The effect of scan length on the reliability of resting-state fMRI connectivity estimates

Intraclass correlations: Uses in assessing rater reliability.

Shrout, P. E., & Fleiss, J. L. (1979) · Psychological Bulletin · doi:10.1037/0033-2909.86.2.420 · Cited by 24,532

Advances in functional and structural MR image analysis and implementation as FSL

Smith, S. M., Jenkinson, M., Woolrich, M. W., Beckmann, C. F., Behrens, T. E. J., Johansen-Berg, H., Bannister, P. R., De Luca, M., Drobnjak, I., Flitney, D. E., et al. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.07.051 · Cited by 13,630

Measures of the Amount of Ecologic Association Between Species

Dice, L. R. (1945) · Ecology · doi:10.2307/1932409 · Cited by 12,187

Co-Planar Stereotaxic Atlas of the Human Brain

Talairach, J., & Tournoux, P. (1988) · Medical Entomology and Zoology · Cited by 11,798

AFNI: Software for analysis and visualization of functional magnetic resonance neuroimages

Cox, R. W. (1996) · Computers and Biomedical Research · doi:10.1006/cbmr.1996.0014 · Cited by 10,913

Functional connectivity in the motor cortex of resting human brain using echo‐planar mri

Biswal, B., Zerrin Yetkin, F., Haughton, V. M., & Hyde, J. S. (1995) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910340409 · Cited by 9,812

The human brain is intrinsically organized into dynamic, anticorrelated functional networks

Fox, M. D., Snyder, A. Z., Vincent, J. L., Corbetta, M., Van Essen, D. C., & Raichle, M. E. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0504136102 · Cited by 8,553

Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm

Zhang, Y., Brady, M., & Smith, S. M. (2001) · IEEE Transactions on Medical Imaging · doi:10.1109/42.906424 · Cited by 7,628

Co-planar stereotaxic atlas of the human brain

Laitinen, L. (1989) · Clinical Neurology and Neurosurgery · doi:10.1016/0303-8467(89)90128-5 · Cited by 7,565

Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion

Power, J. D., Barnes, K. A., Snyder, A. Z., Schlaggar, B. L., & Petersen, S. E. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.10.018 · Cited by 7,429

Alzheimer’s Pathology Is Associated with Dedifferentiation of Intrinsic Functional Memory Networks in Aging

Cassady, K. E., Adams, J. N., Chen, X., Maaß, A., Harrison, T. M., Landau, S. M., Baker, S. L., & Jagust, W. J. (2021) · Cerebral Cortex · doi:10.1093/cercor/bhab122 · Cited by 46

Connectome-Based Prediction of Optimal Weight Loss Six Months After Bariatric Surgery

Zhang, W., Ji, G., Manza, P., Li, G., Hu, Y., Wang, J., Lv, G., He, Y., von Deneen, K. M., Han, Y., et al. (2020) · Cerebral Cortex · doi:10.1093/cercor/bhaa374 · Cited by 40

Multimodal brain connectome-based prediction of suicide risk in people with late-life depression

Gao, M., Wong, N. M. L., Lin, C., Huang, C., Liu, H., Toh, C., Wu, C. W., Tsai, Y., Lee, S.-H., & Lee, T. M. C. (2023) · Nature Mental Health · doi:10.1038/s44220-022-00007-7 · Cited by 43

The effect of lysergic acid diethylamide (LSD) on whole-brain functional and effective connectivity

Bedford, P., Hauke, D. J., Wang, Z., Röth, V., Nagy-Huber, M., Holze, F., Ley, L., Vizeli, P., Liechti, M. E., Borgwardt, S., et al. (2023) · Neuropsychopharmacology · doi:10.1038/s41386-023-01574-8 · Cited by 42

The YOUth cohort study: MRI protocol and test-retest reliability in adults

Buimer, E. E. L., Pas, P., Brouwer, R. M., Froeling, M., Hoogduin, H. M., Leemans, A., Luijten, P. R., van Nierop, B. J., Raemaekers, M. A. H., Schnack, H. G., et al. (2020) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2020.100816 · Cited by 38

Uses of Human MR and PET Imaging in Research of Neurodegenerative Brain Diseases

Schwarz, C. G. (2021) · Neurotherapeutics · doi:10.1007/s13311-021-01030-9 · Cited by 40

Sleep discrepancy is associated with alterations in the salience network in patients with insomnia disorder: An EEG-fMRI study

