The DOI matches its Crossref record; 30 of the 32 references it cites were found in a registry or an index.
A new meta-analytic method for neuroimaging studies that combines reported peak coordinates and statistical parametric maps
Open accessAbstract
Meta-analyses are essential to summarize the results of the growing number of neuroimaging studies in psychiatry, neurology and allied disciplines. Image-based meta-analyses use full image information (i.e. the statistical parametric maps) and well-established statistics, but images are rarely available making them highly unfeasible. Peak-probability meta-analyses such as activation likelihood estimation (ALE) or multilevel kernel density analysis (MKDA) are more feasible as they only need reported peak coordinates. Signed-differences methods, such as signed differential mapping (SDM) build upon the positive features of existing peak-probability methods and enable meta-analyses of studies comparing patients with controls. In this paper we present a new version of SDM, named Effect Size SDM (ES-SDM), which enables the combination of statistical parametric maps and peak coordinates and uses well-established statistics. We validated the new method by comparing the results of an ES-SDM meta-analysis of studies on the brain response to fearful faces with the results of a pooled analysis of the original individual data. The results showed that ES-SDM is a valid and reliable coordinate-based method, whose performance might be additionally increased by including statistical parametric maps. We anticipate that ES-SDM will be a helpful tool for researchers in the fields of psychiatry, neurology and allied disciplines.
Overview
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“This method, which has been validated and used in several structural and functional fMRI studies creates a brain map of the effect size of the difference between the two conditions (CS+ and CS -)for each study (either from SPMs or from peak information) and afterwards conducts a voxel-wise random-effects meta-analysis (weighting the studies for sample size and variance) 13,[20][21][22]”
From Neural signatures of human fear conditioning: an updated and extended meta-analysis of fMRI studies (2016) · cites this paper as [13]
In the citing paper
“Including original SPMs, as opposed to including only peak regional effects (typically reported in tables of statistics), substantially increases the analyses statistical power 13”
From Neural signatures of human fear conditioning: an updated and extended meta-analysis of fMRI studies (2016) · cites this paper as [13]
In the citing paper
“Despite providing an optimal balance between sensitivity and false positive rate, 13 the default AES-SDM statistical thresholds were based on uncorrected P-values, which may be seen as a limitation.”
From Neural signatures of human fear conditioning: an updated and extended meta-analysis of fMRI studies (2016) · cites this paper as [13]
In the citing paper
“Our study nevertheless has some limitations inherent to most meta-analyses; the different studies included employed various statistical thresholds, and although our methods provide excellent control for false positives it is more difficult to avoid false negatives.13”
From Neural signatures of human fear conditioning: an updated and extended meta-analysis of fMRI studies (2016) · cites this paper as [13]
Citations
Cites
Meta-analysis in clinical trials
DerSimonian, R., & Laird, N. (1986) · Controlled Clinical Trials · doi:10.1016/0197-2456(86)90046-2 · Cited by 39,552
Cochrane Handbook for Systematic Reviews of Interventions: Cochrane Book Series
(2008) · doi:10.1002/9780470712184 · Cited by 25,048
Measures of the Amount of Ecologic Association Between Species
Dice, L. R. (1945) · Ecology · doi:10.2307/1932409 · Cited by 12,187
Wasserman, S. S., Hedges, L. V., & Olkin, I. (1988) · Journal of Educational Statistics · doi:10.2307/1164953 · Cited by 10,377
Distribution Theory for Glass's Estimator of Effect Size and Related Estimators
Hedges, L. V. (1981) · Journal of Educational Statistics · doi:10.2307/1164588 · Cited by 5,695
Statistical Methods for Meta-Analysis.
Freeman, P. R., Hedges, L. V., & Olkin, I. (1986) · Biometrics · doi:10.2307/2531069 · Cited by 4,839
Eickhoff, S. B., Laird, A. R., Grefkes, C., Wang, L. E., Zilles, K., & Fox, P. T. (2009) · Human Brain Mapping · doi:10.1002/hbm.20718 · Cited by 1,924
Bias and Efficiency of Meta-Analytic Variance Estimators in the Random-Effects Model
Viechtbauer, W. (2005) · Journal of Educational and Behavioral Statistics · doi:10.3102/10769986030003261 · Cited by 1,699
Meta-analysis of the functional neuroanatomy of single-word reading: method and validation
Turkeltaub, P. E., Eden, G. F., Jones, K. M., & Zeffiro, T. A. (2002) · NeuroImage · doi:10.1006/nimg.2002.1131 · Cited by 1,604
The Handbook of Research Synthesis
Hanka, R. (1994) · BMJ · doi:10.1136/bmj.309.6952.488a · Cited by 1,065
Flagged first, then by citations
2 of the 32 references couldn’t be matched to a known paper.
