<meta charset="utf8"></head><body>用 EEG 和 fMRI 解码宗教诵经期间的大脑活动

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	<li>Gao, J., Leung, H. K., Wu, B. W. Y., Skouras, S., Sik, H. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+neurophysiological+correlates+of+religious+chanting.">The neurophysiological correlates of religious chanting.</a> Sci Rep. 9 (1), 4262 (2019).</li><li>Sik, H. H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Modulation+of+the+neurophysiological+response+to+fearful+and+stressful+stimuli+through+repetitive+religious+chanting.">Modulation of the neurophysiological response to fearful and stressful stimuli through repetitive religious chanting.</a> J Vis Exp. (181), e62960 (2022).</li><li>Gao, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Repetitive+religious+chanting+invokes+positive+emotional+schema+to+counterbalance+fear:+A+multimodal+functional+and+structural+MRI+study.">Repetitive religious chanting invokes positive emotional schema to counterbalance fear: A multimodal functional and structural MRI study.</a> Front Behav Neurosci. 14, 548856 (2020).</li><li>Saarikivi, K., Chan, T. M. 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A., Koike, Y., Yoshimura, N. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Independent+components+of+EEG+activity+correlating+with+emotional+state.">Independent components of EEG activity correlating with emotional state.</a> Brain Sci. 10 (10), 669 (2020).</li><li>Bigdely-Shamlo, N., Mullen, T., Kreutz-Delgado, K., Makeig, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Measure+projection+analysis:+a+probabilistic+approach+to+EEG+source+comparison+and+multi-subject+inference.">Measure projection analysis: a probabilistic approach to EEG source comparison and multi-subject inference.</a> Neuroimage. 72, 287-303 (2013).</li><li>Harmony, T. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+functional+significance+of+delta+oscillations+in+cognitive+processing.">The functional significance of delta oscillations in cognitive processing.</a> Front Integr Neurosci. 7, 83 (2013).</li><li>Tompson, S., Chua, H. 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H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+Randomized+Controlled+Trial+of+Awareness+Training+Program+(ATP),+a+Group-Based+Mahayana+Buddhist+Intervention.">A Randomized Controlled Trial of Awareness Training Program (ATP), a Group-Based Mahayana Buddhist Intervention.</a> Mindfulness. 10, 1280-1293 (2019).</li><li>Gomes, B. A., Plaska, C. R., Ortega, J., Ellmore, T. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+simultaneous+EEG-fMRI+study+of+thalamic+load-dependent+working+memory+delay+period+activity.">A simultaneous EEG-fMRI study of thalamic load-dependent working memory delay period activity.</a> Front Behav Neurosci. 17, 1132061 (2023).</li><li>Gao, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Repetitive+religious+chanting+modulates+the+late-stage+brain+response+to+fear-and+stress-provoking+pictures.">Repetitive religious chanting modulates the late-stage brain response to fear-and stress-provoking pictures.</a> Front Psychol. 7, 2055 (2017).</li><li>Ciccarelli, G., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Simultaneous+real-time+EEG-fMRI+neurofeedback:+A+systematic+review.">Simultaneous real-time EEG-fMRI neurofeedback: A systematic review.</a> Front Hum Neurosci. 17, 1123014 (2023).</li><li>Abreu, R., Nunes, S., Leal, A., Figueiredo, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Physiological+noise+correction+using+ECG-derived+respiratory+signals+for+enhanced+mapping+of+spontaneous+neuronal+activity+with+simultaneous+EEG-fMRI.">Physiological noise correction using ECG-derived respiratory signals for enhanced mapping of spontaneous neuronal activity with simultaneous EEG-fMRI.</a> Neuroimage. 154, 115-127 (2017).</li></ol>

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>3.0 T Philips MRI scanner</td>
			<td>Philips</td>
			<td>3.0T</td>
			<td>MRI data acquisition device</td>
		</tr>
		<tr>
			<td>EEGLAB</td>
			<td>Swartz Center for Computational Neuroscience</td>
			<td>13.6.5b</td>
			<td>EEG analysis software</td>
		</tr>
		<tr>
			<td>Electroencephalogram (EEG) system</td>
			<td>Electrical Geodesics, Inc. (EGI)</td>
			<td>GES 200</td>
			<td>EEG acquisition device</td>
		</tr>
		<tr>
			<td>HRVAS</td>
			<td>Ramshur, J.</td>
			<td>Version 1</td>
			<td>Plug-in for EEGLAB to process ECG data</td>
		</tr>
		<tr>
			<td>HydroCel GSN 128 channels</td>
			<td>Electrical Geodesics, Inc. (EGI)</td>
			<td>GSN 130</td>
			<td>EEG cap</td>
		</tr>
		<tr>
			<td>iMac 27&#34;</td>
			<td>Apple</td>
			<td>Version 10.8</td>
			<td>Running the Netstation software</td>
		</tr>
		<tr>
			<td>LabChart</td>
			<td>ADInstruments</td>
			<td>Version 8</td>
			<td>Physiological data acquisition software</td>
		</tr>
		<tr>
			<td>LIPSIA</td>
			<td>Max-Planck-Institute for Human Cognitive and Brain Sciences</td>
			<td>Version 2.2.7</td>
			<td>fMRI data analysis software</td>
		</tr>
		<tr>
			<td>Matlab</td>
			<td>MathWorks</td>
			<td>R2011a</td>
			<td>EEGLAB is based on Matlab, statistical analysis tool for EEG data</td>
		</tr>
		<tr>
			<td>Netstation</td>
			<td>Electrical Geodesics, Inc. (EGI)</td>
			<td>Version 3</td>
			<td>EEG acquisition software</td>
		</tr>
		<tr>
			<td>PowerLab 8/35</td>
			<td>ADInstruments</td>
			<td>PL3508</td>
			<td>Physiological data acquisition hardware</td>
		</tr>
		<tr>
			<td>SPSS</td>
			<td>IBM</td>
			<td>Version 27</td>
			<td>Statistical analysis tool for behavior and EEG ROI data</td>
		</tr>
		<tr>
			<td>Windows PC</td>
			<td>Dell</td>
			<td>Version 8</td>
			<td>Running the LabChart software</td>
		</tr>
	</tbody>
</table>

religious chanting and self-related brain regions: a multi-modal neuroimaging study

