The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
Estimating brain age using high-resolution pattern recognition: Younger brains in long-term meditation practitioners
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Meditation experience is associated with increased cortical thickness
Lazar, S. W., Kerr, C. E., Wasserman, R. H., Gray, J. R., Greve, D. N., Treadway, M. T., McGarvey, M., Quinn, B. T., Dusek, J. A., Benson, H., et al. (2005) · NeuroReport · doi:10.1097/01.wnr.0000186598.66243.19 · Cited by 1,698
Fox, K. C. R., Nijeboer, S., Dixon, M. L., Floman, J. L., Ellamil, M., Rumak, S. P., Sedlmeier, P., & Christoff, K. (2014) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2014.03.016 · Cited by 804
Luders, E., Toga, A. W., Lepore, N., & Gaser, C. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2008.12.061 · Cited by 469 · cited 1×
“Note that this was a re-analysis of data overlapping, fully or in part, with those used in prior studies (Luders et al., 2009, 2011, 2012a,b, 2013a,b, 2014, 2015; Kurth et al., 2015a,b).”
Age effects on gray matter volume and attentional performance in Zen meditation
Pagnoni, G., & Cekic, M. (2007) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2007.06.008 · Cited by 370
Pfefferbaum, A., Rohlfing, T., Rosenbloom, M. J., Chu, W., Colrain, I. M., & Sullivan, E. V. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2012.10.008 · Cited by 256
Advanced BrainAGE in older adults with type 2 diabetes mellitus
Franke, K., Gaser, C., Manor, B., & Novak, V. (2013) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2013.00090 · Cited by 221
Enhanced brain connectivity in long-term meditation practitioners
Luders, E., Clark, K., Narr, K. L., & Toga, A. W. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.05.075 · Cited by 209
Exploring age‐related brain degeneration in meditation practitioners
Luders, E. (2014) · Annals of the New York Academy of Sciences · doi:10.1111/nyas.12217 · Cited by 79
Innes, K. E., & Selfe, T. K. (2014) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2014.00040 · Cited by 72
Changes of individual BrainAGE during the course of the menstrual cycle
Franke, K., Hagemann, G., Schleussner, E., & Gaser, C. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.04.036 · Cited by 72
Cited by
Cole, J. H., Poudel, R. P. K., Tsagkrasoulis, D., Caan, M. W. A., Steves, C., Spector, T. D., & Montana, G. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.07.059 · Cited by 872
“At the same time, brain-predicted age has been used to demonstrate protective influences on brain ageing, including meditation (Luders et al., 2016) and increased levels of education and physical exercise (Steffener et al.”
BackgroundCole, J. H., Ritchie, S. J., Bastin, M. E., Valdés Hernández, M. C., Muñoz Maniega, S., Royle, N., Corley, J., Pattie, A., Harris, S. E., Zhang, Q., et al. (2018) · Molecular Psychiatry · doi:10.1038/mp.2017.62 · Cited by 831
Guendelman, S., Medeiros, S., & Rampes, H. (2017) · Frontiers in Psychology · doi:10.3389/fpsyg.2017.00220 · Cited by 577
“5 years younger than matched control subjects (Luders et al., 2016).”
BackgroundInfluentialAlexander, R., Aragón, O. R., Bookwala, J., Cherbuin, N., Gatt, J. M., Kahrilas, I. J., Kästner, N., Lawrence, A., Lowe, L., Morrison, R. G., et al. (2021) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2020.12.002 · Cited by 303
Self-citationSex and gender differences in cognitive resilience to aging and Alzheimer's disease
Arenaza‐Urquijo, E. M., Boyle, R., Casaletto, K., Anstey, K. J., Vila‐Castelar, C., Colverson, A., Palpatzis, E., Eissman, J. M., Kheng Siang Ng, T., Raghavan, S., et al. (2024) · Alzheimer's & Dementia · doi:10.1002/alz.13844 · Cited by 223
Metadata
- Authors
- Luders, E., Cherbuin, N., & Gaser, C.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2016-07
- Volume
- 134
- Pages
- 508-513
- ISSN
- 1053-8119 (ISSN-L)
- OpenAlex
- W2335229748
- Cited by
- 186
- References
- 10
- FWCI
- 12.94
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Estimating brain age using high-resolution pattern recognition: Younger brains in long-term meditation practitioners. https://app.cochat.ai/papers/10.1016/j.neuroimage.2016.04.007
- The paper
- Luders, E., Cherbuin, N., & Gaser, C. (2016). Estimating brain age using high-resolution pattern recognition: Younger brains in long-term meditation practitioners. NeuroImage. https://doi.org/10.1016/j.neuroimage.2016.04.007
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