Research works printed but not linked: 1
- 10.3102/10769986006002107 · DOI · Paper page
Cited by
Sorted by citations
Items 101–200 of 765
Lopez-Gamundi, P., Yao, Y., Chong, T. T. ‐., Heekeren, H. R., Herrero, E. M., & Marco‐Pallarés, J. (2021) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2021.10.024 · Cited by 126
Validity of modulation and optimal settings for advanced voxel-based morphometry
Raduà, J., Canales-Rodríguez, E. J., Pomarol-Clotet, E., & Salvador, R. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2013.07.084 · Cited by 122
Dong, D., Wang, Y., Jia, X., Li, Y., Chang, X., Vandekerckhove, M. M. P., Luo, C., & Yao, D. (2017) · Schizophrenia Research · doi:10.1016/j.schres.2017.11.013 · Cited by 111
Suarez‐Jimenez, B., Albajes‐Eizagirre, A., Lazarov, A., Zhu, X., Harrison, B. J., Raduà, J., Neria, Y., & Fullana, M. A. (2019) · Psychological Medicine · doi:10.1017/s0033291719001387 · Cited by 125
van Balkom, T. D., van den Heuvel, O. A., Berendse, H. W., van der Werf, Y. D., & Vriend, C. (2020) · Neuropsychology Review · doi:10.1007/s11065-020-09440-w · Cited by 122
Liu, J., Cao, L., Li, H., Gao, Y., Bu, X., Liang, K., Bao, W., Zhang, S., Qiu, H., Li, X., et al. (2022) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2022.104574 · Cited by 109
Zeng, J., Yu, S., Cao, H., Su, Y., Dong, Z., & Yang, X. (2021) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2021.06.031 · Cited by 110
Serra-Blasco, M., Raduà, J., Soriano‐Mas, C., Gómez‐Benlloch, A., Casteràs, D. P., Carulla‐Roig, M., Albajes‐Eizagirre, A., Arnone, D., Klauser, P., Canales-Rodríguez, E. J., et al. (2021) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2021.07.002 · Cited by 105
Self-citationZheng, H., Hu, Y.-B., Wang, Z.-L., Wang, M., Du, X.-X., & Dong, G. (2019) · Progress in Neuro-psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2019.109656 · Cited by 100
Pan, N., Wang, S., Zhao, Y., Lai, H., Qin, K., Li, J., Biswal, B. B., Sweeney, J. A., & Gong, Q. (2021) · Human Brain Mapping · doi:10.1002/hbm.25361 · Cited by 107
Chan, M. M. Y., Yau, S. S. Y., & Han, Y. M. Y. (2021) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2021.02.035 · Cited by 108
Cooper, D., Barker, V., Raduà, J., Fusar‐Poli, P., & Lawrie, S. M. (2013) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2013.07.008 · Cited by 107
Schulze, L., Schulze, A., Renneberg, B., Schmahl, C., & Niedtfeld, I. (2019) · Biological Psychiatry: Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2018.11.004 · Cited by 102
Picó‐Pérez, M., Alemany-Navarro, M., Dunsmoor, J. E., Raduà, J., Albajes‐Eizagirre, A., Vervliet, B., Cardoner, N., Benet, O., Harrison, B. J., Soriano‐Mas, C., et al. (2019) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2019.06.029 · Cited by 105
Self-citationGray matter abnormalities in opioid-dependent patients: A neuroimaging meta-analysis
Wollman, S. C., Alhassoon, O. M., Hall, M. G., Stern, M. J., Connors, E. J., Kimmel, C. L., Allen, K. E., Stephan, R. A., & Raduà, J. (2016) · The American Journal of Drug and Alcohol Abuse · doi:10.1080/00952990.2016.1245312 · Cited by 101
Liu, J., Li, Y., Zhang, W., Xiao, Y., Liu, L., Gao, X., Shah, C., Li, S., Bo, T., Gong, Q., et al. (2017) · European Child & Adolescent Psychiatry · doi:10.1007/s00787-017-0964-4 · Cited by 108
Han, J. E., Boachie, N., García‐García, I., Michaud, A., & Dagher, A. (2018) · Physiology & Behavior · doi:10.1016/j.physbeh.2018.02.037 · Cited by 108
