Power calculation for group fMRI studies accounting for arbitrary design and temporal autocorrelation

Temporal Autocorrelation in Univariate Linear Modeling of FMRI Data

Woolrich, M. W., Ripley, B. D., Brady, M., & Smith, S. M. (2001) · NeuroImage · doi:10.1006/nimg.2001.0931 · Cited by 2,859

General multilevel linear modeling for group analysis in FMRI

Beckmann, C. F., Jenkinson, M., & Smith, S. M. (2003) · NeuroImage · doi:10.1016/s1053-8119(03)00435-x · Cited by 1,464

Estimating sample size in functional MRI (fMRI) neuroimaging studies: Statistical power analyses

Desmond, J. E., & Glover, G. H. (2002) · Journal of Neuroscience Methods · doi:10.1016/s0165-0270(02)00121-8 · Cited by 716

Classical and Bayesian Inference in Neuroimaging: Applications

Friston, K. J., Glaser, D. E., Henson, R. N., Kiebel, S. J., Phillips, C. L. M., & Ashburner, J. (2002) · NeuroImage · doi:10.1006/nimg.2002.1091 · Cited by 709

Empirical Analyses of BOLD fMRI Statistics

Zarahn, E., Aguirre, G. K., & D’Esposito, M. (1997) · NeuroImage · doi:10.1006/nimg.1997.0263 · Cited by 695

Stochastic Designs in Event-Related fMRI

Friston, K. J., Zarahn, E., Josephs, O., Henson, R. N., & Dale, A. M. (1999) · NeuroImage · doi:10.1006/nimg.1999.0498 · Cited by 634

Classical and Bayesian Inference in Neuroimaging: Theory

Friston, K. J., Penny, W. D., Phillips, C. L. M., Kiebel, S. J., Hinton, G. E., & Ashburner, J. (2002) · NeuroImage · doi:10.1006/nimg.2002.1090 · Cited by 597

Empirical Analyses of BOLD fMRI Statistics

Aguirre, G. K., Zarahn, E., & D’Esposito, M. (1997) · NeuroImage · doi:10.1006/nimg.1997.0264 · Cited by 474

Optimization of experimental design in fMRI: a general framework using a genetic algorithm

Wager, T. D., & Nichols, T. E. (2003) · NeuroImage · doi:10.1016/s1053-8119(02)00046-0 · Cited by 458

Event-related functional magnetic resonance imaging: modelling, inference and optimization

Josephs, O., & Henson, R. N. A. (1999) · Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences · doi:10.1098/rstb.1999.0475 · Cited by 425

Midazolam and Ketamine Produce Distinct Neural Changes in Memory, Pain, and Fear Networks during Pain

Vogt, K. M., Ibinson, J. W., Smith, C., Citro, A. T., Norton, C. M., Karim, H. T., Popov, V., Mahajan, A., Aizenstein, H. J., Reder, L. M., et al. (2021) · Anesthesiology · doi:10.1097/aln.0000000000003774 · Cited by 18

The Physiological Bases of Hidden Noise-Induced Hearing Loss: Protocol for a Functional Neuroimaging Study

Dewey, R. S., Hall, D. A., Guest, H., Prendergast, G., Plack, C. J., & Francis, S. (2018) · JMIR Research Protocols · doi:10.2196/resprot.9095 · Cited by 18

Physiological Measurements

Dalenberg, J. R., Hoogeveen, H. R., & Lorist, M. M. (2018) · Elsevier eBooks · doi:10.1016/b978-0-08-101743-2.00011-x · Cited by 18

Power of mind: Attentional focus rather than palatability dominates neural responding to visual food stimuli in females with overweight

Franssen, S., Jansen, A. T. M., van den Hurk, J., Roebroeck, A. F., & Roefs, A. (2020) · Appetite · doi:10.1016/j.appet.2020.104609 · Cited by 21

Phonemic segmentation of narrative speech in human cerebral cortex

Gong, X. L., Huth, A. G., Deniz, F., Johnson, K. A., Gallant, J. L., & Theunissen, F. E. (2023) · Nature Communications · doi:10.1038/s41467-023-39872-w · Cited by 19

Magnetic Resonance Imaging Studies on Acupuncture Therapy in Depression: A Systematic Review

