BACKGROUND: Contact heat evoked potentials (CHEP) is a thermal stimulus modality used in pain research. We examine a commercial CHEP stimulator (CHEPS) that is designed to work in an fMRI environment, but poorly understood in the MEG environment. The CHEPS attains target temperatures rapidly using sophisticated control signals that unfortunately induce artifacts in the MEG. In this paper, we summarize our experiences using the CHEPS in MEG to study pain using an experimental paradigm, and propose a novel method for managing its artifact. NEW METHOD: We introduce a novel damped sinusoid modeling (DSM) technique to remove the CHEPS artifact based on estimates of the underlying sinusoids and damping factors. We show comparisons to signal space projection (SSP) and temporal signal space separation (tSSS) methods. RESULTS: The CHEPS artifact is highly dynamic, yet deterministic, switching rapidly from one frequency to another, with different spatial components. The galvanic connection between the subject and the CHEPS probe alters its performance, making pre-characterization difficult. COMPARISON WITH EXISTING METHODS: SSP methods failed to remove the artifact completely. TSSS performed better than SSP; however, tSSS requires the use of a multipolar head model that decreases the dimensionality and possibly the information content of the data. In contrast, DSM offers a strictly temporal modeling approach in which the artifact is estimated as a sum of damped sinusoids which is subtracted from the data. CONCLUSION: Though the CHEPS increases the noise floor and introduces artifacts to the data, we believe the device can be successfully used in MEG if appropriate artifact removal techniques are followed.
BACKGROUND: Contact heat evoked potentials (CHEP) is a thermal stimulus modality used in pain research. We examine a commercial CHEP stimulator (CHEPS) that is designed to work in an fMRI environment, but poorly understood in the MEG environment. The CHEPS attains target temperatures rapidly using sophisticated control signals that unfortunately induce artifacts in the MEG. In this paper, we summarize our experiences using the CHEPS in MEG to study pain using an experimental paradigm, and propose a novel method for managing its artifact. NEW METHOD: We introduce a novel damped sinusoid modeling (DSM) technique to remove the CHEPS artifact based on estimates of the underlying sinusoids and damping factors. We show comparisons to signal space projection (SSP) and temporal signal space separation (tSSS) methods. RESULTS: The CHEPS artifact is highly dynamic, yet deterministic, switching rapidly from one frequency to another, with different spatial components. The galvanic connection between the subject and the CHEPS probe alters its performance, making pre-characterization difficult. COMPARISON WITH EXISTING METHODS: SSP methods failed to remove the artifact completely. TSSS performed better than SSP; however, tSSS requires the use of a multipolar head model that decreases the dimensionality and possibly the information content of the data. In contrast, DSM offers a strictly temporal modeling approach in which the artifact is estimated as a sum of damped sinusoids which is subtracted from the data. CONCLUSION: Though the CHEPS increases the noise floor and introduces artifacts to the data, we believe the device can be successfully used in MEG if appropriate artifact removal techniques are followed.
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