Keramatian, K., Chakrabarty, T., Saraf, G., Pinto, J. V., & Yatham, L. N. (2020) · Bipolar Disorders · doi:10.1111/bdi.12995 · Cited by 100
Gray Matter Structural Alterations in Social Anxiety Disorder: A Voxel-Based Meta-Analysis
Wang, X., Cheng, B., Luo, Q., Qiu, L., & Wang, S. (2018) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2018.00449 · Cited by 103
Parlatini, V., Itahashi, T., Lee, Y., Liu, S., Nguyen, T. T., Aoki, Y. Y., Forkel, S. J., Catani, M., Rubia, K., Zhou, J. H., et al. (2023) · Molecular Psychiatry · doi:10.1038/s41380-023-02173-1 · Cited by 107
Guo, Z., Tang, X., Xiao, S., Yan, H., Sun, S., Yang, Z., Huang, L., Chen, Z., & Wang, Y. (2024) · Molecular Autism · doi:10.1186/s13229-024-00593-6 · Cited by 111
Meng, Y., Qiu, C., Zhu, H., Lama, S., Lui, S., Gong, Q., & Zhang, W. (2014) · Behavioural Brain Research · doi:10.1016/j.bbr.2014.05.021 · Cited by 97
Raduà, J., Ojeda, N., Gómez, J., Guillén‐Grima, F., & Ortuño, F. (2014) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2014.03.016 · Cited by 96
Li, J., Pan, P., Huang, R., & Shang, H. (2011) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2011.12.001 · Cited by 96
Chan, M. M. Y., & Han, Y. M. Y. (2020) · Molecular Autism · doi:10.1186/s13229-020-00374-x · Cited by 96
Towards a neural model of infant cry perception
Witteman, J., Van IJzendoorn, M. H., Rilling, J. K., Bos, P. A., Schiller, N. O., & Bakermans-Kranenburg, M. J. (2019) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2019.01.026 · Cited by 94
Structural and functional brain alterations in obstructive sleep apnea: a multimodal meta-analysis
Huang, X. D., Tang, S., Lyu, X., Yang, C., & Chen, X. (2018) · Sleep Medicine · doi:10.1016/j.sleep.2018.09.025 · Cited by 97
Jauhar, S., Fortea, L., Solanes, A., Albajes‐Eizagirre, A., McKenna, P. J., & Raduà, J. (2021) · PLoS ONE · doi:10.1371/journal.pone.0255292 · Cited by 103
Brain changes after spinal cord injury, a quantitative meta-analysis and review
Dahlberg, L. S., Becerra, L. R., Borsook, D., & Linnman, C. (2018) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2018.04.018 · Cited by 95
Schurz, M., Maliske, L., & Kanske, P. (2020) · Cortex · doi:10.1016/j.cortex.2020.05.006 · Cited by 110
Bao, W., Gao, Y., Cao, L., Li, H., Liu, J., Liang, K., Hu, X., Zhang, L., Hu, X., Gong, Q., et al. (2021) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2021.10.017 · Cited by 92
Pan, P., Zhan, H., Xia, M., Zhang, Y., Guan, D., & Xu, Y. (2016) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2016.11.018 · Cited by 93
Neural correlates during working memory processing in major depressive disorder
Wang, X.-L., Du, M.-Y., Chen, T.-L., Chen, Z.-Q., Huang, X.-Q., Luo, Y., Zhao, Y.-J., Kumar, P., & Gong, Q.-Y. (2015) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2014.08.011 · Cited by 89
Functional and Structural Brain Correlates of Socioeconomic Status
Yaple, Z. A., & Yu, R. (2019) · Cerebral Cortex · doi:10.1093/cercor/bhz080 · Cited by 103
Gray Matter Features of Reading Disability: A Combined Meta-Analytic and Direct Analysis Approach
Eckert, M. A., Berninger, V. W., Vaden, K. I., Gebregziabher, M., & Tsu, L. (2016) · eNeuro · doi:10.1523/eneuro.0103-15.2015 · Cited by 92
Radua, J., Romeo, M., Mataix-Cols, D., & Fusar-Poli, P. (2013) · Current Medicinal Chemistry · doi:10.2174/0929867311320030017 · Cited by 91
Self-citationLi, X., & Wang, J. (2021) · Brain Imaging and Behavior · doi:10.1007/s11682-020-00299-2 · Cited by 89
