An Approach to Simultaneous Acquisition of Real-Time MRI Video, EEG, and Surface EMG for Articulatory, Brain, and Muscle Activity During Speech Production
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arXiv
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| Auteurs principaux: | , , , , , , , , , , , , , , , , , , |
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| Format: | Preprint |
| Publié: |
2026
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| _version_ | 1866918371334815744 |
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| author | Lee, Jihwan Razmara, Parsa Huang, Kevin Foley, Sean Kommineni, Aditya Hsu, Haley Jeong, Woojae Kumar, Prakash Shi, Xuan Lee, Yoonjeong Feng, Tiantian Medani, Takfarinas Tian, Ye Kadiri, Sudarsana Reddy Nayak, Krishna S. Byrd, Dani Goldstein, Louis Leahy, Richard M. Narayanan, Shrikanth |
| author_facet | Lee, Jihwan Razmara, Parsa Huang, Kevin Foley, Sean Kommineni, Aditya Hsu, Haley Jeong, Woojae Kumar, Prakash Shi, Xuan Lee, Yoonjeong Feng, Tiantian Medani, Takfarinas Tian, Ye Kadiri, Sudarsana Reddy Nayak, Krishna S. Byrd, Dani Goldstein, Louis Leahy, Richard M. Narayanan, Shrikanth |
| contents | Speech production is a complex process spanning neural planning, motor control, muscle activation, and articulatory kinematics. While the acoustic speech signal is the most accessible product of the speech production act, it does not directly reveal its causal neurophysiological substrates. We present the first simultaneous acquisition of real-time (dynamic) MRI, EEG, and surface EMG, capturing several key aspects of the speech production chain: brain signals, muscle activations, and articulatory movements. This multimodal acquisition paradigm presents substantial technical challenges, including MRI-induced electromagnetic interference and myogenic artifacts. To mitigate these, we introduce an artifact suppression pipeline tailored to this tri-modal setting. Once fully developed, this framework is poised to offer an unprecedented window into speech neuroscience and insights leading to brain-computer interface advances. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_04840 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | An Approach to Simultaneous Acquisition of Real-Time MRI Video, EEG, and Surface EMG for Articulatory, Brain, and Muscle Activity During Speech Production Lee, Jihwan Razmara, Parsa Huang, Kevin Foley, Sean Kommineni, Aditya Hsu, Haley Jeong, Woojae Kumar, Prakash Shi, Xuan Lee, Yoonjeong Feng, Tiantian Medani, Takfarinas Tian, Ye Kadiri, Sudarsana Reddy Nayak, Krishna S. Byrd, Dani Goldstein, Louis Leahy, Richard M. Narayanan, Shrikanth Audio and Speech Processing Artificial Intelligence Computation and Language Speech production is a complex process spanning neural planning, motor control, muscle activation, and articulatory kinematics. While the acoustic speech signal is the most accessible product of the speech production act, it does not directly reveal its causal neurophysiological substrates. We present the first simultaneous acquisition of real-time (dynamic) MRI, EEG, and surface EMG, capturing several key aspects of the speech production chain: brain signals, muscle activations, and articulatory movements. This multimodal acquisition paradigm presents substantial technical challenges, including MRI-induced electromagnetic interference and myogenic artifacts. To mitigate these, we introduce an artifact suppression pipeline tailored to this tri-modal setting. Once fully developed, this framework is poised to offer an unprecedented window into speech neuroscience and insights leading to brain-computer interface advances. |
| title | An Approach to Simultaneous Acquisition of Real-Time MRI Video, EEG, and Surface EMG for Articulatory, Brain, and Muscle Activity During Speech Production |
| topic | Audio and Speech Processing Artificial Intelligence Computation and Language |
| url | https://arxiv.org/abs/2603.04840 |