The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.
A generalized form of context-dependent psychophysiological interactions (gPPI): A comparison to standard approaches
Open accessAbstract
Functional MRI (fMRI) allows one to study task-related regional responses and task-dependent connectivity analysis using psychophysiological interaction (PPI) methods. The latter affords the additional opportunity to understand how brain regions interact in a task-dependent manner. The current implementation of PPI in Statistical Parametric Mapping (SPM8) is configured primarily to assess connectivity differences between two task conditions, when in practice fMRI tasks frequently employ more than two conditions. Here we evaluate how a generalized form of context-dependent PPI (gPPI; http://www.nitrc.org/projects/gppi), which is configured to automatically accommodate more than two task conditions in the same PPI model by spanning the entire experimental space, compares to the standard implementation in SPM8. These comparisons are made using both simulations and an empirical dataset. In the simulated dataset, we compare the interaction beta estimates to their expected values and model fit using the Akaike information criterion (AIC). We found that interaction beta estimates in gPPI were robust to different simulated data models, were not different from the expected beta value, and had better model fits than when using standard PPI (sPPI) methods. In the empirical dataset, we compare the model fit of the gPPI approach to sPPI. We found that the gPPI approach improved model fit compared to sPPI. There were several regions that became non-significant with gPPI. These regions all showed significantly better model fits with gPPI. Also, there were several regions where task-dependent connectivity was only detected using gPPI methods, also with improved model fit. Regions that were detected with all methods had more similar model fits. These results suggest that gPPI may have greater sensitivity and specificity than standard implementation in SPM. This notion is tempered slightly as there is no gold standard; however, data simulations with a known outcome support our conclusions about gPPI. In sum, the generalized form of context-dependent PPI approach has increased flexibility of statistical modeling, and potentially improves model fit, specificity to true negative findings, and sensitivity to true positive findings.
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.
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?
The check wasn’t confident either way, so it gives no verdict — never disputed.
In the citing paper
“with amygdala dysfunction underlying psychopathology;59”
From Distinct and shared therapeutic neural mechanisms of mindfulness-based and social support stress reduction groups in adults with autism spectrum disorder (2023) · cites this paper as [59]
Experimental — accuracy not yet measured
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
A new look at the statistical model identification
Akaike, H. (1974) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1974.1100705 · Cited by 51,879
Model selection and multimodel inference: a practical information-theoretic approach.
Guthery, F. S., Burnham, K. P., & Anderson, D. R. (2003) · The Journal of Wildlife Management · doi:10.2307/3802723 · Cited by 41,495
ANew Look at the Statistical Model Identification
AKAlKE, H. (2011) · Cited by 4,177
Psychophysiological and Modulatory Interactions in Neuroimaging
Friston, K. J., Buechel, C., Fink, G. R., Morris, J., Rolls, E., & Dolan, R. J. (1997) · NeuroImage · doi:10.1006/nimg.1997.0291 · Cited by 3,097
Linear Systems Analysis of Functional Magnetic Resonance Imaging in Human V1
Boynton, G., Engel, S., Glover, G., & Heeger, D. (1996) · Journal of Neuroscience · doi:10.1523/jneurosci.16-13-04207.1996 · Cited by 2,522
Analysis of fMRI Time-Series Revisited
Friston, K. J., Holmes, A. P., Poline, J., Grasby, P. M., Williams, S., Frackowiak, R. S. J., & Turner, R. (1995) · NeuroImage · doi:10.1006/nimg.1995.1007 · Cited by 2,504
A Population-Average, Landmark- and Surface-based (PALS) atlas of human cerebral cortex
Van Essen, D. C. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2005.06.058 · Cited by 1,151
Erroneous analyses of interactions in neuroscience: A problem of significance
Nieuwenhuis, S., Forstmann, B. U., & Wagenmakers, E.-J. (2011) · Nature Neuroscience · doi:10.1038/nn.2886 · Cited by 864
Gitelman, D. R., Penny, W. D., Ashburner, J., & Friston, K. J. (2003) · NeuroImage · doi:10.1016/s1053-8119(03)00058-2 · Cited by 799
Characterizing evoked hemodynamics with fMRI.