Zhang, J., Wu, X., Nie, D., Zhuo, Y., Li, J., Hu, Q., Xu, J., & Yu, H. (2021) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2021.670739 · Cited by 18

Functional specificity and neural integration in the aesthetic appreciation of artworks with implied motion

Bara, I., Darda, K. M., Kurz, A. S., & Ramsey, R. (2021) · European Journal of Neuroscience · doi:10.1111/ejn.15479 · Cited by 17

Research Methods in Social and Affective Neuroscience

Berkman, E. T., Cunningham, W. A., & Lieberman, M. D. (2014) · Cambridge University Press eBooks · doi:10.1017/cbo9780511996481.011 · Cited by 17

Optimal design of multi-subject blocked fMRI experiments

Maus, B., van Breukelen, G., Goebel, R., & Berger, M. P. F. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.03.019 · Cited by 16

A Preferential Role for Ventromedial Prefrontal Cortex in Assessing “the Value of the Whole” in Multiattribute Object Evaluation

Pelletier, G., Aridan, N., Fellows, L. K., & Schönberg, T. (2021) · Journal of Neuroscience · doi:10.1523/jneurosci.0241-21.2021 · Cited by 22

Health Communications: Predicting Behavior Change from the Brain

Cascio, C. N., Cin, S. D., & Falk, E. B. (2013) · Springer eBooks · doi:10.1007/978-1-4614-6852-3_4 · Cited by 16

Inconsistency of findings due to low power: A structural MRI study of bilingualism

Munson, B. A., & Hernández, A. E. (2019) · Brain and Language · doi:10.1016/j.bandl.2019.104642 · Cited by 14

Interactive effects of gender and sexual orientation on cortical thickness, surface area and gray matter volume: a structural brain MRI study

Wang, D., Han, L., Xi, C., Xu, Y., Lai, J., Lu, S., Huang, M., Hu, J., Wei, N., Xu, W., et al. (2020) · Quantitative Imaging in Medicine and Surgery · doi:10.21037/qims.2020.03.07 · Cited by 15

More complex than you might think: Neural representations of food reward value in obesity

Pimpini, L., Kochs, S., Franssen, S., van den Hurk, J., Valente, G., Roebroeck, A. F., Jansen, A. T. M., & Roefs, A. (2022) · Appetite · doi:10.1016/j.appet.2022.106164 · Cited by 16

Beyond boundaries: investigating shared and divergent connectivity in the pre-/postcentral gyri and supplementary motor area

Alahmadi, A. A. S. (2024) · Neuroreport · doi:10.1097/wnr.0000000000002011 · Cited by 14

Arterial cerebral blood volume-weighted functional MRI using pseudocontinuous arterial spin tagging (AVAST)

Jahanian, H., Peltier, S., Noll, D. C., & Garcia, L. H. (2014) · Magnetic Resonance in Medicine · doi:10.1002/mrm.25220 · Cited by 13

Exploring Functional Connectivity Networks with Multichannel Brain Array Coils

Anteraper, S. A., Whitfield, S., Keil, B. R., Shannon, S., Gabrieli, J. D. E., & Triantafyllou, C. (2013) · Brain Connectivity · doi:10.1089/brain.2012.0113 · Cited by 13

Can we have a second helping? A preregistered direct replication study on the neurobiological mechanisms underlying self‐control

Scholz, C., Chan, H., Poldrack, R. A., de Ridder, D. T. D., Smidts, A., & van der Laan, L. N. (2022) · Human Brain Mapping · doi:10.1002/hbm.26065 · Cited by 10

Differential perception of sharp pain in patients with borderline personality disorder

Schloss, N., Shabes, P., Kuniss, S., Willis, F. M., Treede, R., Schmahl, C. G., & Baumgärtner, U. (2019) · European Journal of Pain · doi:10.1002/ejp.1411 · Cited by 13

Alternative-based thresholding with application to presurgical fMRI

Durnez, J., Moerkerke, B., Bartsch, A., & Nichols, T. E. (2013) · Cognitive Affective & Behavioral Neuroscience · doi:10.3758/s13415-013-0185-3 · Cited by 13

Number of events and reliability in fMRI

Turner, B. O., & Miller, M. B. (2013) · Cognitive Affective & Behavioral Neuroscience · doi:10.3758/s13415-013-0178-2 · Cited by 12

