Centre de Psychiatrie et Neurosciences, INSERM-Université Paris Descartes, Paris, France.
Fédération de Recherche en Neurosciences, FR3636, CNRS-Université Paris Descartes, Paris, France.
Schizophr Bull. 2019 Oct 24;45(6):1358-1366. doi: 10.1093/schbul/sby186.
The ability to infer from uncertain information is impaired in schizophrenia and is associated with hallucinations and false beliefs. The accumulation of information is a key process for generating a predictive internal model, which statistically estimates an outcome from a specific situation. This study examines if updating the predictive model by the accumulation of information in absence of feedback is impaired in schizophrenia. We explored the implicit adaptation to the probability of being instructed to perform a movement (33%-Go, 50%-Go, or 66%-Go) in a Go/NoGo task in terms of reaction times (RTs), electromyographic activity, and corticospinal excitability (CSE) of primary motor cortex (M1). CSE was assessed at two time points to evaluate prediction of the upcoming instruction based on previously accumulated information: at rest (preceding the warning signal) and at the Go/NoGo signal onset. Three groups were compared: patients with schizophrenia (n = 20), unaffected siblings (n = 16), and healthy controls (n = 20). Controls and siblings showed earlier movement onset and increased CSE with higher Go probability. CSE adaptation seemed long-lasting, because the two CSE measures, at least 1500 ms apart, strongly correlated. Patients with schizophrenia failed to show movement onset (RT) adaptation and modulation of CSE. In contrast, all groups decreased movement duration with increasing Go probability. Modulation of CSE in the anticipatory phase of the potential movement reflected the estimation of upcoming response probability in unaffected controls and siblings. Impaired modulation of CSE supports the hypothesis that implicit adaptation to probabilistic context is altered in schizophrenia.
从不确定信息中推断的能力在精神分裂症中受损,与幻觉和错误信念有关。信息的积累是生成预测内部模型的关键过程,该模型从特定情况统计估计结果。本研究检查了在没有反馈的情况下通过信息积累来更新预测模型是否在精神分裂症中受损。我们探索了在 Go/NoGo 任务中,在没有反馈的情况下,根据被指示执行运动的概率(33%-Go、50%-Go 或 66%-Go)的信息积累,对运动潜伏期 (RT)、肌电图活动和初级运动皮层 (M1) 的皮质脊髓兴奋性 (CSE) 进行了隐性适应。评估了 CSE 在两个时间点上的情况,以根据之前积累的信息预测即将到来的指令:在休息时(在警告信号之前)和在 Go/NoGo 信号出现时。比较了三组:精神分裂症患者(n = 20)、未受影响的兄弟姐妹(n = 16)和健康对照组(n = 20)。对照组和兄弟姐妹的运动起始更快,随着 Go 概率的增加,CSE 也增加。CSE 适应似乎具有持久性,因为相隔至少 1500 毫秒的两个 CSE 测量值强烈相关。精神分裂症患者未能表现出运动起始(RT)适应和 CSE 调节。相比之下,所有组都随着 Go 概率的增加而减少运动持续时间。在潜在运动的预期阶段,CSE 的调制反映了未受影响的对照组和兄弟姐妹对即将到来的反应概率的估计。CSE 调节受损支持这样一种假设,即对概率上下文的隐性适应在精神分裂症中发生改变。