A neural architecture for imagined and overt speech motor dynamics

Mental imagery is a hallmark of human cognition, yet its neural mechanisms remain poorly understood. Speech imagery (the internal simulation of speech without overt articulation) has been proposed to partially share substrates with speech production, but its spatiotemporal dynamics remain controversial. Here, we leveraged high-resolution electrocorticography to investigate shared and modality-specific coding of articulatory kinematic trajectories during speech imagery and articulation. Linear modeling revealed robust articulatory kinematic trajectories encoding in frontoparietal cortex across modalities. Supramodal populations across middle premotor, subcentral and postcentral–supramarginal regions exhibited spatiotemporal stability during integrative planning. In contrast, modality-specific populations for speech imagery and articulation were somatotopically interleaved in primary sensorimotor cortex, revealing a distinct spatiotemporal organization. We further developed a generalized decoding framework that achieved high prediction accuracy for speech imagery (median 80.4%; chance 16.7%), comparable to speech articulation (78.3%). These findings uncover a somato-cognitive organization linking supramodal planning with modality-specific representations, informing imagery-based brain–computer interfaces. Using high-density electrocorticography, Zhao et al. reveal shared frontoparietal planning and modality-specific sensorimotor codes for imagined and spoken speech, enabling robust decoding of internal articulatory dynamics.

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Publication Details

Journal
Nature Neuroscience
Published
2026-09-29
DOI
https://doi.org/10.1038/s41593-026-02456-0
Primary Topic
Action Observation and Synchronization
Type
article
Field-Weighted Citation Impact
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article

A neural architecture for imagined and overt speech motor dynamics

Binke Yuan, Jinsong Wu, Junfeng Lu, Xing Tian et al.
Nature Neuroscience
Action Observation and Synchronization
article

A neural architecture for imagined and overt speech motor dynamics

Binke Yuan, Jinsong Wu, Junfeng Lu, Xing Tian, Zehao Zhao, Youkun Qian, Shelley Xiuli Tong, Gao Chen, Yan Liu, Yuanning Li, Yuan Yin, Zhenjie Wang, Xiaowei Gao
article en

Abstract

Mental imagery is a hallmark of human cognition, yet its neural mechanisms remain poorly understood. Speech imagery (the internal simulation of speech without overt articulation) has been proposed to partially share substrates with speech production, but its spatiotemporal dynamics remain controversial. Here, we leveraged high-resolution electrocorticography to investigate shared and modality-specific coding of articulatory kinematic trajectories during speech imagery and articulation. Linear modeling revealed robust articulatory kinematic trajectories encoding in frontoparietal cortex across modalities. Supramodal populations across middle premotor, subcentral and postcentral–supramarginal regions exhibited spatiotemporal stability during integrative planning. In contrast, modality-specific populations for speech imagery and articulation were somatotopically interleaved in primary sensorimotor cortex, revealing a distinct spatiotemporal organization. We further developed a generalized decoding framework that achieved high prediction accuracy for speech imagery (median 80.4%; chance 16.7%), comparable to speech articulation (78.3%). These findings uncover a somato-cognitive organization linking supramodal planning with modality-specific representations, informing imagery-based brain–computer interfaces. Using high-density electrocorticography, Zhao et al. reveal shared frontoparietal planning and modality-specific sensorimotor codes for imagined and spoken speech, enabling robust decoding of internal articulatory dynamics.

Nature Neuroscience
University of Hong Kong (HK)
Quality Education
Openalex Percentile: Top 7%
Action Observation and Synchronization
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