Religious chanting, a very popular practice in Eastern cultures, is often compared to prayer in Western societies1. Despite its prevalence, scientific research on the neural correlates of religious chanting remains rather limited. Sophisticated multimodal electrophysiological and neuroimaging techniques were utilized in this study to fill this knowledge gap and to explore the neural associations of chanting Amit&#257;bha Buddha, one of the most widespread and one of the oldest actively preserved religious traditions2,3. Repetitive religious chanting can serve as an effective technique in Buddhist counseling to help soothe one&#39;s mind from turbulent thoughts and emotions.
Given the high spatial resolution of functional magnetic resonance imaging (fMRI), it can be applied to overcome the limitations of traditional EEG studies4. Combining fMRI&#160;and electroencephalogram (EEG) source clustering via independent component analysis (ICA), the study identifies and groups independent components of brain activity across participants. This method introduces a novel strategy for identifying signals from mixed EEG sources or disparate sources across participants, which has been challenging due to differences in brain anatomy and electrode placement.
The form of repetitive religious chanting that was studied with this protocol involves repetitive recitation of the name of Amit&#257;bha Buddha. It is also a meditative practice that has been reported to elicit blissful sensations and transcendental experiences. Amongst different Buddhist practices, the practice of chanting&#160;Amit&#257;bha Buddha is&#160;simple and easily accessible. This practice promises rebirth in the Pure Land for all those who sincerely call upon this name, which has similarities to certain traditions in Western religion1,3.
Through multimodal neuroimaging, this study aims to provide a comprehensive understanding of the neural correlates of repetitive religious chanting. The protocol can contribute to the booming field of research on the neurophysiological effects of different religious and meditative practices.
The study hypothesized that repetitive religious chanting would lead to significant signal changes in brain regions responsible for self-related processes. Furthermore, given the positive emotions attributed to Amit&#257;bha Buddha, we hypothesized that emotional shifts would transpire during religious chanting. These effective changes are likely to coincide with modifications in peripheral physiological indicators, such as variations in multi-band heart rate variability (HRV) indices and respiration rate5.

<meta charset="utf8"></head><body>作者聚焦：探索与宗教吟诵相关的动态神经变化

宗教诵经和自相关脑区：一项多模态神经影像学研究

This protocol presents a multi-modal neuroimaging approach to explore the potential brain activity associated with repetitive religious chanting, a ...

religious-chanting-self-related-brain-regions-multi-modal

Research

JoVE Journal

Neuroscience

Religious Chanting and Self-Related Brain Regions: A Multi-Modal Neuroimaging Study

413 次观看.  The University of Hong Kong. 我们的研究使用多模态神经成像技术探索宗教吟诵的神经生理学相关性。我们的目标是揭示重复宗教吟诵所涉及的大脑区域和神经过程，以及它们与非宗教吟诵和休息状态有何不同。最近的研究开始使用先进的神经影像学方法调查各种冥想和宗教活动对大脑的影响。这些发展揭示了这种做法潜在治疗益处背后的神经机制。我们的研究结合了高密...

视频: 作者聚焦：探索与宗教吟诵相关的动态神经变化

This protocol presents a multi-modal neuroimaging approach to explore the potential brain activity associated with repetitive religious chanting, a widespread form of mind training in both Eastern and Western cultures. High-density electroencephalogram (EEG), with its superior temporal resolution, allows for capturing the dynamic changes in brain activity during religious chanting. Through source localization methods, these can be attributed to various alternative potential brain region sources. Twenty practitioners of religious chanting were measured with EEG. However, the spatial resolution of EEG is less precise, in comparison to functional magnetic resonance imaging (fMRI). Thus, one highly experienced practitioner underwent an fMRI scanning session to guide the source localization more precisely. The fMRI data helped guide the selection of EEG source localization, making the calculation of K-means of the EEG source localization in the group of 20 intermediate practitioners more precise and reliable. This method enhanced EEG&#39;s ability to identify the brain regions specifically engaged during religious chanting, particularly the cardinal role of the posterior cingulate cortex (PCC). The PCC is a brain area related to focus and self-referential processing. These multimodal neuroimaging and neurophysiological results reveal that repetitive religious chanting can induce lower centrality and higher delta-wave power compared to non-religious chanting and resting state conditions. The combination of fMRI and EEG source analysis provides a more detailed understanding of the brain&#39;s response to repetitive religious chanting. The protocol contributes significantly to the research on the neural mechanisms involved in religious and meditative practices, which is becoming more prominent nowadays. The results of this study could have significant implications for developing future neurofeedback techniques and psychological interventions.

Here, we present a protocol to investigate the neurophysiological correlates of various meditation forms, including religious chanting. This method uniquely integrates fMRI eigenvector results for region selection in electroencephalogram (EEG) source analysis using k-means clustering. The results provide an in-depth understanding of the neural processes involved in repetitive religious chanting.