Emotional learning promotes perceptual predictions by remodeling stimulus representation in visual cortex

Meaux, E., Virginie Sterpenich, A., & Vuilleumier, P. O. (2019) · Scientific Reports · doi:10.1038/s41598-019-52615-6 · Cited by 12

Neurocognitive mechanisms underlying improvement of prosocial responses by a novel implicit compassion promotion task

Kim, S. A., Hamann, S. B., & Kim, S. H. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118333 · Cited by 13

Aripiprazole compared with placebo for auditory verbal hallucinations in youth with borderline personality disorder: Protocol for the VERBATIM randomized controlled trial

Chanen, A. M., Betts, J. K., Jackson, H. J., McGorry, P. D., Nelson, B., Cotton, S., Bartholomeusz, C., Jovev, M., Ratheesh, A., Davey, C. G., et al. (2019) · Early Intervention in Psychiatry · doi:10.1111/eip.12774 · Cited by 12

Reply to: fMRI replicability depends upon sufficient individual-level data

Turner, B. O., Santander, T., Paul, E. J., Barbey, A. K., & Miller, M. B. (2019) · Communications Biology · doi:10.1038/s42003-019-0379-5 · Cited by 12

Neural and self-reported responses to antisocial news stories: Entertaining versus traditional news introduction

Kim, S. A., Kim, S. H., & Hamann, S. B. (2021) · Computers in Human Behavior · doi:10.1016/j.chb.2021.106994 · Cited by 11

Optimal Design for Functional Magnetic Resonance Imaging Experiments

Maus, B., & van Breukelen, G. (2013) · Zeitschrift für Psychologie · doi:10.1027/2151-2604/a000145 · Cited by 11

Neural Correlates of Consumer Buying Motivations: A 7T functional Magnetic Resonance Imaging (fMRI) Study

Goodman, A. M., Wang, Y., Kwon, W., Byun, S., Katz, J. S., & Deshpande, G. (2017) · Frontiers in Neuroscience · doi:10.3389/fnins.2017.00512 · Cited by 11

Providing Evidence for the Null Hypothesis in Functional Magnetic Resonance Imaging Using Group-Level Bayesian Inference

Masharipov, R. S., Knyazeva, I., Nikolaev, Y., Korotkov, A. D., Didur, M., Cherednichenko, D. V., & Kireev, M. V. (2021) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2021.738342 · Cited by 12

Hierarchical Bayesian Analyses for Modeling BOLD Time Series Data

Molloy, M. F., Bahg, G., Li, X., Steyvers, M., Lu, Z., & Turner, B. M. (2018) · Computational Brain & Behavior · doi:10.1007/s42113-018-0013-5 · Cited by 11

Predictive Coding and Internal Error Correction in Speech Production

Teghipco, A., Okada, K., Murphy, E., & Hickok, G. S. (2022) · Neurobiology of Language · doi:10.1162/nol_a_00088 · Cited by 13

Efficacy and neural mechanism of acupuncture treatment in older adults with subjective cognitive decline: study protocol for a randomised controlled clinical trial

Yan, C.-Q., Zhou, P., Wang, X., Tu, J. F., Hu, S., Huo, J., Wang, Z., Shi, G., Zhang, Y., Li, J., et al. (2019) · BMJ Open · doi:10.1136/bmjopen-2018-028317 · Cited by 10

Variational Bayesian Parameter Estimation Techniques for the General Linear Model

Starke, L., & Ostwald, D. (2017) · Frontiers in Neuroscience · doi:10.3389/fnins.2017.00504 · Cited by 10

Arterial blood contrast (ABC) enabled by magnetization transfer (MT): a novel MRI technique for enhancing the measurement of brain activation changesPreprint

Schulz, J., Fazal, Z. A., Metere, R., Marques, J. P., & Norris, D. G. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.05.20.106666 · Cited by 10

A standardized framework to test event-based experiments

Lepauvre, A., Hirschhorn, R., Bendtz, K., Mudrik, L., & Melloni, L. (2024) · Behavior Research Methods · doi:10.3758/s13428-024-02508-y · Cited by 9