Friston, K. J., Frith, C., Turner, R., & Frackowiak, R. (1995) · NeuroImage · doi:10.1006/nimg.1995.1018 · Cited by 711
Flagged first, then by citations
Cited by
Sorted by citations
Items 101–200 of 1,000
Lordier, L., Loukas, S., Grouiller, F., Vollenweider, A., Vasung, L., Meskaldij, D., Lejeune, F., Pittet, M. P., Borradori-Tolsa, C., Lazeyras, F., et al. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.03.078 · Cited by 92
Ren, J., Huang, F., Zhou, Y., Zhuang, L., Xu, J., Gao, C., Qin, S., & Luo, J. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.116751 · Cited by 89
de Wit, S. J., van der Werf, Y. D., Mataix-Cols, D., Trujillo, J. P., van Oppen, P., Veltman, D. J., & van den Heuvel, O. A. (2015) · Psychological Medicine · doi:10.1017/s0033291715001026 · Cited by 86
Klapper, A., Ramsey, R., Wigboldus, D., & Cross, E. S. (2014) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_00651 · Cited by 85
Tozzi, L., Goldstein‐Piekarski, A. N., Korgaonkar, M. S., & Williams, L. M. (2019) · Biological Psychiatry · doi:10.1016/j.biopsych.2019.08.005 · Cited by 88
White, S. F., VanTieghem, M., Brislin, S. J., Sypher, I., Sinclair, S., Pine, D. S., Hwang, S., & Blair, J. (2015) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2015.15020250 · Cited by 84
How Tasks Change Whole-Brain Functional Organization to Reveal Brain-Phenotype Relationships
Greene, A. S., Gao, S., Noble, S., Scheinost, D., & Constable, R. T. (2019) · Cell Reports · doi:10.1016/j.celrep.2020.108066 · Cited by 82
Jacobs, E. G., Weiss, B. K., Makris, N., Whitfield-Gabrieli, S., Buka, S. L., Klibanski, A., & Goldstein, J. M. (2016) · Cerebral Cortex · doi:10.1093/cercor/bhw127 · Cited by 91
Functional connectivity in inhibitory control networks and severity of cannabis use disorder
Filbey, F. M., & Yezhuvath, U. S. (2013) · The American Journal of Drug and Alcohol Abuse · doi:10.3109/00952990.2013.841710 · Cited by 90
Gold, A. L., Shechner, T., Farber, M. J., Spiro, C. N., Leibenluft, E., Pine, D. S., & Britton, J. C. (2016) · Depression and Anxiety · doi:10.1002/da.22470 · Cited by 82
Hwang, S., Nolan, Z. T., White, S. F., Williams, W. C., Sinclair, S., & Blair, J. (2016) · Psychological Medicine · doi:10.1017/s0033291716000118 · Cited by 86
Zhou, X., Zimmermann, K., Xin, F., Zhao, W., Derckx, R. T., Sassmannshausen, A., Scheele, D., Hurlemann, R., Weber, B., Kendrick, K. M., et al. (2019) · Biological Psychiatry: Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2019.04.006 · Cited by 77
Multimodal mapping of the face connectome
Wang, Y., Metoki, A., Smith, D. V., Medaglia, J. D., Zang, Y., Benear, S. L., Popal, H. S., Lin, Y., & Olson, I. R. (2020) · Nature Human Behaviour · doi:10.1038/s41562-019-0811-3 · Cited by 93
Yao, S., Becker, B., Geng, Y., Zhao, Z., Xu, X., Zhao, W., Ren, P., & Kendrick, K. M. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.02.035 · Cited by 75
Gold, A. L., Abend, R., Britton, J. C., Behrens, B., Farber, M. J., Ronkin, E. G., Chen, G., Leibenluft, E., & Pine, D. S. (2020) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2019.19060650 · Cited by 80
Sex-dependent neural effect of oxytocin during subliminal processing of negative emotion faces.
