Top

Mindfulness

Gepubliceerd in:

29-02-2024 | ORIGINAL PAPER

Silence Practice Modulates the Resting State Functional Connectivity of Language Network with Default Mode and Dorsal Attention Networks in Long-Term Meditators

Auteurs: Vaibhav Tripathi, Kathryn J. Devaney, Sara W. Lazar, David C. Somers

Gepubliceerd in: Mindfulness | Uitgave 3/2024

Abstract

Objectives

The practice of silence is integral to some meditation traditions. Research is lacking on how silence practice affects brain connectivity. We hypothesized that silent, retreat-based meditation practice would reduce the connection between the language network from core cognitive networks such as the dorsal attention network (DAN) and default mode network (DMN).

Method

In a retrospective study, we analyzed resting state functional MRI (rsfMRI) data in 13 long-term Vipassana meditators (LTM) (~ 11,000 average hours of lifetime meditation experience) and healthy controls (n = 34) with no experience in meditation. We also compared our results with a large-scale dataset—Human Connectome Project (n = 169) (HCP). We compared the within and across functional connectivity among the three networks and correlated meditation experience and days spent in silence with the network connectivities.

Results

We found that the meditators have decoupled functional connectivity strengths (F_(2,204) = 10.27, p < 0.01) between the DMN and language network (M = − 0.05, SD = 0.19) as compared to HCP controls (M = 0.14, SD = 0.14). The DAN had a negatively correlated connectivity strength with the language network in meditators (r = − 0.20) as compared to both control groups (r = 0.02) and a strong inverse relation (r = − 0.54) was found between DAN-language connectivity and the number of days spent in silent retreat.

Conclusions

Our study finds a potential role of silence training in changing the connectivities of three cognitive networks, DMN, DAN, and language network, resulting in reduced thoughts during meditation and a deeper experience of meditation.

Preregistration

This study is not preregistered.

vorige artikel Ultra-Brief Breath Counting (Mindfulness) Training Abolishes Negative Affect–Induced Alcohol Motivation in Hazardous Community Drinkers

volgende artikel The Impact of Blended Mindfulness Intervention (BMI) on University Students’ Sustained Attention, Working Memory, Academic Achievement, and Electroencephalogram (EEG) Asymmetry

Barch, D. M., Burgess, G. C., Harms, M. P., Petersen, S. E., Schlaggar, B. L., Corbetta, M., Glasser, M. F., Curtiss, S., Dixit, S., Feldt, C., Nolan, D., Bryant, E., Hartley, T., Footer, O., Bjork, J. M., Poldrack, R., Smith, S., Johansen-Berg, H., Snyder, A. Z., & Essen, D. C. V. (2013). Function in the Human Connectome: Task-fMRI and individual differences in behavior. NeuroImage, 80, 169. https://doi.org/10.1016/j.neuroimage.2013.05.033CrossRefPubMed

Boccia, M., Piccardi, L., & Guariglia, P. (2015). The meditative mind: A comprehensive meta-analysis of MRI studies. BioMed Research International, 2015, 419808. https://doi.org/10.1155/2015/419808CrossRefPubMedPubMedCentral

Boot, W. R., Blakely, D. P., & Simons, D. J. (2011). Do action video games improve perception and cognition? Frontiers in Psychology, 2, 226. https://doi.org/10.3389/fpsyg.2011.00226

Brefczynski-Lewis, J. A., Lutz, A., Schaefer, H. S., Levinson, D. B., & Davidson, R. J. (2007). Neural correlates of attentional expertise in long-term meditation practitioners. Proceedings of the National Academy of Sciences, 104(27), 11483–11488. https://doi.org/10.1073/pnas.0606552104CrossRef

Brewer, J. A., Worhunsky, P. D., Gray, J. R., Tang, Y.-Y., Weber, J., & Kober, H. (2011). Meditation experience is associated with differences in default mode network activity and connectivity. Proceedings of the National Academy of Sciences, 108(50), 20254–20259. https://doi.org/10.1073/pnas.1112029108CrossRef

Buckner, R. L., & Carroll, D. C. (2007). Self-projection and the brain. Trends in Cognitive Sciences, 11(2), 49–57. https://doi.org/10.1016/j.tics.2006.11.004CrossRefPubMed

Buckner, R. L., & DiNicola, L. M. (2019). The brain’s default network: Updated anatomy, physiology and evolving insights. Nature Reviews Neuroscience, 20(10), 593–608. https://doi.org/10.1038/s41583-019-0212-7CrossRefPubMed