Brain and Behavior in Persuasion: The Role of Affective‐Cognitive Matching

Plinio, S. D., Aquino, A., Haddock, G., Alparone, F. R., & Ebisch, S. J. H. (2025) · Psychophysiology · doi:10.1111/psyp.70088 · Cited by 11

Is the Brainstem Activation Different Between Healthy Young Male and Female Volunteers at Initiation of Voiding? A High Definition 7-Tesla Magnetic Resonance Imaging Study

Schott, B., Choksi, D., Tran, K., Karmonik, C., Salazar, B., Boone, T. B., & Khavari, R. (2023) · International Neurourology Journal · doi:10.5213/inj.2346104.052 · Cited by 9

Oxytocin differentially modulates reward system responses to social and non-social incentives

Thurston, M. D., Ericksen, L. C., Jacobson, M. M., Bustamante, A., Koppelmans, V., Mickey, B. J., & Love, T. (2024) · Psychopharmacology · doi:10.1007/s00213-024-06695-6 · Cited by 9

Robust Spatial Extent Inference With a Semiparametric Bootstrap Joint Inference Procedure

Vandekar, S., Satterthwaite, T. D., Xia, C. H., Adebimpe, A., Ruparel, K., Gur, R. C., Gur, R. E., & Shinohara, R. T. (2019) · Biometrics · doi:10.1111/biom.13114 · Cited by 9

Low-level carbon monoxide exposure affects BOLD fMRI response

Bendell, C., Moosavi, S. H., & Herigstad, M. (2019) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1177/0271678x19887358 · Cited by 9

Psychobiology of Stress and Adolescent Depression (PSY SAD) Study: Protocol overview for an fMRI-based multi-method investigation

Sichko, S., Bui, T. Q., Vinograd, M., Shields, G. S., Saha, K., Devkota, S., Alvarez, H. A. O., Carroll, J., Cole, S. W., Irwin, M. R., et al. (2021) · Brain Behavior & Immunity - Health · doi:10.1016/j.bbih.2021.100334 · Cited by 9

The Role of the Medial Prefrontal Cortex in Spatial Margin of Safety Calculations

Qi, S., Cross, L., Wise, T., Sui, X., O’Doherty, J. P., & Mobbs, D. (2024) · Journal of Neuroscience · doi:10.1523/jneurosci.1162-22.2024 · Cited by 9

The diagnostic potential of resting state functional MRI: Statistical concerns

Doubovikov, E. D., & Aksenov, D. P. (2025) · NeuroImage · doi:10.1016/j.neuroimage.2025.121334 · Cited by 9

Arithmetic in the signing brain: Differences and similarities in arithmetic processing between deaf signers and hearing non‐signers

Andin, J., Elwér, Å., & Mäki‐Torkko, E. (2022) · Journal of Neuroscience Research · doi:10.1002/jnr.25138 · Cited by 8

Acute effects of the designer drugs benzylpiperazine (BZP) and trifluoromethylphenylpiperazine (TFMPP) using functional magnetic resonance imaging (fMRI) and the Stroop task—a pilot study

Curley, L. E., Kydd, R. R., Robertson, M. C., Pillai, A., McNair, N. A., Lee, H., Kirk, I. J., & Russell, B. R. (2015) · Psychopharmacology · doi:10.1007/s00213-015-3933-y · Cited by 8

Therapeutic effects of non-invasive, individualized, transcranial neuromodulation treatment for voiding dysfunction in multiple sclerosis patients: study protocol for a pilot clinical trial

Tran, K., Shi, Z., Karmonik, C., John, B. S., Rajab, H., Helekar, S. A., Boone, T. B., & Khavari, R. (2021) · Pilot and Feasibility Studies · doi:10.1186/s40814-021-00825-z · Cited by 8

Association of Working Memory With Distributed Executive Control Networks in Schizophrenia

Wylie, K. P., Harris, J. G., Ghosh, D., D, A. O. M., & Tregellas, J. R. (2019) · Journal of Neuropsychiatry · doi:10.1176/appi.neuropsych.18060131 · Cited by 9

Short Version Dental Anxiety Inventory Score May Predict the Response in the Insular Cortex to Stimuli Mimicking Dental Treatment

Yeung, A. W. K., Lee, J. C. M., Tanabe, H. C., Ng, S. K. S., Khong, P., Leung, W. K., & Goto, T. K. (2019) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2019.00204 · Cited by 7