Luo, L., Becker, B., Geng, Y., Zhao, Z., Gao, S., Zhao, W., Yao, S., Zheng, X., Ma, X., Gao, Z., et al. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.08.079 · Cited by 79
Steinbeis, N., Bernhardt, B. C., & Singer, T. (2015) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsu057 · Cited by 79
Koike, T., Sumiya, M., Nakagawa, E., Okazaki, S., & Sadato, N. (2019) · eNeuro · doi:10.1523/eneuro.0284-18.2019 · Cited by 84
Shanahan, L. K., Gjorgieva, E., Paller, K. A., Kahnt, T., & Gottfried, J. A. (2018) · eLife · doi:10.7554/elife.39681 · Cited by 69
Geng, Y., Zhao, W., Zhou, F., Ma, X., Yao, S., Hurlemann, R., Becker, B., & Kendrick, K. M. (2018) · Frontiers in Neuroscience · doi:10.3389/fnins.2018.00512 · Cited by 78
Schreiter, S., Spengler, S., Willert, A., Mohnke, S., Herold, D., Erk, S., Romanczuk‐Seiferth, N., Quinlivan, E., Attar, C. H., Banzhaf, C., et al. (2016) · Psychological Medicine · doi:10.1017/s0033291716001963 · Cited by 84
Striatal Hypersensitivity During Stress in Remitted Individuals with Recurrent Depression
Admon, R., Holsen, L. M., Aizley, H. G., Remington, A., Whitfield, S., Goldstein, J. M., & Pizzagalli, D. A. (2014) · Biological Psychiatry · doi:10.1016/j.biopsych.2014.09.019 · Cited by 77
A common neural network differentially mediates direct and social fear learning
Lindström, B., Haaker, J., & Olsson, A. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.11.039 · Cited by 80
Boccadoro, S., Cracco, E., Hudson, A. R., Bardi, L., Nijhof, A. D., Wiersema, J. R., Braß, M., & Mueller, S. C. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116193 · Cited by 79
I can see where you would be: Patterns of fMRI activity reveal imagined landmarks
Boccia, M., Sulpizio, V., Palermo, L., Piccardi, L., Guariglia, C., & Galati, G. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.08.034 · Cited by 76
Zhou, F., Geng, Y., Xin, F., Li, J., Feng, P., Liu, C., Zhao, W., Feng, T., Guastella, A. J., Ebstein, R. P., et al. (2019) · Biological Psychiatry · doi:10.1016/j.biopsych.2019.07.007 · Cited by 70
Sharoh, D., van Mourik, T., Bains, L. J., Segaert, K., Weber, K., Peter Hagoort, A., & Norris, D. G. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1907858116 · Cited by 77
Congruency and reactivation aid memory integration through reinstatement of prior knowledge
van Kesteren, M. T. R., Rignanese, P., Gianferrara, P. G., Krabbendam, L., & Meeter, M. (2020) · Scientific Reports · doi:10.1038/s41598-020-61737-1 · Cited by 85
Neural Insensitivity to the Effects of Hunger in Women Remitted From Anorexia Nervosa
Kaye, W. H., Wierenga, C. E., Bischoff‐Grethe, A., Berner, L. A., Ely, A. V., Bailer, U. F., Paulus, M. P., & Fudge, J. L. (2020) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2019.19030261 · Cited by 77
Differential involvement of frontoparietal network and insula cortex in emotion regulation
Li, W., Yang, P., Ngetich, R. K., Zhang, J., Jin, Z., & Li, L. (2021) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2021.107991 · Cited by 83
McPherson, M. J., Barrett, F. S., López-González, M., Jiradejvong, P., & Limb, C. J. (2016) · Scientific Reports · doi:10.1038/srep18460 · Cited by 84
Yuan, K., Yu, D., Bi, Y., Wang, R., Li, M., Zhang, Y., Dong, M., Zhai, J., Li, Y., Lu, X., et al. (2017) · Human Brain Mapping · doi:10.1002/hbm.23690 · Cited by 76
Genauck, A., Quester, S., Wüstenberg, T., Mörsen, C. P., Heinz, A., & Romanczuk‐Seiferth, N. (2017) · Scientific Reports · doi:10.1038/s41598-017-16433-y · Cited by 84
Schmitt, R., Winter, D., Niedtfeld, I., Herpertz, S. C., & Schmahl, C. G. (2016) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2016.07.003 · Cited by 80
