心理学
自闭症
认知心理学
自闭症谱系障碍
推论
人口
意识的神经相关物
概念化
预测编码
精神分裂症(面向对象编程)
感知
贝叶斯推理
预测效度
感觉系统
神经科学
编码(社会科学)
人工智能
计算机科学
认知
贝叶斯概率
发展心理学
医学
精神科
统计
环境卫生
数学
作者
Luca Tarasi,Jelena Trajkovic,Stefano Diciotti,Giuseppe di Pellegrino,Francesca Ferri,Mauro Ursino,Vincenzo Romei
标识
DOI:10.1016/j.neubiorev.2021.11.006
摘要
The brain is a predictive machine. Converging data suggests a diametric predictive strategy from autism spectrum disorders (ASD) to schizophrenic spectrum disorders (SSD). Whereas perceptual inference in ASD is rigidly shaped by incoming sensory information, the SSD population is prone to overestimate the precision of their priors' models. Growing evidence considers brain oscillations pivotal biomarkers to understand how top-down predictions integrate bottom-up input. Starting from the conceptualization of ASD and SSD as oscillopathies, we introduce an integrated perspective that ascribes the maladjustments of the predictive mechanism to dysregulation of neural synchronization. According to this proposal, disturbances in the oscillatory profile do not allow the appropriate trade-off between descending predictive signal, overweighted in SSD, and ascending prediction errors, overweighted in ASD. These opposing imbalances both result in an ill-adapted reaction to external challenges. This approach offers a neuro-computational model capable of linking predictive coding theories with electrophysiological findings, aiming to increase knowledge on the neuronal foundations of the two spectra features and stimulate hypothesis-driven rehabilitation/research perspectives.
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