Caucheteux, C., & King, J.-R. (2022). Brains and algorithms partially converge in natural language processing. Communications Biology, 5, 134. https://doi.org/10.1038/s42003-022-03036-1

Cheng, P., Grover, S., Wen, W., Sankaranarayanan, S., Davies, S., Fragetta, J., Soto, D., & Reinhart, R. M. G. (2022). Dissociable rhythmic mechanisms enhance memory for conscious and nonconscious perceptual contents. Proceedings of the National Academy of Sciences, 119(44), e2211147119. https://doi.org/10.1073/pnas.2211147119CrossRef

Christoff, K., Irving, Z. C., Fox, K. C. R., Spreng, R. N., & Andrews-Hanna, J. R. (2016). Mind-wandering as spontaneous thought: A dynamic framework. Nature Reviews Neuroscience, 17(11), 718–731. https://doi.org/10.1038/nrn.2016.113CrossRefPubMed

Dale, A. M., Fischl, B., & Sereno, M. I. (1999). Cortical surface-based analysis: I. Segmentation and Surface Reconstruction. Neuroimage, 9(2), 179–194. https://doi.org/10.1006/nimg.1998.0395CrossRefPubMed

Dennison, P. (2019). The human default consciousness and its disruption: Insights from an EEG study of Buddhist Jhāna meditation. Frontiers in Human Neuroscience, 13, 178. https://doi.org/10.3389/fnhum.2019.00178

Devaney, K. J., Levin, E. J., Tripathi, V., Higgins, J. P., Lazar, S. W., & Somers, D. C. (2021). Attention and default mode network assessments of meditation experience during active cognition and rest. Brain Sciences, 11(5), 566. https://doi.org/10.3390/brainsci11050566

DiNicola, L. M., Braga, R. M., & Buckner, R. L. (2020). Parallel distributed networks dissociate episodic and social functions within the individual. Journal of Neurophysiology, 123(3), 1144–1179. https://doi.org/10.1152/jn.00529.2019CrossRefPubMedPubMedCentral

Dixon, M. L., Andrews-Hanna, J. R., Spreng, R. N., Irving, Z. C., Mills, C., Girn, M., & Christoff, K. (2017). Interactions between the default network and dorsal attention network vary across default subsystems, time, and cognitive states. NeuroImage, 147, 632–649. https://doi.org/10.1016/j.neuroimage.2016.12.073CrossRefPubMed

Du, J., DiNicola, L. M., Angeli, P. A., Saadon-Grosman, N., Sun, W., Kaiser, S., Ladopoulou, J., Xue, A., Yeo, B. T. T., Eldaief, M. C., & Buckner, R. L. (2023). Within-individual organization of the human cerebral cortex: Networks, global topography, and function. bioRxiv. https://doi.org/10.1101/2023.08.08.552437

Faskowitz, J., Esfahlani, F. Z., Jo, Y., Sporns, O., & Betzel, R. F. (2020). Edge-centric functional network representations of human cerebral cortex reveal overlapping system-level architecture. Nature Neuroscience, 23, 1644–1654. https://doi.org/10.1038/s41593-020-00719-y

Fedorenko, E., Behr, M. K., & Kanwisher, N. (2011). Functional specificity for high-level linguistic processing in the human brain. Proceedings of the National Academy of Sciences, 108(39), 16428–16433. https://doi.org/10.1073/pnas.1112937108CrossRef

Fialoke, S., Tripathi, V., Thakral, S., Dhawan, A., Majahan, V., & Garg, R. (2023). Brain connectivity changes in meditators and novices during yoga nidra: A novel fMRI study. bioRxiv. https://doi.org/10.1101/2023.09.15.557655

Finn, E. S., Shen, X., Scheinost, D., Rosenberg, M. D., Huang, J., Chun, M. M., Papademetris, X., & Constable, R. T. (2015). Functional connectome fingerprinting: Identifying individuals using patterns of brain connectivity. Nature Neuroscience, 18, 1664–1671. https://doi.org/10.1038/nn.4135

Fischl, B., & Dale, A. M. (2000). Measuring the thickness of the human cerebral cortex from magnetic resonance images. Proceedings of the National Academy of Sciences, 97(20), 11050–11055. https://doi.org/10.1073/pnas.200033797CrossRef

Fischl, B., Sereno, M. I., & Dale, A. M. (1999). Cortical surface-based analysis II Inflation, flattening, and a surface-based coordinate system. NeuroImage, 9(2), 195–207. https://doi.org/10.1006/nimg.1998.0396