Kaldewaij, R., Koch, S. B. J., Hashemi, M. M., Zhang, W., Klumpers, F., & Roelofs, K. (2021) · Nature Human Behaviour · doi:10.1038/s41562-021-01055-2 · Cited by 88
Prokopiou, P. C., Engels, N., Papp, K. V., Scott, M. R., Schultz, A. P., Schneider, C., Farrell, M. E., Buckley, R. F., Quiroz, Y. T., Fakhri, G. E., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-28986-2 · Cited by 81
Fan, Y., Pestke, K., Feeser, M., Aust, S., Pruessner, J. C., Böker, H., Bajbouj, M., & Grimm, S. (2015) · Neuropsychopharmacology · doi:10.1038/npp.2015.123 · Cited by 75
Cognitive dissonance induction in everyday life: An fMRI study
de Vries, J., Byrne, M., & Kehoe, E. G. (2014) · Social Neuroscience · doi:10.1080/17470919.2014.990990 · Cited by 82
Memory consolidation reconfigures neural pathways involved in the suppression of emotional memories
Liu, Y., Lin, W., Liu, C., Luo, Y., Wu, J., Bayley, P. J., & Qin, S. (2016) · Nature Communications · doi:10.1038/ncomms13375 · Cited by 80
Franzmeier, N., Hartmann, J., Taylor, A. N. W., Caballero, M. Á. A., Lee, S.-V., Buerger, K., Kambeitz-Ilankovic, L., Ertl-Wagner, B., Mueller, C., Catak, C., et al. (2017) · Journal of Alzheimer's Disease · doi:10.3233/jad-170360 · Cited by 69
Differential effects of parent and peer presence on neural correlates of risk taking in adolescence
van Hoorn, J., McCormick, E. M., Rogers, C. R., Ivory, S. L., & Telzer, E. H. (2018) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsy071 · Cited by 82
Functional connectivity change as shared signal dynamics
Cole, M. W., Yang, G. J., Murray, J. D., Repovš, G., & Anticevic, A. (2016) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2015.11.011 · Cited by 60
Bein, O., Reggev, N., & Maril, A. (2014) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2014.09.046 · Cited by 75
Dídac Vidal-piñeiro, A., Martín-Trias, P., Arenaza‐Urquijo, E. M., Sala‐Llonch, R., Clemente, I. C., Mena-Sánchez, I., Bargalló, N., Falcón, C., Pascual‐Leone, Á., & Bartrés‐Faz, D. (2014) · Brain stimulation · doi:10.1016/j.brs.2013.12.016 · Cited by 70
Fowler, C. H., Miernicki, M. E., Rudolph, K. D., & Telzer, E. H. (2017) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2017.09.002 · Cited by 71
Brain responses to drug cues predict craving changes in abstinent heroin users: A preliminary study
Liu, S., Wang, S., Zhang, M., Xu, Y., Shao, Z., Chen, L., Yang, W., Liu, J., & Yuan, K. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118169 · Cited by 69
Metoki, A., Wang, Y., & Olson, I. R. (2021) · Cerebral Cortex · doi:10.1093/cercor/bhab260 · Cited by 72
Gorka, S. M., Fitzgerald, D. A., King, A. C., & Phan, K. L. (2013) · Psychopharmacology · doi:10.1007/s00213-013-3090-0 · Cited by 71
Goldstein, J. M., Cohen, J. E., Mareckova, K., Holsen, L., Whitfield-Gabrieli, S., Gilman, S. E., Buka, S. L., & Hornig, M. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2014464118 · Cited by 70
Meier, M. L., Stämpfli, P., Vrana, A., Humphreys, B. K., Seifritz, E., & Hotz-Boendermaker, S. (2016) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2016.00386 · Cited by 73
Voice-sensitive brain networks encode talker-specific phonetic detail
Myers, E. B., & Theodore, R. M. (2016) · Brain and Language · doi:10.1016/j.bandl.2016.11.001 · Cited by 71
Abrams, D. A., Chen, T., Odriozola, P., Cheng, K. M., Baker, A. E., Padmanabhan, A., Ryali, S., Kochalka, J., Feinstein, C., & Menon, V. (2016) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1602948113 · Cited by 81
Michels, L., Tuura, R., & Kucian, K. (2017) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2017.03.005 · Cited by 71
Jarcho, J. M., Romer, A. L., Shechner, T., Galvan, A., Guyer, A. E., Leibenluft, E., Pine, D. S., & Nelson, E. E. (2015) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2015.03.002 · Cited by 70