A systematic examination of the neural correlates of subjective time perception with fMRI and tDCS

Li, W. O., Yu, C. K.-C., & Yuen, K. S. L. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119368 · Cited by 7

Neurological and psychological mechanisms of the specific and nonspecific effects of acupuncture on knee osteoarthritis: study protocol for a randomized, controlled, crossover trial

Li, J., Liu, C., Zhang, N., Yan, C.-Q., Tu, J., Wang, Y., Qi, Y., Liu, J., & Wang, X. (2020) · Trials · doi:10.1186/s13063-020-04908-9 · Cited by 7

A Unified Sparse Recovery and Inference Framework for Functional Diffuse Optical Tomography Using Random Effect Model

Lee, O., Tak, S., & Ye, J. C. (2015) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2015.2407891 · Cited by 6

Changed ACC-DMN functional connectivity after acupuncture with deqi for functional dyspepsia treatment

Sun, R., Ma, P., He, Z., Yin, T., Qu, Y., Yin, S., Liu, X., Jin, L., Zhang, T., Huang, L., et al. (2020) · 世界针灸杂志：英文版 · doi:10.1016/j.wjam.2020.10.009 · Cited by 6

Effects of mindset on hormonal responding, neural representations, subjective experience and intake

Franssen, S., Jansen, A. T. M., van den Hurk, J., Adam, T. C., Geyskens, K., Roebroeck, A. F., & Roefs, A. (2022) · Physiology & Behavior · doi:10.1016/j.physbeh.2022.113746 · Cited by 6

Setting sample size using cost efficiency in fMRI studies

Guo, Q., Hall, McKinnon, Thabane, L., Goeree, R. A., & Pullenayegum (2012) · Open Access Medical Statistics · doi:10.2147/oams.s30830 · Cited by 6

Improving effect size estimation and statistical power with multi-echo fMRI and its impact on understanding the neural systems supporting mentalizingPreprint

Lombardo, M. V., Bonnie Auyeung, B., Holt, R., Waldman, J., Ruigrok, A. N. V., Mooney, N., Bullmore, E. T., Baron‐Cohen, S., & Kundu, P. (2015) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/017350 · Cited by 6

fMRI replicability depends upon sufficient individual-level dataPreprint

Nee, D. E. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/352633 · Cited by 8

Neural correlates of immediate versus delayed extinction when simultaneously varying the time of the test in humans

Kampa, M., Hermann, A., Stark, R. M., & Klucken, T. (2023) · Cerebral Cortex · doi:10.1093/cercor/bhad205 · Cited by 5

Advances in longitudinal MRI diagnostic tests

Hernández-García, L., & Buschkuehl, M. (2012) · Expert Opinion on Medical Diagnostics · doi:10.1517/17530059.2012.686995 · Cited by 5

Accuracy, reliability, validity and limitations of functional and structural magnetic resonance imaging data

Seixas, D., & Lima, D. (2011) · Cortex · doi:10.1016/j.cortex.2011.04.023 · Cited by 5

Introducing Alternative-Based Thresholding for Defining Functional Regions of Interest in fMRI

Degryse, J., Seurinck, R., Durnez, J., González-Castillo, J., Bandettini, P. A., & Moerkerke, B. (2017) · Frontiers in Neuroscience · doi:10.3389/fnins.2017.00222 · Cited by 6

Elucidating the neurobiology of cyberbullying using functional Magnetic Resonance Imaging (fMRI): A hypothesis

McLoughlin, L. T., Shan, Z., Broadhouse, K. M., Lagopoulos, J., Winks, N., & Hermens, D. F. (2019) · Aggression and Violent Behavior · doi:10.1016/j.avb.2019.101360 · Cited by 5

Improving ACL Reconstruction Outcomes

Wilk, K. E., Spindler, K. P., McCarty, E. C., Grooms, D. R., & Silbernagel, K. G. (2017) · Journal of Orthopaedic and Sports Physical Therapy · doi:10.2519/jospt.webinars.2017.0404 · Cited by 5

Neural correlates of effort-based valuation with prospective choicesPreprint

Aridan, N., Malecek, N. J., Poldrack, R. A., & Schönberg, T. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/357327 · Cited by 5