Li, Y., Zou, G., Shao, Y., Yao, P., Liu, J., Zhou, S., Hu, S., Xu, J., Guo, Y., Gao, J., et al. (2022) · NeuroImage Clinical · doi:10.1016/j.nicl.2022.103111 · Cited by 39

Evidence for increased parallel information transmission in human brain networks compared to macaques and male mice

Griffa, A., Mach, M., Dedelley, J., Gutierrez‐Barragan, D., Gozzi, A., Allali, G., Grandjean, J., Ville, D. V. D., & Amico, E. (2023) · Nature Communications · doi:10.1038/s41467-023-43971-z · Cited by 50

Increased connectivity between sensorimotor and attentional areas in Parkinson’s disease

Onu, M., Badea, L., Roceanu, A. M., Tivarus, M. E., & Bajenaru, O. A. (2015) · Neuroradiology · doi:10.1007/s00234-015-1556-y · Cited by 40

Temporal Changes in Local Functional Connectivity Density Reflect the Temporal Variability of the Amplitude of Low Frequency Fluctuations in Gray Matter

Tomasi, D. G., Kojori, E. S., & Volkow, N. D. (2016) · PLoS ONE · doi:10.1371/journal.pone.0154407 · Cited by 43

Applications of dynamic functional connectivity to pain and its modulation

Necka, E. A., Lee, I., Kucyi, A., Cheng, J. C., Yu, Q., & Atlas, L. Y. (2019) · PAIN Reports · doi:10.1097/pr9.0000000000000752 · Cited by 44

A systematic review of resting-state functional connectivity in obesity: Refining current neurobiological frameworks and methodological considerations moving forward

Parsons, N., Steward, T., Clohesy, R., Almgren, H., & Duehlmeyer, L. (2021) · Reviews in Endocrine and Metabolic Disorders · doi:10.1007/s11154-021-09665-x · Cited by 42

Frequency-specific network topologies in the resting human brain

Sasai, S., Homae, F., Watanabe, H., Sasaki, A. T., Tanabe, H. C., Sadato, N., & Taga, G. (2014) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2014.01022 · Cited by 40

Effects of dexamphetamine-induced dopamine release on resting-state network connectivity in recreational amphetamine users and healthy controls

Schrantee, A., Ferguson, B., Stoffers, D., Booij, J., Rombouts, S. A. R. B., & Reneman, L. (2015) · Brain Imaging and Behavior · doi:10.1007/s11682-015-9419-z · Cited by 41

Oxytocin Affects the Connectivity of the Precuneus and the Amygdala: A Randomized, Double-Blinded, Placebo-Controlled Neuroimaging Trial

Kumar, J., Vӧllm, B., & Palaniyappan, L. K. (2015) · The International Journal of Neuropsychopharmacology · doi:10.1093/ijnp/pyu051 · Cited by 40

Improved estimation of subject-level functional connectivity using full and partial correlation with empirical Bayes shrinkage

Mejia, A. F., Nebel, M. B., Barber, A. D., Choe, A. S., Pekar, J. J., Caffo, B. S., & Lindquist, M. A. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.01.029 · Cited by 39

Advantages of short repetition time resting-state functional MRI enabled by simultaneous multi-slice imaging

Jahanian, H., Holdsworth, S. J., Christen, T., Wu, H., Zhu, K., Kerr, A. B., Middione, M. J., Dougherty, R. F., Moseley, M. E., & Zaharchuk, G. (2018) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2018.09.033 · Cited by 39

Increased functional segregation of brain network associated with symptomatology and sustained attention in chronic post-traumatic stress disorder

Zhu, H., Li, Y., Yuan, M., Ren, Z., Yuan, C., Meng, Y., Wang, J., Deng, W., Qiu, C., Huang, X., et al. (2019) · Journal of Affective Disorders · doi:10.1016/j.jad.2019.01.012 · Cited by 37

Psychophysiological Interactions in a Visual Checkerboard Task: Reproducibility, Reliability, and the Effects of Deconvolution

Di, X., & Biswal, B. B. (2017) · Frontiers in Neuroscience · doi:10.3389/fnins.2017.00573 · Cited by 38

MDMA-induced changes in within-network connectivity contradict the specificity of these alterations for the effects of serotonergic hallucinogens

