Spatiotemporal encoding signatures of covert speech revealed by source-localized EEG and fMRI

Covert speech, the silent production of words without overt articulation, is fundamental to human cognition and a potential target for restoring communication in speech-impaired populations. Yet where, when, and how the human brain represents specific phrase content during covert speech remains largely unresolved. Here, we combine source-localized EEG (n = 57) with fMRI validation in the same cohort (n = 49) to map the encoding of five covert command phrases.

Phrase-discriminative activity is concentrated before estimated articulation onset, peaking at 200–400 ms and strongest in the theta band. Cross-modal representational similarity analysis reveals convergent EEG–fMRI phrase representations in left sensorimotor cortex, while phase-lag connectivity identifies left postcentral gyrus as a phrase-sensitive functional hub within a parietal-somatosensory-temporal sequence during the speech planning period. Beyond these group-level signatures, individual-specific encoding patterns substantially exceed group-average effects.

These findings provide a temporally precise, cross-validated cortical map of covert speech and identify targets for speech neuroscience and non-invasive brain-computer interfaces. We thank Wei Khang Jeremy Sim for writing the script for stimuli, LaiGuan Fong for helping with data collection, and Rong Hui Jonathan Chua and Parasuraman Padmanabhan for project administration. This work was supported by funding from the Cognitive Neuroimaging Centre, NTU Shared Research Facility (D821/CoNiC) and DSO National Laboratories (DSOCL21193).

V.L. is supported by the RIE2025 Human Potential Programme Prenatal/Early Childhood Grant (H22P0M0002), administered by A*STAR and by the Ministry of Education, Singapore under its Social Science & Humanities Research Fellowship (MOE2020-SSHR-008). College of Computing and Data Science, Nanyang Technological University, Singapore, Singapore Wei Zhang, Muyun Jiang, Zhiwei Guo, Shuailei Zhang & Cuntai Guan Cognitive Neuroimaging Centre, Nanyang Technological University, Singapore, Singapore Wei Zhang, Kok Ann Colin Teo & Raghavan Bhuvanakantham Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore IGP-Neuroscience, Interdisciplinary Graduate Programme, Nanyang Technological University, Singapore, Singapore Division of Neurosurgery, National University Health System, Singapore, Singapore DSO National Laboratories, Singapore, Singapore Early Mental Potential and Wellbeing Research (EMPOWER) Centre, Nanyang Technological University, Singapore, Singapore Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore Hungarian Research Network (HUN-REN), Budapest, Hungary Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden Center of AI in Medicine (C-AIM), Nanyang Technological University, Singapore, Singapore The authors declare no competing interests. Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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