Residual effects of cannabis use in adolescent and adult brains — A meta-analysis of fMRI studies
Blest‐Hopley, G., Giampietro, V., & Bhattacharyya, S. (2018) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2018.03.008 · Cited by 93
Hall, M. G., Alhassoon, O. M., Stern, M. J., Wollman, S. C., Kimmel, C. L., Perez-Figueroa, A. M., & Raduà, J. (2015) · The American Journal of Drug and Alcohol Abuse · doi:10.3109/00952990.2015.1044607 · Cited by 91
Pan, P. L., Song, W., Yang, J., Huang, R., Chen, K., Gong, Q. Y., Zhong, J. G., Shi, H. C., & Shang, H. F. (2012) · Dementia and Geriatric Cognitive Disorders · doi:10.1159/000338176 · Cited by 90
Neural bases of atypical emotional face processing in autism: A meta-analysis of fMRI studies
Aoki, Y. Y., Cortese, S., & Tansella, M. (2014) · The World Journal of Biological Psychiatry · doi:10.3109/15622975.2014.957719 · Cited by 103
Possible roles for fronto-striatal circuits in reading disorder
Hancock, R., Richlan, F., & Hoeft, F. (2016) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2016.10.025 · Cited by 88
Resting-State Brain Abnormalities in Chronic Subjective Tinnitus: A Meta-Analysis
Chen, Y., Wang, F., Wang, J., Bo, F., Xia, W., Gu, J., & Yin, X. (2017) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2017.00022 · Cited by 90
Su, T., Gong, J., Tang, G., Qiu, S., Chen, P., Chen, G., Wang, J., Huang, L., & Wang, Y. (2021) · Human Brain Mapping · doi:10.1002/hbm.25602 · Cited by 87
Peng, Z., Lui, S. S. Y., Cheung, E. F. C., Jin, Z. H., Miao, G., Jin, J., & Chan, R. C. K. (2012) · Asian Journal of Psychiatry · doi:10.1016/j.ajp.2012.07.004 · Cited by 87
Rocchetti, M., Radua, J., Paloyelis, Y., Xenaki, L., Frascarelli, M., Caverzasi, E., Politi, P., & Fusar‐Poli, P. (2014) · Psychiatry and Clinical Neurosciences · doi:10.1111/pcn.12185 · Cited by 83
A meta-analysis of fMRI studies of language comprehension in children
Enge, A., Friederici, A. D., & Skeide, M. A. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116858 · Cited by 91
Zhao, Y., Yang, L., Gong, G., Cao, Q., & Liu, J. (2021) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2021.110477 · Cited by 87
Zeng, J., Yan, J., Cao, H., Su, Y., Song, Y. Y., Luo, Y., & Yang, X. (2022) · Translational Psychiatry · doi:10.1038/s41398-022-02201-8 · Cited by 89
Meta-analysis of non-statistically significant unreported effects
Albajes‐Eizagirre, A., Solanes, A., & Raduà, J. (2018) · Statistical Methods in Medical Research · doi:10.1177/0962280218811349 · Cited by 83
Aberrant structural connectivity in childhood maltreatment: A meta-analysis
Lim, L. L., Howells, H., Raduà, J., & Rubia, K. (2020) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2020.07.004 · Cited by 85
Chen, G., Guo, Y., Zhu, H., Kuang, W., Bi, F., Ai, H., Gu, Z., Huang, X., Lui, S., & Gong, Q. (2017) · Progress in Neuro-Psychopharmacology and Biological Psychiatry · doi:10.1016/j.pnpbp.2017.03.011 · Cited by 81
Hájek, T., Alda, M., Hajek, E., & Ivanoff, J. (2013) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2013.08.015 · Cited by 78
Brain activation during human defensive behaviour: A systematic review and preliminary meta-analysis
Patrick, F., Kempton, M. J., Marwood, L., Williams, S., Young, A. H., & Perkins, A. M. (2019) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2018.12.028 · Cited by 82