Social hierarchy modulates neural responses of empathy for pain
Feng, C., Li, Z., Xue, F., Wang, L., Tian, T., & Luo, Y. (2015) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsv135 · Cited by 68
Ladouceur, C. D., Kerestes, R., Schlund, M. W., Shirtcliff, E. A., Lee, Y., & Dahl, R. E. (2018) · Psychoneuroendocrinology · doi:10.1016/j.psyneuen.2018.12.016 · Cited by 76
Santangelo, V., & Macaluso, E. (2013) · Journal of Neuroscience · doi:10.1523/jneurosci.4138-12.2013 · Cited by 73
Admon, R., Nickerson, L. D. H., Dillon, D. G., Holmes, A. J., Bogdan, R., Kumar, P., Dougherty, D. D., Iosifescu, D. V., Mischoulon, D., D, M. F. M., et al. (2014) · Psychological Medicine · doi:10.1017/s0033291714001123 · Cited by 75
The right inferior frontal gyrus processes nested non-local dependencies in music
Cheung, V. K. M., Meyer, L., Friederici, A. D., & Koelsch, S. (2018) · Scientific Reports · doi:10.1038/s41598-018-22144-9 · Cited by 67
Sex- and context-dependent effects of oxytocin on social sharing
Ma, X., Zhao, W., Luo, R., Zhou, F., Geng, Y., Xu, L., Gao, Z., Zheng, X., Becker, B., & Kendrick, K. M. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.08.004 · Cited by 68
The neural circuitry of affect-induced distortions of trust
Engelmann, J. B., Meyer, F., Ruff, C. C., & Fehr, E. (2019) · Science Advances · doi:10.1126/sciadv.aau3413 · Cited by 70
Integration of individual and social information for decision-making in groups of different sizes
Park, S. A., Goïame, S., O'Connor, D. A., & Dreher, J.-C. (2017) · PLOS Biology · doi:10.1371/journal.pbio.2001958 · Cited by 67
Abd-Elsalam, S. M., Ezz, M. M., Hashem, S., Elakel, W., Salama, R. M., Elmakhzangy, H., & ElHefnawi, M. (2019) · Informatics in Medicine Unlocked · doi:10.1016/j.imu.2019.100267 · Cited by 67
Young, K. S., Burklund, L. J., Torre, J. B., Saxbe, D., Lieberman, M. D., & Craske, M. G. (2017) · Psychiatry Research - Neuroimaging · doi:10.1016/j.pscychresns.2017.01.005 · Cited by 64
“Psychophysiological interaction (PPI) analyses were conducted using right and left amygdala seed regions to assess functional connectivity of these regions in a task-dependent manner, implemented using generalized PPI (gPPI) within SPM8 (McLaren et al., 2012).”
MethodZhao, W., Yao, S., Li, Q., Geng, Y., Ma, X., Luo, L., Xu, L., & Kendrick, K. M. (2016) · Human Brain Mapping · doi:10.1002/hbm.23190 · Cited by 65
Ho, S.-H. S., & Swain, J. E. (2017) · Behavioural Brain Research · doi:10.1016/j.bbr.2017.02.045 · Cited by 66
The left inferior frontal gyrus: A neural crossroads between abstract and concrete knowledge
Rosa, P. A. D., Catricalà, E., Canini, M., Vigliocco, G., & Cappa, S. F. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.04.021 · Cited by 63
Neural Correlates of Motor Imagery of Gait in Amyotrophic Lateral Sclerosis
Abidi, M., de Marco, G., Grami, F., Termoz, N., Couillandre, A., Querin, G., Bede, P., & Pradat, P. (2020) · Journal of Magnetic Resonance Imaging · doi:10.1002/jmri.27335 · Cited by 65
Trujillo, J. P., Gerrits, N. J. H. M., Veltman, D. J., Berendse, H. W., van der Werf, Y. D., & van den Heuvel, O. A. (2015) · Human Brain Mapping · doi:10.1002/hbm.22723 · Cited by 68
Configural and Elemental Coding of Natural Odor Mixture Components in the Human Brain
Howard, J. D., & Gottfried, J. A. (2014) · Neuron · doi:10.1016/j.neuron.2014.10.012 · Cited by 67
Dynamic network coding of working-memory domains and working-memory processes
Soreq, E., Leech, R., & Hampshire, A. (2019) · Nature Communications · doi:10.1038/s41467-019-08840-8 · Cited by 64
