incorrect predictions about sensory information. Critically, we show that greater errors in statistical learning and inference are related to increased psychotic-like experiences. These findings link neurophysiology to behavior during statistical learning and prediction formation, as well as providing further evidence for the idea of a continuum of psychosis in the healthy, nonclinical population. While perceiving the world, we make inferences by learning the statistics present in the sensory environment. It has been argued that psychosis may emerge because of a failure to learn sensory statistics, resulting in an impaired representation of the world. Recently, it has been proposed that psychosis exists on a continuum; however, there is conflicting evidence on whether sensory learning deficits align on the nonclinical end of the psychosis continuum. We found that statistical learning of sensory events is associated with the magnitude of mismatch negativity and, critically, is impaired in healthy people who report more psychotic-like experiences. We replicated these findings in an independent sample, demonstrating strengthened credibility to support the continuum of psychosis that extends into the nonclinical population.
我们的感知源于大脑对感官信息进行推断或预测模型的能力。最近有人提出,精神特质可能与预测过程受损有关。在这里,我们研究了在稳定和不稳定环境中,在一组具有不同程度类精神病体验的健康人类个体(= 75;36 名男性,39 名女性)中,统计学习和推理的大脑动力学。我们使用脑电图测量了对声音序列的预测误差反应,通过行为记录感官统计学习错误来明确测量感官推断,并使用动态因果建模来挖掘潜在的神经回路。我们讨论了在两个实验中都具有复制性的发现(发现数据集,= 31;验证数据集,= 44)。首先,我们发现,在稳定的情况下,参与者表现出更精确的预测模型,这反映在对意外声音的预测误差响应更大,以及统计学习错误减少。此外,在稳定条件下衰减预测误差的个体被发现对感官信息做出更大的错误预测。至关重要的是,我们表明,统计学习和推断中的较大错误与增加的类精神病体验有关。这些发现将神经生理学与统计学习和预测形成期间的行为联系起来,并为健康非临床人群中精神病的连续体这一观点提供了进一步的证据。在感知世界时,我们通过学习感官环境中的统计数据来进行推断。有人认为,精神病可能是由于未能学习到感官统计数据而出现的,导致对世界的表示受损。最近,有人提出精神病是连续的;然而,在非临床精神病连续体的末端是否存在感官学习缺陷,这方面存在相互矛盾的证据。我们发现,对感官事件的统计学习与失匹配负波的幅度有关,而且,在报告更多类精神病体验的健康人中,统计学习受损。我们在一个独立的样本中复制了这些发现,为支持扩展到非临床人群的精神病连续体的可信度提供了更强有力的支持。