Wang, Y., Gao, Y., Tang, S., Lu, L., Zhang, L., Bu, X., Li, H., Hu, X., Hu, X., Jiang, P., et al. (2020) · EBioMedicine · doi:10.1016/j.ebiom.2020.102742 · Cited by 83
Sha, Z., Xia, M., Lin, Q., Cao, M., Tang, Y., Xu, K., Song, H., Wang, Z., Wang, F., Fox, P. T., et al. (2017) · Cerebral Cortex · doi:10.1093/cercor/bhx273 · Cited by 88
Neural substrates of smoking and reward cue reactivity in smokers: a meta-analysis of fMRI studies
Lin, X., Deng, J., Shi, L., Wang, Q., Li, P., Li, H., Liu, J., Que, J., Chang, S., Bao, Y., et al. (2020) · Translational Psychiatry · doi:10.1038/s41398-020-0775-0 · Cited by 78
Wang, J., Zhang, J., Zang, Y., & Wu, T. (2018) · GigaScience · doi:10.1093/gigascience/giy071 · Cited by 80
Ding, Y., Chen, X., Chen, Z., Li, L., Li, X., Castellanos, F. X., Bai, T., Bo, Q., Cao, J., Chang, Z., et al. (2022) · Translational Psychiatry · doi:10.1038/s41398-022-01995-x · Cited by 87
A Meta-analysis of Voxel-based Brain Morphometry Studies in Obstructive Sleep Apnea
Shi, Y., Chen, L., Chen, T., Li, L., Dai, J., Lui, S., Huang, X., Sweeney, J. A., & Gong, Q. (2017) · Scientific Reports · doi:10.1038/s41598-017-09319-6 · Cited by 81
Vitolo, E., Tatu, K., Pignolo, C., Cauda, F., Costa, T., Ando, A. M. C., & Zennaro, A. (2017) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2017.09.014 · Cited by 87
Sindermann, L., Redlich, R., Opel, N., Böhnlein, J., Dannlowski, U., & Leehr, E. J. (2021) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2021.07.022 · Cited by 80
Chen, G., Wang, J., Gong, J., Qi, Z., Fu, S., Tang, G., Chen, P., Huang, L., & Wang, Y. (2022) · Psychological Medicine · doi:10.1017/s0033291722002392 · Cited by 79
Yu, M., Gao, X., Niu, X., Zhang, M., Yang, Z., Han, S., Cheng, J., & Zhang, Y. (2023) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2022.1070142 · Cited by 93
Thome, J., Terpou, B. A., McKinnon, M. C., & Lanius, R. A. (2019) · Depression and Anxiety · doi:10.1002/da.22977 · Cited by 80
Hu, X., Du, M., Chen, L., Li, L., Zhou, M., Zhang, L., Liu, Q., Lu, L., Mreedha, K., Huang, X., et al. (2017) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2017.04.012 · Cited by 75
Liloia, D., Brasso, C., Cauda, F., Mancuso, L., Nani, A., Manuello, J., Costa, T., Duca, S., & Rocca, P. (2021) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2021.01.010 · Cited by 71
Zhang, Z., Zhang, Y., Wang, H., Lei, M., Jiang, Y., Xiong, D., Chen, Y., Zhang, Y., Zhao, G., Wang, Y., et al. (2025) · Psychological Medicine · doi:10.1017/s0033291725000303 · Cited by 82
Shi, H., Yuan, C., Dai, Z., Ma, H., & Sheng, L. (2016) · Seminars in Arthritis and Rheumatism · doi:10.1016/j.semarthrit.2016.06.002 · Cited by 75
Diagnosis of attention deficit hyperactivity disorder using imaging and signal processing techniques
Sridhar, C., Bhat, S., Acharya, U. R., Adeli, H., & Bairy, G. M. (2017) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2017.07.009 · Cited by 75
Structure of the alexithymic brain: A parametric coordinate-based meta-analysis
Xu, P., Opmeer, E. M., van Tol, M., Goerlich, K. S., & Aleman, A. (2018) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2018.01.004 · Cited by 83
Pezzoli, S., Emsell, L., Yip, S. W., Dima, D., Giannakopoulos, P., Zarei, M., Tognin, S., Arnone, D., James, A. C., Haller, S., et al. (2017) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2017.11.005 · Cited by 74
Fabro, L. D., Schmidt, A., Fortea, L., Delvecchio, G., D’Agostino, A., Raduà, J., Borgwardt, S., & Brambilla, P. (2021) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2021.06.020 · Cited by 74