King, A. P., Block, S. R., Sripada, R. K., Rauch, S. A. M., Porter, K. E., Favorite, T. K., Giardino, N., & Liberzon, I. (2016) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2016.00154 · Cited by 64
Understanding psychophysiological interaction and its relations to beta series correlation
Di, X., Zhang, Z., & Biswal, B. B. (2020) · Brain Imaging and Behavior · doi:10.1007/s11682-020-00304-8 · Cited by 62
Barksdale, B. R., Enten, L., DeMarco, A., Kline, R., Doss, M. K., Nemeroff, C. B., & Fonzo, G. A. (2025) · Molecular Psychiatry · doi:10.1038/s41380-025-03033-w · Cited by 64
Cisler, J. M., Sigel, B. A., Kramer, T. L., Smitherman, S., Vanderzee, K. L., Pemberton, J. R., & Kilts, C. D. (2015) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2015.09.011 · Cited by 71
Hanson, J. L., Knodt, A. R., Brigidi, B. D., & Hariri, A. R. (2017) · Psychological Medicine · doi:10.1017/s0033291717003348 · Cited by 64
Hearne, L. J., Cocchi, L., Zalesky, A., & Mattingley, J. B. (2015) · Human Brain Mapping · doi:10.1002/hbm.22802 · Cited by 67
Smith, D. V., Gseir, M., Speer, M. E., & Delgado, M. R. (2016) · Human Brain Mapping · doi:10.1002/hbm.23216 · Cited by 61
The role of motor system in action-related language comprehension in L1 and L2: An fMRI study
Tian, L., Chen, H., Zhao, W., Wu, J., Zhang, Q., De, A., Leppänen, P. H. T., Cong, F., & Parviainen, T. M. (2019) · Brain and Language · doi:10.1016/j.bandl.2019.104714 · Cited by 62
Wen, Z., Seo, J., Pace-Schott, E. F., & Milad, M. R. (2022) · Molecular Psychiatry · doi:10.1038/s41380-022-01462-5 · Cited by 62
Neural correlates of emotion acceptance vs worry or suppression in generalized anxiety disorder
Ellard, K. K., Barlow, D. H., Whitfield-Gabrieli, S., Gabrieli, J. D. E., & Deckersbach, T. (2017) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsx025 · Cited by 59
“To explore differences in emotion regulation driven functional connectivity, a generalized psychophysiological interaction (gPPI) analysis (Friston et al., 1997; McLaren et al., 2012) was conducted using SPM8.”
MethodWeyandt, L. L., Clarkin, C. M., Holding, E. Z., May, S. E., Marraccini, M. E., Guðmundsdóttir, B. G., Shepard, E., & Thompson, L. (2020) · Clinical and Translational Neuroscience · doi:10.1177/2514183x20974231 · Cited by 80
Perceptual coupling and decoupling of the default mode network during mind-wandering and reading
Zhang, M., Bernhardt, B. C., Wang, X., Varga, D., Krieger‐Redwood, K., Royer, J., Rodríguez‐Cruces, R., de Wael, R. V., Margulies, D. S., Smallwood, J., et al. (2022) · eLife · doi:10.7554/elife.74011 · Cited by 67
Controllability Modulates the Anticipatory Response in the Human Ventromedial Prefrontal Cortex
Kerr, D. L., McLaren, D. G., Mathy, R. M., & Nitschke, J. B. (2012) · Frontiers in Psychology · doi:10.3389/fpsyg.2012.00557 · Cited by 61
Self-citationNeural correlates of conceptual-level fear generalization in posttraumatic stress disorder
Mid-Atlantic MIRECC Workgroup, Morey, R. A., Haswell, C. C., Stjepanović, D., Dunsmoor, J. E., & LaBar, K. S. (2020) · Neuropsychopharmacology · doi:10.1038/s41386-020-0661-8 · Cited by 64
Oxytocin enhances the pain‐relieving effects of social support in romantic couples
Kreuder, A., Wassermann, L., Wollseifer, M., Ditzen, B., Eckstein, M., Stoffel‐Wagner, B., Hennig, J., Hurlemann, R., & Scheele, D. (2019) · Human Brain Mapping · doi:10.1002/hbm.24368 · Cited by 62
The role of the right temporo–parietal junction in social decision‐making
Bitsch, F., Berger, P., Nagels, A., Falkenberg, I., & Straube, B. (2018) · Human Brain Mapping · doi:10.1002/hbm.24061 · Cited by 61
Oliva, V., Hartley-Davies, R., Moran, R., Pickering, A. E., & Brooks, J. C. (2022) · eLife · doi:10.7554/elife.71877 · Cited by 61
