Supramodal and modality-specific neural information supports multi-feature prediction errors across cortical levels

超模态和模态特异性神经信息支持跨皮层水平的多特征预测误差。

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Abstract

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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