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Time-Frequency Analysis of Motor-Evoked Potential in Patients with Stroke vs Healthy Subjects: a Transcranial Magnetic Stimulation Study

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Abstract

Conventional analysis of motor-evoked potential (MEP) is performed in time domain using amplitude and latency, which encapsulates information relevant to the cortical excitability of the brain. The study investigated the importance of time-frequency analysis by comparing MEPs in time-frequency domains (TFD) of healthy versus stroke survivors. Six healthy subjects and ten patients with stroke were enrolled. Single-pulse transcranial magnetic stimulation (TMS) at resting motor threshold (RMT) was given at extensor digitorum communis muscle cortical representation to obtain MEP. MEPs were obtained at resting motor threshold (100% RMT subjects and patients), supra-threshold range (100–170% RMT), and different voluntary contractions (100% RMT) to subjects. Fast Fourier transform and continuous wavelet transform (CWT) were used for analysis. Frequency spectrum showed 98% and 66% of signal power in 0–100 Hz for subjects and patients, respectively. Top 10, top 25, and top 50 percentile power of CWT were calculated for each MEP. Frequency spectrum of top 10 and top 25 percentile power of subjects were different (p < 0.05) and dispersed to 0–500 Hz for patients; both groups having a 40-Hz peak. Total power of MEP was found to be low (p < 0.05) in patients as compared to subjects and top 10, top 25, and top 50 percentile power showed decrease. Clinical scores—MAS and FM—were observed to be correlated to frequency and time-frequency features (p < 0.05). Frequency spectrum belonging top 10 percentile power of different level voluntary contractions showed statistical significance (p < 0.05). However, no significant differences were observed for MEPs at different supra-threshold intensities. Results suggest time-frequency analysis might provide objective ways to quantify TMS measures for stroke patients.

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Acknowledgments

The authors would like to express sincere gratitude to healthy subjects and patients who agreed to participate in the study. Also, they thank Mr. Vikas Kumar and Ms. Komal at TMS laboratory for their support during data acquisition and Mr. Dixit Sharma for the help in data analysis.

Funding

This work was supported by Science and Engineering Research Board (SERB), DST, Government of India (YSS/2015/000697). Neha Singh was supported with research fellowship funds from the Ministry of Human Resource and Development (MHRD), Government of India.

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Authors and Affiliations

  1. Centre for Biomedical Engineering, Indian Institute of Technology Delhi (IITD), Block III, Room No: 298, Hauz Khas, New Delhi, 110016, India

    Neha Singh, Megha Saini, Sneh Anand & Amit Mehndiratta

  2. Department of Psychiatry, All Indian Institute of Medical Sciences (AIIMS), New Delhi, India

    Nand Kumar

  3. Department of Physiology, All Indian Institute of Medical Sciences (AIIMS), New Delhi, India

    K. K. Deepak

  4. Department of Biomedical Engineering, All India Institute of Medical Sciences (AIIMS), New Delhi, India

    Sneh Anand & Amit Mehndiratta

  5. Department of Neurology, All India Institute of Medical Sciences (AIIMS), New Delhi, India

    M. V. Padma Srivastava

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Contributions

Conceptualization: NS, AM; data curation: NS,MS; formal analysis: NS, AM; funding acquisition: AM; methodology: NS, AM; resources: NK, SA, PS; supervision: AM; writing the original draft: NS, AM; writing the review and editing: NS, AM, KKD, NK, PS.

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Correspondence to Amit Mehndiratta.

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The authors declare that they have no competing interests.

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All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. The study was approved by the Institutional Review Board (IRB) at the All India Institute of Medical Science, New Delhi (IEC/NP-99/13.03.2015).

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Informed consent was obtained from all individual participants included in the study.

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Appendix

Appendix

Table 4 Amplitude and latency of MEP response curve (100% RMT) of six subjects and ten patients
Full size table
Table 5 Details of bandpower of MEP at different supra-threshold stimulus intensities (100 to 170%) RMT of subjects and patients at different frequency range
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Table 6 Details of power and frequency range of MEP at 100% RMT of subjects and patients at top 10, top 25, and top 50 percentile
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Table 7 Details of total power of CWT coefficients (p < 0.05) of MEP at 100% RMT of subjects and patients
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Table 8 Magnitude of 40 Hz peak frequency in MEP in time-frequency domain
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Table 9 Details of frequency range at top 10 percentile of MEP and peak frequency of MEP response at 100% RMT and 0%, 50%, and 100% MVC for healthy subjects
Full size table

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Singh, N., Saini, M., Kumar, N. et al. Time-Frequency Analysis of Motor-Evoked Potential in Patients with Stroke vs Healthy Subjects: a Transcranial Magnetic Stimulation Study. SN Compr. Clin. Med. 1, 764–780 (2019). https://doi.org/10.1007/s42399-019-00113-1

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