Greene, R. K., Spanos, M., Alderman, C., Walsh, E., Bizzell, J., Mosner, M. G., Kinard, J. L., Stuber, G. D., Chandrasekhar, T., Politte, L. C., et al. (2018) · Journal of Neurodevelopmental Disorders · doi:10.1186/s11689-018-9228-y · Cited by 55
Lenartowicz, A., Lu, S., Rodriguez, C., Lau, E. P., Walshaw, P. D., McCracken, J. T., Cohen, M. S., & Loo, S. K. (2016) · NeuroImage Clinical · doi:10.1016/j.nicl.2016.01.023 · Cited by 65
Visual-motor functional connectivity in preschool children emerges after handwriting experience
Vinci-Booher, S., James, T. W., & James, K. H. (2016) · Trends in Neuroscience and Education · doi:10.1016/j.tine.2016.07.006 · Cited by 58
Increased anterior cingulate cortex response precedes behavioural adaptation in anorexia nervosa
Geisler, D., Ritschel, F., King, J. A., Bernardoni, F., Seidel, M., Boehm, I., Runge, F., Goschke, T., Roessner, V., Smolka, M. N., et al. (2017) · Scientific Reports · doi:10.1038/srep42066 · Cited by 58
Distributed Neural Activity Patterns during Human-to-Human Competition
Piva, M., Zhang, X., Noah, J. A., Chang, S. W. C., & Joy Hirsch, C. (2017) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2017.00571 · Cited by 58
Horne, C. M., & Norbury, R. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.01.025 · Cited by 61
Spontaneous Brain Activity Predicts Task-Evoked Activity During Animate Versus Inanimate Touch
Scalabrini, A., Ebisch, S. J. H., Huang, Z., Plinio, S. D., Perrucci, M. G., Romani, G. L., Mucci, C., & Northoff, G. (2018) · Cerebral Cortex · doi:10.1093/cercor/bhy340 · Cited by 58
Krause-Utz, A., Winter, D., Schriner, F., Chiu, C.-D., Lis, S., Spinhoven, P., Bohus, M., Schmahl, C., & Elzinga, B. M. (2018) · European Archives of Psychiatry and Clinical Neuroscience · doi:10.1007/s00406-017-0806-x · Cited by 57
Heinzel, S., Kaufmann, C., Grützmann, R., Hummel, R., Klawohn, J., Riesel, A., Bey, K., Lennertz, L., Wagner, M., & Kathmann, N. (2018) · NeuroImage: Clinical · doi:10.1016/j.nicl.2017.10.039 · Cited by 55
Ellard, K. K., Gosai, A. K., Felicione, J. M., Peters, A. T., Shea, C. V., Sylvia, L. G., Nierenberg, A. A., Widge, A. S., Dougherty, D. D., & Deckersbach, T. (2018) · Bipolar Disorders · doi:10.1111/bdi.12709 · Cited by 59
Bertocci, M. A., Afriyie-Agyemang, Y., Rozovsky, R., Iyengar, S., Stiffler, R. S., Aslam, H. A., Bebko, G. M., & Phillips, M. L. (2022) · Molecular Psychiatry · doi:10.1038/s41380-022-01899-8 · Cited by 65
Metadata
- Authors
- McLaren, D. G., Ries, M. L., Xu, G., & Johnson, S. C.
- Affiliations
- University of Wisconsin–Madison (US)
- Corresponding author
- Johnson, Sterling C.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2012-07
- Volume
- 61
- Issue
- 4
- Pages
- 1277-1286
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC3376181
- OpenAlex
- W2132137022
- Cited by
- 1,445
- References
- 24
- Citations by year
- 2026: 99 · 2025: 121 · 2024: 113 · 2023: 100 · 2022: 117 · 2021: 125 · 2020: 139 · 2019: 115 · 2018: 129 · 2017: 120 · 2016: 122 · 2015: 71 · 2014: 44 · 2013: 19 · 2012: 7
- FWCI
- 23.11
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Department of Veterans Affairs Merit Review (I01CX000165)
- National Institutes of Health (AG021155, AG000213)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Keywords
- generalized psychophysiological interaction, functional MRI, statistical parametric mapping, model fit, Akaike information criterion, brain connectivity
- MeSH terms
- Brain, Brain Mapping, Female, Humans, Image Interpretation, Computer-Assisted, Magnetic Resonance Imaging, Male, Middle Aged, Models, Neurological, Psychophysiology, Sensitivity and Specificity
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