Müller, F., Holze, F., Dolder, P. C., Ley, L., Vizeli, P., Soltermann, A., Liechti, M. E., & Borgwardt, S. (2020) · Neuropsychopharmacology · doi:10.1038/s41386-020-00906-2 · Cited by 39

Individualized precision targeting of dorsal attention and default mode networks with rTMS in traumatic brain injury-associated depression

Siddiqi, S., Kandala, S., Hacker, C. D., Trapp, N. T., Leuthardt, E. C., Carter, A. R., & Brody, D. L. (2023) · Scientific Reports · doi:10.1038/s41598-022-21905-x · Cited by 38

Atomoxetine Treatment Strengthens an Anti-Correlated Relationship between Functional Brain Networks in Medication-Naïve Adults with Attention-Deficit Hyperactivity Disorder: A Randomized Double-Blind Placebo-Controlled Clinical Trial

Lin, H.-Y., & Gau, S. S.-F. (2016) · International Journal of Neuropsychopharmacology · doi:10.1093/ijnp/pyv094 · Cited by 37

Estimates of locus coeruleus function with functional magnetic resonance imaging are influenced by localization approaches and the use of multi-echo data

Turker, H. B., Riley, E., Luh, W., Colcombe, S. J., & Swallow, K. M. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118047 · Cited by 42

Mapping individual differences across brain network structure to function and behavior with connectome embedding

Levakov, G., Faskowitz, J., Avidan, G., & Sporns, O. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118469 · Cited by 41

Functional connectivity using high density EEG shows competitive reliability and agreement across test/retest sessions

Rolle, C. E., Narayan, M., Wu, W., Toll, R. T., Johnson, N. D., Caudle, T., Yan, M., El-Said, D., Watts, M., Eisenberg, M. L., et al. (2021) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2021.109424 · Cited by 37

Functional connectivity subtypes associate robustly with ASD diagnosis

Urchs, S. G., Tam, A., Orban, P., Moreau, C., Benhajali, Y., Nguyen, H. D., Evans, A. C., & Bellec, P. (2022) · eLife · doi:10.7554/elife.56257 · Cited by 37

Resting state functional connectivity in the default mode network: Relationships between cannabis use, gender, and cognition in adolescents and young adults

Ritchay, M. M., Huggins, A. A., Wallace, A. L., Larson, C. L., & Lisdahl, K. M. (2021) · NeuroImage Clinical · doi:10.1016/j.nicl.2021.102664 · Cited by 36

Personalizing repetitive transcranial magnetic stimulation for precision depression treatment based on functional brain network controllability and optimal control analysis

Fang, F. Z., Godlewska, B. R., Cho, R. Y., Savitz, S. I., Selvaraj, S., & Zhang, Y. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119465 · Cited by 37

The “Hub Disruption Index,” a Reliable Index Sensitive to the Brain Networks Reorganization. A Study of the Contralesional Hemisphere in Stroke

Termenón, M., Achard, S., Jaillard, A. S., & Delon‐Martin, C. (2016) · Frontiers in Computational Neuroscience · doi:10.3389/fncom.2016.00084 · Cited by 38

How restful is it with all that noise? Comparison of Interleaved silent steady state (ISSS) and conventional imaging in resting-state fMRI

Andoh, J., Ferreira, M., Leppert, I. R., Matsushita, R., Pike, G. B., & Zatorre, R. J. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.11.065 · Cited by 36

Sample heterogeneity in unipolar depression as assessed by functional connectivity analyses is dominated by general disease effects

Feder, S. C., Sundermann, B., Wersching, H., Teuber, A., Kugel, H., Teismann, H., Heindel, W. L., Berger, K., & Pfleiderer, B. (2017) · Journal of Affective Disorders · doi:10.1016/j.jad.2017.06.055 · Cited by 38

Differential associations of combined vs. isolated cannabis and nicotine on brain resting state networks

Filbey, F. M., Gohel, S., Prashad, S., & Biswal, B. B. (2018) · Brain Structure and Function · doi:10.1007/s00429-018-1690-5 · Cited by 35

Functional disruption in prefrontal-striatal network in obsessive-compulsive disorder

Sha, Z., Versace, A., Edmiston, E. K., Fournier, J. C. J., Graur, S., Greenberg, T., Santos, J. P. L., Chase, H. W., Stiffler, R. S., Bonar, L. K., et al. (2020) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2020.111081 · Cited by 41

Evaluating the evidence for a neuroimaging subtype of posttraumatic stress disorder