Fischl, B., Salat, D. H., Busa, E., Albert, M., Dieterich, M., Haselgrove, C., van der Kouwe, A., Killiany, R., Kennedy, D., Klaveness, S., Montillo, A., Makris, N., Rosen, B., & Dale, A. M. (2002). Whole brain segmentation: Automated labeling of neuroanatomical structures in the human brain. Neuron, 33(3), 341–355. https://doi.org/10.1016/S0896-6273(02)00569-XCrossRefPubMed

Fischl, B., Salat, D. H., van der Kouwe, A. J. W., Makris, N., Ségonne, F., Quinn, B. T., & Dale, A. M. (2004). Sequence-independent segmentation of magnetic resonance images. NeuroImage, 23, S69–S84. https://doi.org/10.1016/j.neuroimage.2004.07.016CrossRefPubMed

Fox, M. D., Snyder, A. Z., Vincent, J. L., Corbetta, M., Van Essen, D. C., & Raichle, M. E. (2005). The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proceedings of the National Academy of Sciences, 102(27), 9673–9678. https://doi.org/10.1002/poc.610010207CrossRef

Froeliger, B., Garland, E. L., Kozink, R. V., Modlin, L. A., Chen, N.-K., McClernon, F. J., Greeson, J. M., & Sobin, P. (2012). Meditation-state functional connectivity (msFC): Strengthening of the dorsal attention network and beyond. Evidence-Based Complementary and Alternative Medicine, 2012, 680407. https://doi.org/10.1155/2012/680407CrossRefPubMedPubMedCentral

Glasser, M. F., Sotiropoulos, S. N., Wilson, J. A., Coalson, T. S., Fischl, B., Andersson, J. L., Xu, J., Jbabdi, S., Webster, M., Polimeni, J. R., Van Essen, D. C., & Jenkinson, M. (2013). The minimal preprocessing pipelines for the Human Connectome Project. NeuroImage, 80, 105–124. https://doi.org/10.1016/j.neuroimage.2013.04.127CrossRefPubMed

Gordon, E. M., Laumann, T. O., Marek, S., Raut, R. V., Gratton, C., Newbold, D. J., Greene, D. J., Coalson, R. S., Snyder, A. Z., Schlaggar, B. L., Petersen, S. E., Dosenbach, N. U. F., & Nelson, S. M. (2020). Default-mode network streams for coupling to language and control systems. Proceedings of the National Academy of Sciences of the United States of America, 117(29), 17308–17319. https://doi.org/10.1073/pnas.2005238117CrossRefPubMedPubMedCentral

Greicius, M., & Menon, V. (2004). Default-mode activity during a passive sensory task: Uncoupled from deactivation but impacting activation. Journal of Cognitive Neuroscience, 16(9), 1484–1492. https://doi.org/10.1162/0898929042568532

Hagerty, M. R., Isaacs, J., Brasington, L., Shupe, L., Fetz, E. E., & Cramer, S. C. (2013). Case study of ecstatic meditation: FMRI and EEG evidence of self-stimulating a reward system. Neural Plasticity, 2013, 653572. https://doi.org/10.1155/2013/653572

Heilbron, M., Armeni, K., Schoffelen, J.-M., Hagoort, P., & de Lange, F. P. (2022). A hierarchy of linguistic predictions during natural language comprehension. Proceedings of the National Academy of Sciences, 119(32), e2201968119. https://doi.org/10.1073/pnas.2201968119CrossRef

Jovicich, J., Czanner, S., Greve, D., Haley, E., van der Kouwe, A., Gollub, R., Kennedy, D., Schmitt, F., Brown, G., MacFall, J., Fischl, B., & Dale, A. (2006). Reliability in multi-site structural MRI studies: Effects of gradient non-linearity correction on phantom and human data. NeuroImage, 30(2), 436–443. https://doi.org/10.1016/j.neuroimage.2005.09.046CrossRefPubMed

Kirk, U., Pagnoni, G., Hétu, S., & Montague, R. (2019). Short-term mindfulness practice attenuates reward prediction errors signals in the brain. Scientific Reports, 9(1), 6964. https://doi.org/10.1038/s41598-019-43474-2CrossRefPubMedPubMedCentral

Knecht, S., Dräger, B., Deppe, M., Bobe, L., Lohmann, H., Flöel, A., Ringelstein, E.-B., & Henningsen, H. (2000). Handedness and hemispheric language dominance in healthy humans. Brain, 123(12), 2512–2518. https://doi.org/10.1093/brain/123.12.2512CrossRefPubMed