Characterizing habit learning in the human brain at the individual and group levels: a multi-modal MRI studyPreprint

Gera, R., Or, M. B., Tavor, I., Roll, D., Cockburn, J., Barak, S., Tricomi, E. M., O’Doherty, J. P., & Schönberg, T. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.12.12.520188 · Cited by 5

Effect of Repetitive Transcranial Magnetic Stimulation on the Symptoms and Brain Imaging in Patients with Fibromyalgia Syndrome: A Randomized Controlled Pilot Trial

Ackermann, L., Zeller, D., Odorfer, T., Homola, G. A., Kampf, T., Pham, M., Aster, H.-C., & Sommer, C. (2025) · Pain and Therapy · doi:10.1007/s40122-025-00770-2 · Cited by 5

Sex differences in central salt sensing in the human brain

Romberger, N. T., Stock, J. M., Nuckols, V. R., McMillan, R. K., Wenner, M. M., Farquhar, W. B., & Burciu, R. G. (2025) · American Journal of Physiology-Regulatory, Integrative and Comparative Physiology · doi:10.1152/ajpregu.00211.2025 · Cited by 4

Comprehensive Evaluation of Healthy Volunteers Using Multi-Modality Brain Injury Assessments: An Exploratory, Observational Study

Weaver, L. K., Wilson, S. H., Lindblad, A. S., Churchill, S. K., Deru, K., Price, R. C., Williams, C. S., Orrison, W. W., Patel, J. B., Walker, J. M., et al. (2018) · Frontiers in Neurology · doi:10.3389/fneur.2018.01030 · Cited by 4

POBE: A Computer Program for Optimal Design of Multi-Subject Blocked fMRI Experiments

Maus, B., & van Breukelen, G. (2014) · Journal of Statistical Software · doi:10.18637/jss.v056.i09 · Cited by 4

The cerebral mechanism of the specific and nonspecific effects of acupuncture based on knee osteoarthritis: study protocol for a randomized controlled trial

Zhang, N., Li, J., Yan, C.-Q., Wang, X., Lin, L., Tu, J., Qi, Y., Liu, J., Liu, C., & Wang, Y. (2020) · Trials · doi:10.1186/s13063-020-04518-5 · Cited by 4

Differences in functional brain organization during gesture recognition between autistic and neurotypical individuals

Trujillo, J. P., Özyürek, A., Kan, C. C., Simanova, I., & Harold Bekkering, A. (2022) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsac026 · Cited by 4

Impaired Inter-Hemispheric Functional Connectivity during Resting State in Female Patients with Migraine

Zhang, Y., Liu, N., Wang, Z., Liu, J., Ren, M., Hong, Y., Luo, X., Liu, H., Huo, J., & Wang, Z. (2022) · Brain Sciences · doi:10.3390/brainsci12111505 · Cited by 4

Two-point discrimination responses in children with idiopathic toe walking: A feasibility fMRI study

Donne, J. H., Farrell, M. J., Kolic, J., Powell, J. A., Fahey, M. C., & Williams, C. (2022) · Science Progress · doi:10.1177/00368504221132141 · Cited by 4

Permutation-based group sequential analyses for cognitive neuroscience

Veillette, J. P., Ho, L., & Nusbaum, H. C. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.120232 · Cited by 4

Penalized Likelihood Phenotyping: Unifying Voxelwise Analyses and Multi-Voxel Pattern Analyses in Neuroimaging

Adluru, N., Hanlon, B. M., Antoine Lutz, A., Lainhart, J. E., Alexander, A. L., & Davidson, R. J. (2013) · Neuroinformatics · doi:10.1007/s12021-012-9175-9 · Cited by 4

Power, positive predictive value, and sample size calculations for random field theory-based fMRI inferencePreprint

Ostwald, D., Schneider, S., Bruckner, R., & Horváth, L. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/613331 · Cited by 5

Functional Specificity and Sex Differences in the Neural Circuits Supporting the Inhibition of Automatic ImitationPreprint

Darda, K. M., Butler, E. E., & Ramsey, R. (2018) · PsyArXiv (OSF Preprints) · doi:10.31234/osf.io/rvh56 · Cited by 4

Topological Cluster Statistic (TCS): Towards structural-connectivity-guided fMRI cluster enhancementPreprint

