超模态和特定模态的神经信息支持跨皮质水平的多特征预测误差。

Imaging neuroscience (Cambridge, Mass.) Pub Date : 2025-09-15 eCollection Date: 2025-01-01 DOI:10.1162/IMAG.a.149
Maria Niedernhuber, Francesca Fardo, Micah Allen, Tristan Bekinschtein
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引用次数: 0

摘要

预测编码假设大脑主动预测来自不同感官的输入,当输入的信息偏离内部预期时,会产生预测错误。虽然许多研究都集中在由于违反单一感官特征而引起的预测误差上,但自然环境经常呈现出跨越多个刺激维度和感官模式的更复杂的事件。在本研究中,我们采用分层古怪范式(n = 30)操纵听觉和体感刺激来破坏一个或两个感觉特征,同时记录高密度脑电图。时间解码显示,虽然单和双偏差都诱发了持续的超模激活模式,但双偏差独特地在古怪的100毫秒后开始诱发超模反应。有效的连通性分析确定了不同模式下额下回之间的共同半球间相互作用,以及早期和联想感觉皮层内不同模式的特定连接。我们的研究结果表明,多特征预测误差涉及快速的超模态整合机制和分层组织的特定模态路径。这些结果促进了我们对大脑如何在不同层次的皮层处理中灵活整合多种感觉期望违规的理解,为支持预测性感知的神经结构提供了新的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Supramodal and modality-specific neural information supports multi-feature prediction errors across cortical levels.

Predictive coding posits that the brain actively anticipates inputs from different senses, generating prediction errors when incoming information deviates from internal expectations. While much research has focused on prediction errors elicited by violations of single sensory features, natural environments frequently present more complex events deviating across multiple stimulus dimensions and sensory modalities. In this study, we employed a hierarchical oddball paradigm (n = 30) manipulating auditory and somatosensory stimuli to violate one or two sensory features while high-density EEG was recorded. Temporal decoding revealed that while both single- and double-deviants evoked sustained supramodal activation patterns, double-deviants uniquely elicited a supramodal response starting at 100 ms after the oddball. Effective connectivity analyses identified shared interhemispheric interactions between inferior frontal gyri across modalities, as well as distinct modality-specific connectivity within early and associative sensory cortices. Our findings demonstrate that multi-feature prediction errors recruit both rapid supramodal integration mechanisms and hierarchically organized modality-specific pathways. These results advance our understanding of how the brain flexibly integrates multiple sensory expectation violations across different levels of cortical processing, providing new insights into the neural architecture supporting predictive perception.

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