Kozasa, E. H., Sato, J. R., Lacerda, S. S., Barreiros, M. A. M., Radvany, J., Russell, T. A., Sanches, L. G., Mello, L. E. A. M., & Amaro, E. (2012). Meditation training increases brain efficiency in an attention task. NeuroImage, 59(1), 745–749. https://doi.org/10.1016/j.neuroimage.2011.06.088CrossRefPubMed

Laukkonen, R. E., & Slagter, H. A. (2021). From many to (n)one: Meditation and the plasticity of the predictive mind. Neuroscience & Biobehavioral Reviews, 128, 199–217. https://doi.org/10.1016/j.neubiorev.2021.06.021CrossRef

Lipkin, B., Tuckute, G., Affourtit, J., Small, H., Mineroff, Z., Kean, H., Jouravlev, O., Rakocevic, L., Pritchett, B., Siegelman, M., Hoeflin, C., Pongos, A., Blank, I. A., Struhl, M. K., Ivanova, A., Shannon, S., Sathe, A., Hoffmann, M., Nieto-Castañón, A., & Fedorenko, E. (2022). Probabilistic atlas for the language network based on precision fMRI data from >800 individuals. Scientific Data, 9, 529. https://doi.org/10.1038/s41597-022-01645-3

Lutz, A., Mattout, J., & Pagnoni, G. (2019). The epistemic and pragmatic value of non-action a predictive coding perspective on meditation. Current Opinion in Psychology, 28, 166–171. https://doi.org/10.1016/j.copsyc.2018.12.019CrossRefPubMed

Margulies, D. S., Ghosh, S. S., Goulas, A., Falkiewicz, M., Huntenburg, J. M., Langs, G., Bezgin, G., Eickhoff, S. B., Castellanos, F. X., Petrides, M., Jefferies, E., & Smallwood, J. (2016). Situating the default-mode network along a principal gradient of macroscale cortical organization. Proceedings of the National Academy of Sciences of the United States of America, 113(44), 12574–12579. https://doi.org/10.1073/pnas.1608282113CrossRefPubMedPubMedCentral

Marino, M., Arcara, G., Porcaro, C., & Mantini, D. (2019). Hemodynamic correlates of electrophysiological activity in the default mode network. Frontiers in Neuroscience, 13, 1–12. https://doi.org/10.3389/fnins.2019.01060CrossRef

McCarthy, H., Skokauskas, N., Mulligan, A., Donohoe, G., Mullins, D., Kelly, J., Johnson, K., Fagan, A., Gill, M., Meaney, J., & Frodl, T. (2013). Attention network hypoconnectivity with default and affective network hyperconnectivity in adults diagnosed with attention-deficit/hyperactivity disorder in childhood. JAMA Psychiatry, 70(12), 1329–1337. https://doi.org/10.1001/jamapsychiatry.2013.2174CrossRefPubMed

Pagnoni, G. (2019). The contemplative exercise through the lenses of predictive processing: A promising approach. In Progress in Brain Research (Vol. 244, pp. 299–322). Elsevier. https://doi.org/10.1016/bs.pbr.2018.10.022

Power, J. D., Barnes, K. A., Snyder, A. Z., Schlaggar, B. L., & Petersen, S. E. (2012). Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. NeuroImage, 59(3), 2142–2154. https://doi.org/10.1016/j.neuroimage.2011.10.018CrossRefPubMed

Rahrig, H., Vago, D. R., Passarelli, M. A., Auten, A., Lynn, N. A., & Brown, K. W. (2022). Meta-analytic evidence that mindfulness training alters resting state default mode network connectivity. Scientific Reports, 12(1), 12260. https://doi.org/10.1038/s41598-022-15195-6CrossRefPubMedPubMedCentral

Rosenberg, M. D., Finn, E. S., Scheinost, D., Papademetris, X., Shen, X., Constable, R. T., & Chun, M. M. (2015). A neuromarker of sustained attention from whole-brain functional connectivity. Nature Neuroscience, 19(1), 165–171. https://doi.org/10.1038/nn.4179CrossRefPubMedPubMedCentral

Ruck, L., & Schoenemann, P. T. (2021). Handedness measures for the Human Connectome Project: Implications for data analysis. Laterality, 26(5), 584–606. https://doi.org/10.1080/1357650X.2020.1866001CrossRefPubMed