Wang, Y., Li, Q., Li, Y., He, N., Tang, Y., Chen, L., Long, F., Chen, Y., Kemp, G. J., Lui, S., et al. (2024) · Cerebral Cortex · doi:10.1093/cercor/bhae094 · Cited by 77
Dong, D., Wang, Y., Chang, X., Jiang, Y., Klugah‐Brown, B., Luo, C., & Yao, D. (2017) · Schizophrenia Research · doi:10.1016/j.schres.2017.01.005 · Cited by 72
Brain responses to social norms: Meta‐analyses of f MRI studies
Zinchenko, O. O., & Arsalidou, M. (2017) · Human Brain Mapping · doi:10.1002/hbm.23895 · Cited by 74
Dugre, J. R., Raduà, J., Carignan-Allard, M., Dumais, A., Rubia, K., & Potvin, S. (2020) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2020.09.013 · Cited by 75
Tang, X., Guo, Z., Chen, G., Sun, S., Xiao, S., Chen, P., Tang, G., Huang, L., & Wang, Y. (2024) · Ageing Research Reviews · doi:10.1016/j.arr.2024.102240 · Cited by 77
Wang, X., Luo, Q., Tian, F., Cheng, B., Qiu, L., Wang, S., He, M., Wang, H., Duan, M., & Jia, Z. (2019) · Journal of Psychiatry and Neuroscience · doi:10.1503/jpn.180002 · Cited by 72
Trauma-specific grey matter alterations in PTSD
Meng, L., Jiang, J., Jin, C., Liu, J., Zhao, Y., Wang, W., Li, K., & Gong, Q. (2016) · Scientific Reports · doi:10.1038/srep33748 · Cited by 71
Pan, P., Shi, H., Zhong, J., Xiao, P., Shen, Y., Wu, L., Song, Y., & He, G.-X. (2012) · Neurological Sciences · doi:10.1007/s10072-012-1256-x · Cited by 72
Is obesity related to enhanced neural reactivity to visual food cues? A review and meta-analysis
Morys, F., García‐García, I., & Dagher, A. (2020) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsaa113 · Cited by 71
Picó‐Pérez, M., Moreira, P. S., Ferreira, V. D. M., Raduà, J., Mataix‐Cols, D., Sousa, N., Soriano‐Mas, C., & Morgado, P. F. (2020) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2020.01.033 · Cited by 72
Self-citationZheng, R., Zhang, Y., Yang, Z., Han, S., & Cheng, J. (2021) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2021.671348 · Cited by 71
The roles, challenges, and merits of the p value
Chén, O. Y., Bodelet, J., Saraiva, R. G., Phan, H., Di, J., Nagels, G., Schwantje, T., Cao, H., Gou, J., Reinen, J., et al. (2023) · Patterns · doi:10.1016/j.patter.2023.100878 · Cited by 86
Naghibi, N., Jahangiri, N., Khosrowabadi, R., Eickhoff, C. R., Eickhoff, S. B., Coull, J. T., & Tahmasian, M. (2024) · Neuropsychology Review · doi:10.1007/s11065-023-09588-1 · Cited by 69
Dai, Z., Zhong, J., Xiao, P., Zhu, Y., Chen, F., Pan, P., & Shi, H. (2015) · Neuroscience · doi:10.1016/j.neuroscience.2015.04.066 · Cited by 70
Yang, X., Si, T., Gong, Q., Qiu, L., Jia, Z., Zhou, M., Zhao, Y., Hu, X., Wu, M. C., & Zhu, H. (2016) · Australian & New Zealand Journal of Psychiatry · doi:10.1177/0004867415623858 · Cited by 73
Dugre, J. R., Dumais, A., Bitar, N., & Potvin, S. (2018) · PeerJ · doi:10.7717/peerj.4749 · Cited by 71
Ding, Y., Ou, Y., Pan, P., Shan, X., Chen, J., Liu, F., Zhao, J., & Guo, W. (2018) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2018.11.009 · Cited by 70
Dahlberg, L. S., Lungu, O., & Doyon, J. (2020) · Frontiers in Neurology · doi:10.3389/fneur.2020.00127 · Cited by 68
Neural bases of antisocial behavior: a voxel-based meta-analysis
Aoki, Y. Y., Inokuchi, R., Nakao, T., & Yamasue, H. (2013) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nst104 · Cited by 73
What do results from coordinate-based meta-analyses tell us?
