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在具有波动性的oddball任务中定位分层预测误差和精度:计算见解以及与健康个体心理社会功能的关系

Localizing hierarchical prediction errors and precisions during an oddball task with volatility: Computational insights and relationship with psychosocial functioning in healthy individuals.

作者信息

Charlton Colleen E, Hauke Daniel J, Wobmann Michelle, de Bock Renate, Andreou Christina, Borgwardt Stefan, Roth Volker, Diaconescu Andreea O

机构信息

Krembil Centre for Neuroinformatics, Centre for Addiction and Mental Health (CAMH), Toronto, ON, Canada.

Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom.

出版信息

Imaging Neurosci (Camb). 2025 Feb 3;3. doi: 10.1162/imag_a_00461. eCollection 2025.

Abstract

The auditory mismatch negativity (MMN) has been widely used to investigate deficits in early auditory information processing, particularly in psychosis. Predictive coding theories suggest that impairments in sensory learning may arise from disturbances in hierarchical message passing, likely due to aberrant precision-weighting of prediction errors (PEs). This study employed a modified auditory oddball paradigm with varying phases of stability and volatility to disentangle the impact of hierarchical PEs on auditory MMN generation in 43 healthy controls (HCs). Single-trial EEG data were modeled with a hierarchical Bayesian model of learning to identify neural correlates of low-level PEs about tones and high-level PEs about environmental volatility. Our analysis revealed a reduced expression of the auditory MMN in volatile compared to stable phases of the paradigm. Additionally, lower Global Functioning (GF): Social scores were associated with a reduced difference waveform at 332 ms after stimulus presentation across the entire MMN paradigm. Further analysis revealed that this association was present during the volatile phase but not the stable phase of the paradigm. Source reconstruction suggested that the association between the stable difference waveform and psychosocial functioning originated in the left superior temporal gyrus. Finally, we found significant EEG signatures of both low- and high-level PEs and precision ratios. Our findings highlight the value of computational models in understanding the neural mechanisms involved in early auditory information processing and their connection to psychosocial functioning.

摘要

听觉失匹配负波(MMN)已被广泛用于研究早期听觉信息处理中的缺陷,尤其是在精神病方面。预测编码理论表明,感觉学习障碍可能源于层次化信息传递的干扰,这可能是由于预测误差(PEs)的异常精确加权所致。本研究采用了一种经过修改的听觉oddball范式,该范式具有不同的稳定期和波动期,以厘清层次化PEs对43名健康对照者(HCs)听觉MMN产生的影响。单试次脑电图数据采用层次贝叶斯学习模型进行建模,以识别关于音调的低层次PEs和关于环境波动性的高层次PEs的神经关联。我们的分析显示,与范式的稳定期相比,波动期的听觉MMN表达降低。此外,较低的总体功能(GF):社交得分与整个MMN范式中刺激呈现后332毫秒时差异波形的减小有关。进一步分析表明,这种关联在范式的波动期存在,但在稳定期不存在。源重建表明,稳定差异波形与心理社会功能之间的关联起源于左侧颞上回。最后,我们发现了低层次和高层次PEs以及精确率的显著脑电图特征。我们的研究结果凸显了计算模型在理解早期听觉信息处理所涉及的神经机制及其与心理社会功能的联系方面的价值。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/951e/12319832/f0da4b23a2f4/imag_a_00461_fig1.jpg

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