Sina Mansour, L., Seguin, C., Winkler, A. M., Noble, S., & Zalesky, A. (2022) · Research Square · doi:10.21203/rs.3.rs-2059418/v1 · Cited by 4

Exploring cognitive Landscapes: Longitudinal Dynamics of left insula gliomas using neuropsychological inquiry, fMRI, and intra-resection real time neuropsychological testing

Cargnelutti, E., Maieron, M., D’Agostini, S., Ius, T., Škrap, M., & Tomasino, B. (2024) · NeuroImage Clinical · doi:10.1016/j.nicl.2024.103689 · Cited by 3

Altered resting-state amygdala-cerebellar functional connectivity is associated with intolerance of uncertainty in patients with obsessive-compulsive disorder: A longitudinal study

Guo, Q., Zhu, R., Zhou, H., Wang, D., & Zhang, X. (2025) · Journal of Anxiety Disorders · doi:10.1016/j.janxdis.2025.103048 · Cited by 3

Distinct neural circuits processing pleasant and unpleasant sounds: an fMRI-based approach

Aldhafeeri, F. M. (2025) · BMC Neuroscience · doi:10.1186/s12868-025-00975-3 · Cited by 3

Research Directions for Methodological Improvement of the Statistical Analysis of Electroencephalography Data Collected in NeuroIS

Frédette, M., Labonté-LeMoyne, É., Léger, P., Courtemanche, F., & Sénécal, S. (2015) · Lecture notes in information systems and organisation · doi:10.1007/978-3-319-18702-0_27 · Cited by 3

The Resting Brain Sets Support-Giving in Motion: Dorsomedial Prefrontal Cortex Activity During Momentary Rest Primes Supportive Responding

Inagaki, T. K., Brietzke, S. C., & Meyer, M. L. (2020) · Cerebral Cortex Communications · doi:10.1093/texcom/tgaa081 · Cited by 3

Arithmetic in the adult deaf signing brain

Andin, J., Elwér, Å., & Mäki‐Torkko, E. (2019) · Journal of Neuroscience Research · doi:10.1002/jnr.24569 · Cited by 3

Predicting the abnormality of brain and compute the cognitive power of human using deep learning techniques using functional magnetic resonance images

Palraj, K., & Kalaivani, V. (2021) · Soft Computing · doi:10.1007/s00500-021-06292-1 · Cited by 3

Theta Burst Transcranial Magnetic Stimulation of Fronto-Parietal Networks: Modulation by Mental State

Taylor, S. F., Lee, T. G., Jonides, J. J., Tso, I. F., & Hernández-García, L. (2020) · Journal of Psychiatry and Brain Science · doi:10.20900/jpbs.20200011 · Cited by 3

Dissecting Social Working Memory: Neural and Behavioral Evidence for Externally and Internally Oriented Components

Pan, H., Chen, Z., Xu, N., Wang, B., Hu, Y., Zhou, H., Perry, A., Kong, X., Shen, M., & Gao, Z. (2025) · Neuroscience Bulletin · doi:10.1007/s12264-025-01465-6 · Cited by 2

IMAGING BIOMARKERS IN DRUG DEVELOPMENT: CASE STUDIES

Tauscher, J. T., & Schwarz, A. J. (2011) · Cambridge University Press eBooks · doi:10.1017/cbo9780511976087.012 · Cited by 2

canning the Horizon: Future challenges for neuroimaging research. Russell A. Poldrack Chris I. Baker Joke Durnez Krzysztof J. Gorgolewski Paul M.

Poline, B., Vul, E., & Tal (2016) · Cited by 2

Improving the Eligibility of Task-Based fMRI Studies for Meta-Analysis: A Review and Reporting Recommendations

Acar, F., Maumet, C., Heuten, T., Vervoort, M., Bossier, H., Seurinck, R., & Moerkerke, B. (2023) · Neuroinformatics · doi:10.1007/s12021-023-09643-5 · Cited by 2

Neural responses to reward, threat, and emotion regulation and transition to hazardous alcohol use

Kirk‐Provencher, K. T., Sloan, M. E., Andereas, K., Erickson, C. J., Hakimi, R. H., Penner, A. E., & Gowin, J. L. (2024) · Alcohol and Alcoholism · doi:10.1093/alcalc/agae043 · Cited by 2