Albajes‐Eizagirre, A., & Raduà, J. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.04.065 · Cited by 66
A systematic review and meta-analysis of voxel-based morphometric studies of migraine
Zhang, X., Zhou, J., Guo, M., Cheng, S., Chen, Y., Jiang, N., Li, X., Hu, S., Tian, Z., Li, Z., et al. (2022) · Journal of Neurology · doi:10.1007/s00415-022-11363-w · Cited by 67
Wang, Q., Li, H., Li, Y.-D., Lv, Y., Ma, H.-B., Xiang, A.-F., Jia, X., & Liu, D.-Q. (2021) · Brain Imaging and Behavior · doi:10.1007/s11682-021-00460-5 · Cited by 57
Arvanitis, A., Handley, R., Kempton, M. J., & Dazzan, P. (2014) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2014.03.014 · Cited by 69
The neuroanatomy of psychotic diathesis: A meta-analytic review
Palaniyappan, L. K., Balain, V., & Liddle, P. F. (2012) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2012.06.007 · Cited by 68
Li, W., Chen, Z., Wu, M. C., Zhu, H., Gu, L., Zhao, Y., Kuang, W., Bi, F., Kemp, G. J., & Gong, Q. (2016) · Journal of Affective Disorders · doi:10.1016/j.jad.2016.12.032 · Cited by 68
Wang, W., Zhao, Y., Hu, X., Huang, X., Kuang, W., Lui, S., Kemp, G. J., & Gong, Q. (2017) · Scientific Reports · doi:10.1038/s41598-017-08944-5 · Cited by 65
Ji, G., Hu, P., Liu, T., Li, Y., Chen, X., Zhu, C., Tian, Y., Chen, X., & Wang, K. (2018) · Radiology · doi:10.1148/radiol.2018172183 · Cited by 66
Metadata
- Authors
- Radua, J., Mataix-Cols, D., Phillips, M. L., El-Hage, W., Kronhaus, D. M., Cardoner, N., & Surguladze, S.
- Affiliations
- University of Pittsburgh (US)
- Cygnet Healthcare Ltd (GB)
- Bellvitge University Hospital (ES)
- King's College London (GB)
- Venue
- European Psychiatry
- Publisher
- Cambridge University Press (CUP)
- Published
- 2011-06-11
- Volume
- 27
- Issue
- 8
- Pages
- 605-611
- ISSN
- 0924-9338 (ISSN-L)
- 1778-3585
- OpenAlex
- W2064405215
- Cited by
- 765
- References
- 32
- Citations by year
- 2026: 63 · 2025: 81 · 2024: 60 · 2023: 73 · 2022: 75 · 2021: 76 · 2020: 57 · 2019: 45 · 2018: 58 · 2017: 45 · 2016: 40 · 2015: 23 · 2014: 26 · 2013: 25 · 2012: 17
- FWCI
- 11.17
- Type
- journal article
- Language
- en
- Open access
- green
- hdl.handle.net
- Licence
- cc-by-nc-nd
- www.cambridge.org/core/terms (unspecified)
- Locations
- European Psychiatry (publishedVersion)
- PubMed (publishedVersion)
- Dipòsit Digital de la Universitat de Barcelona (Universitat de Barcelona) (submittedVersion, cc-by-nc-nd)
- ORCA Online Research @Cardiff (Cardiff University) (submittedVersion)
- Research Portal (King's College London) (submittedVersion)
- Funders
- John D. and Catherine T. MacArthur Foundation
- National Institute for Materials Science
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural and Behavioral Psychology Studies
- Keywords
- activation likelihood estimation, method validation
- MeSH terms
- Adult, Brain, Brain Mapping, Facial Expression, Humans, Magnetic Resonance Imaging, Neuropsychological Tests, Reproducibility of Results, Neuroimaging
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