Santaella, D. F., Balardin, J. B., Afonso, R. F., Giorjiani, G. M., Sato, J. R., Lacerda, S. S., Amaro, E., Lazar, S., & Kozasa, E. H. (2019). Greater anteroposterior default mode network functional connectivity in long-term elderly yoga practitioners. Frontiers in Aging Neuroscience, 10, 1–7. https://doi.org/10.3389/fnagi.2019.00158CrossRef

Schaefer, A., Kong, R., Gordon, E. M., Laumann, T. O., Zuo, X.-N., Holmes, A. J., Eickhoff, S. B., & Yeo, B. T. T. (2017). Local-global parcellation of the human cerebral cortex from intrinsic functional connectivity MRI. Cerebral Cortex, 28(9), 3095–3114. https://doi.org/10.1093/cercor/bhx179

Schrimpf, M., Blank, I. A., Tuckute, G., Kauf, C., Hosseini, E. A., Kanwisher, N., Tenenbaum, J. B., & Fedorenko, E. (2021). The neural architecture of language: Integrative modeling converges on predictive processing. Proceedings of the National Academy of Sciences, 118(45), e2105646118. https://doi.org/10.1073/pnas.2105646118CrossRef

Schuman-Olivier, Z., Trombka, M., Lovas, D. A., Brewer, J. A., Vago, D. R., Gawande, R., Dunne, J. P., Lazar, S. W., Loucks, E. B., & Fulwiler, C. (2020). Mindfulness and behavior change. Harvard Review of Psychiatry, 28(6), 371–394. https://doi.org/10.1097/HRP.0000000000000277CrossRefPubMedPubMedCentral

Ségonne, F., Dale, A. M., Busa, E., Glessner, M., Salat, D., Hahn, H. K., & Fischl, B. (2004). A hybrid approach to the skull stripping problem in MRI. NeuroImage, 22(3), 1060–1075. https://doi.org/10.1016/j.neuroimage.2004.03.032CrossRefPubMed

Seppälä, EM, Nitschke, JB, Tudorascu, DL, Hayes, A, Goldstein, MR, Nguyen, DT, Perlman, D, & Davidson, RJ (2014) Breathing-based meditation decreases posttraumatic stress disorder symptoms in U.S. military veterans A randomized controlled longitudinal study Journal of Traumatic Stress, 27(4), 397–405

Seabold, S., & Perktold, J. (2010). Statsmodels: Econometric and statistical modeling with python. In Proceedings of the 9th Python in Science Conference, SciPy 2010. https://doi.org/10.25080/majora-92bf1922-011

Sezer, I., Pizzagalli, D. A., & Sacchet, M. D. (2022). Resting-state fMRI functional connectivity and mindfulness in clinical and non-clinical contexts: A review and synthesis. Neuroscience & Biobehavioral Reviews, 135, 104583. https://doi.org/10.1016/j.neubiorev.2022.104583CrossRef

Shankar, R. (2022). Patanjali Yoga Sutras: The heart of yoga (Vol. 1). Sri Sri Publications Trust.

Srinivasan, T. M. (2013). From meditation to dhyana. International Journal of Yoga, 6(1), 1–3. https://doi.org/10.4103/0973-6131.105934MathSciNetCrossRefPubMedPubMedCentral

Tripathi, V., & Bharadwaj, P. (2021). Neuroscience of the yogic theory of consciousness. Neuroscience of Consciousness, 7(2), 1–15.

Tripathi, V., & Somers, D. C. (2023). Default mode and dorsal attention network functional connectivity associated with alpha and beta peak frequency in individuals. biorXiv. https://doi.org/10.1101/2023.02.19.529136

Van Essen, D. C., Ugurbil, K., Auerbach, E., Barch, D., Behrens, T. E. J., Bucholz, R., Chang, A., Chen, L., Corbetta, M., Curtiss, S. W., Della Penna, S., Feinberg, D., Glasser, M. F., Harel, N., Heath, A. C., Larson-Prior, L., Marcus, D., Michalareas, G., Moeller, S., … Yacoub, E. (2012). The Human Connectome Project: A data acquisition perspective. NeuroImage, 62(4), 2222–2231. https://doi.org/10.1016/j.neuroimage.2012.02.018

Van Essen, D. C., Smith, S. M., Barch, D. M., Behrens, T. E. J., Yacoub, E., & Ugurbil, K. (2013). The WU-Minn Human Connectome Project: An overview. NeuroImage. https://doi.org/10.1016/j.neuroimage.2013.05.041

Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., Bright, J., van der Walt, S. J., Brett, M., Wilson, J., Millman, K. J., Mayorov, N., Nelson, A. R. J., Jones, E., Kern, R., Larson, E., … Vázquez-Baeza, Y. (2020). SciPy 1.0: Fundamental algorithms for scientific computing in Python. Nature Methods, 17(3), 261–272. https://doi.org/10.1038/s41592-019-0686-2

Vivekananda, S. (2010). Patanjali Yoga Sutras. https://archive.org/details/PatanjaliYogaSutraBySwamiVivekananda/

Whitfield, T., Barnhofer, T., Acabchuk, R., Cohen, A., Lee, M., Schlosser, M., Arenaza-Urquijo, E. M., Böttcher, A., Britton, W., Coll-Padros, N., Collette, F., Chételat, G., Dautricourt, S., Demnitz-King, H., Dumais, T., Klimecki, O., Meiberth, D., Moulinet, I., Müller, T., & Marchant, N. L. (2022). The effect of mindfulness-based programs on cognitive function in adults: A systematic review and meta-analysis. Neuropsychology Review, 32(3), 677–702. https://doi.org/10.1007/s11065-021-09519-yCrossRefPubMed

Yeo, B. T. T., Krienen, F. M., Sepulcre, J., Sabuncu, M. R., Lashkari, D., Hollinshead, M., Roffman, J. L., Smoller, J. W., Zöllei, L., Polimeni, J. R., Fischl, B., Liu, H., & Buckner, R. L. (2011). The organization of the human cerebral cortex estimated by intrinsic functional connectivity. Journal of Neurophysiology, 106(3), 1125–1165. https://doi.org/10.1152/jn.00338.2011CrossRefPubMed

Young, K. S., Van Der Velden, A. M., Craske, M. G., Pallesen, K. J., Fjorback, L., Roepstorff, A., & Parsons, C. E. (2018). The impact of mindfulness-based interventions on brain activity: A systematic review of functional magnetic resonance imaging studies. Neuroscience & Biobehavioral Reviews, 84, 424–433. https://doi.org/10.1016/j.neubiorev.2017.08.003CrossRef

Zhang, Z., Luh, W. M., Duan, W., Zhou, G. D., Weinschenk, G., Anderson, A. K., & Dai, W. (2021). Longitudinal effects of meditation on brain resting-state functional connectivity. Scientific Reports, 11, 11361. https://doi.org/10.1038/s41598-021-90729-y

Zheng, A., Montez, D. F., Marek, S., Gilmore, A. W., Newbold, D. J., Laumann, T. O., Kay, B. P., Seider, N. A., Van, A. N., Hampton, J. M., Alexopoulos, D., Schlaggar, B. L., Sylvester, C. M., Greene, D. J., Shimony, J. S., Nelson, S. M., Wig, G. S., Gratton, C., McDermott, K. B., & Dosenbach, N. U. F. (2021). Parallel hippocampal-parietal circuits for self- and goal-oriented processing. Proceedings of the National Academy of Sciences, 118(34), e2101743118. https://doi.org/10.1073/pnas.2101743118CrossRef

Titel: Silence Practice Modulates the Resting State Functional Connectivity of Language Network with Default Mode and Dorsal Attention Networks in Long-Term Meditators
Auteurs: Vaibhav Tripathi
Kathryn J. Devaney
Sara W. Lazar
David C. Somers
Publicatiedatum: 29-02-2024
Uitgeverij: Springer US
Gepubliceerd in: Mindfulness / Uitgave 3/2024
Print ISSN: 1868-8527
Elektronisch ISSN: 1868-8535
DOI: https://doi.org/10.1007/s12671-024-02316-7

Bohn Stafleu van Loghum

Deel dit onderdeel of sectie (kopieer de link)

Abstract

Objectives

Method

Results

Conclusions

Preregistration

Log in om toegang te krijgen

Andere artikelen Uitgave 3/2024

Recalling Tough Times: Exploring the Effect of Acceptance on Autobiographical Memory in Daily Life

The Reliability and Validity of the Chinese Version of the Mindful Self-Care Scale for College Students

Validation and Confirmation of the Equanimity Scale-16 in India and its Relationship with Well-Being

Ultra-Brief Breath Counting (Mindfulness) Training Abolishes Negative Affect–Induced Alcohol Motivation in Hazardous Community Drinkers

Applying Participatory Research in the Development of Clinical Practice Recommendations for Incorporating Mindfulness into Mental Health Treatment with Youth at Risk for Psychosis

Those Who Are Mindful and Those Who Make Them Mindful: Yunus Emre and Mindfulness