The Efficacy and Brain Network Mechanism of Acupuncture for Knee Osteoarthritis: A Study Protocol for Randomized Controlled Neuroimaging Trial

Sun, Y.-Y., Wang, M., Zhao, R.-H., Hao, M.-Y., Song, S., Zhou, Y., & Zhang, N. (2025) · Journal of Pain Research · doi:10.2147/jpr.s500024 · Cited by 2

Effects of Sedative Doses of Propofol, Dexmedetomidine, and Fentanyl on Memory and Pain in Healthy Young Adults: A Randomized, Controlled, Single-blind Crossover Study Using Functional Magnetic Resonance Imaging at 7 Tesla

Vogt, K. M., Simmons, M., Reddy, S. N., Burlew, A. C., Kozdron, C. N., Lavage, D. R., Wang, S., Pryor, K. O., Shafer, S. L., Ibrahim, T. S., et al. (2025) · Anesthesiology · doi:10.1097/aln.0000000000005489 · Cited by 4

Prefrontal and parieto-occipital neural signatures of evidence accumulation and response to computerised Cognitive Behavioural Therapy in depression

Queirazza, F., & Philiastides, M. G. (2025) · npj Mental Health Research · doi:10.1038/s44184-025-00165-3 · Cited by 2

Advances in Functional Neuroimaging of Psychopathology

Burklund, L. J., & Lieberman, M. D. (2011) · Philosophy, psychiatry & psychology · doi:10.1353/ppp.2011.0054 · Cited by 2

A preferential role for ventromedial prefrontal cortex in assessing “the value of the whole” in multi-attribute object evaluationPreprint

Pelletier, G., Aridan, N., Fellows, L. K., & Schönberg, T. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.09.29.319293 · Cited by 2

Simultaneous Brain, Brainstem and Spinal Cord pharmacological-fMRI reveals endogenous opioid network interactions mediating attentional analgesiaPreprint

Oliva, V., Hartley-Davies, R., Moran, R., Pickering, A. E., & Brooks, J. C. W. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.05.05.442823 · Cited by 2

Impact of carbon monoxide on neural activation during a reaction time taskPreprint

Wilson, L. A., & Herigstad, M. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.01.17.524443 · Cited by 1

Protocol for a nested case-control study: identifying neuroimaging biomarkers for the progression of subclinical depression and qi-stagnation constitution to major depressive disorder in adolescents

Wang, J., Zhang, C., Zhang, Y., Liu, Y., Zhang, J., Fang, X., Xia, W., Xie, Y., Lan, Z., Wang, J., et al. (2025) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2024.1516846 · Cited by 1

Fixel-Based White Matter Correlates of Sentence Comprehension in Post-Stroke Aphasia

Fang, D.-X., Ji, X.-T., Li, H.-Z., Xu, S., Yang, Y.-L., Zhan, J.-Y., Kong, A. P.-H., & Hu, R. (2025) · Brain Science · doi:10.3390/brainsci15101039 · Cited by 1

Angry facial expressions elicit a late attentional withdrawal

Ballotta, D., Maramotti, R., Borelli, E., Lui, F., & Pagnoni, G. (2025) · Scientific Reports · doi:10.1038/s41598-025-25609-w · Cited by 1

Power Calculations for Group fMRI Studies Accounting for Arbitrary Design and Temporal Autocorrelation

Mumford, J. A., & Nichols, T. (2017) · Figshare · doi:10.6084/m9.figshare.5630029

A power calculation guide for fMRI studies

Mumford, J. A. (2012) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nss059 · Cited by 171

Power and sample size calculations for fMRI studies based on the prevalence of active peaksPreprint

Durnez, J., Degryse, J., Moerkerke, B., Seurinck, R., Sochat, V., Poldrack, R. A., & Nichols, T. E. (2016) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/049429 · Cited by 69

Advances in fMRI data analysis.

Mumford, J. A. (2006) · Deep Blue (University of Michigan)

Estimating sample size in functional MRI (fMRI) neuroimaging studies: Statistical power analyses

Desmond, J. E., & Glover, G. H. (2002) · Journal of Neuroscience Methods · doi:10.1016/s0165-0270(02)00121-8 · Cited by 716