Esterman, M. S., Stumps, A. D., Jagger-Rickels, A. C., Rothlein, D., Degutis, J. M., Fortenbaugh, F. C., Romer, A. L., Milberg, W., Marx, B. P., & McGlinchey, R. E. (2020) · Science Translational Medicine · doi:10.1126/scitranslmed.aaz9343 · Cited by 37

Investigating functional brain network integrity using a traditional and novel categorical scheme for neurodevelopmental disorders

Dajani, D. R., Burrows, C. A., Odriozola, P., Baez, A., Nebel, M. B., Mostofsky, S. H., & Uddin, L. Q. (2019) · NeuroImage: Clinical · doi:10.1016/j.nicl.2019.101678 · Cited by 33

Profiling intra- and inter-individual differences in brain development across early adolescence

Bottenhorn, K. L., Cardenas‐Iniguez, C., Mills, K. L., Laird, A. R., & Herting, M. M. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.120287 · Cited by 40

Resting-state test–retest reliability of a priori defined canonical networks over different preprocessing steps

Varikuti, D. P., Hoffstaedter, F., Genon, S., Schwender, H. R., Reid, A., & Eickhoff, S. B. (2016) · Brain Structure and Function · doi:10.1007/s00429-016-1286-x · Cited by 36

A practical protocol for measurements of spinal cord functional connectivity

Barry, R. L., Conrad, B. N., Smith, S. A., & Gore, J. C. (2018) · Scientific Reports · doi:10.1038/s41598-018-34841-6 · Cited by 35

Improving the Assessment of Breath-Holding Induced Cerebral Vascular Reactivity Using a Multiband Multi-echo ASL/BOLD Sequence

Cohen, A. D., & Wang, Y. (2019) · Scientific Reports · doi:10.1038/s41598-019-41199-w · Cited by 35

Sex-specific effects of cigarette smoking on caudate and amygdala volume and resting-state functional connectivity

Lin, F., Han, X., Wang, Y., Ding, W., Sun, Y., Zhou, Y., & Lei, H. C. (2020) · Brain Imaging and Behavior · doi:10.1007/s11682-019-00227-z · Cited by 34

Imaging Mechanisms of Disease Progression in Multiple Sclerosis: Beyond Brain Atrophy

Bagnato, F. R., Gauthier, S. A., Laule, C., Moore, G. R. W., Bove, R. M., Cai, Z., Cohen‐Adad, J., Harrison, D. M., Klawiter, E. C., Morrow, S. A., et al. (2020) · Journal of Neuroimaging · doi:10.1111/jon.12700 · Cited by 37

Minimal specifications for non-human primate MRI: Challenges in standardizing and harmonizing data collection

Autio, J. A., Zhu, Q., Li, X., Glasser, M. F., Schwiedrzik, C. M., Fair, D. A., Zimmermann, J., Yacoub, E. S., Menon, R. S., Essen, D. C. V., et al. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118082 · Cited by 39

Maternal parenting behavior and functional connectivity development in children: A longitudinal fMRI study

Pozzi, E., Vijayakumar, N., Byrne, M. L., Bray, K. O., Seal, M. L., Richmond, S., Zalesky, A., & Whittle, S. (2021) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2021.100946 · Cited by 39

Test-Retest Reliability of Diffusion Measures Extracted Along White Matter Language Fiber Bundles Using HARDI-Based Tractography

Boukadi, M., Marcotte, K., Bedetti, C., Houde, J., Désautels, A., Deslauriers‐Gauthier, S., Chapleau, M., Boré, A., Descoteaux, M., & Brambati, S. M. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2018.01055 · Cited by 34

Ischemic Stroke in Pontine and Corona Radiata: Location Specific Impairment of Neural Network Investigated With Resting State fMRI

Jiang, C., Yi, L., Cai, S., & Zhang, L. (2019) · Frontiers in Neurology · doi:10.3389/fneur.2019.00575 · Cited by 35

Measurement reliability for individual differences in multilayer network dynamics: Cautions and considerations

Yang, Z., Telesford, Q. K., Franco, A. R., Lim, R. W.-S., Gu, S., Xu, T., Ai, L., Castellanos, F. X., Yan, C., Colcombe, S. J., et al. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117489 · Cited by 35

Altered Functional Connectivity of the Salience Network in Problematic Smartphone Users

Ahn, J., Lee, D., Namkoong, K., & Jung, Y. (2021) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2021.636730 · Cited by 34

Reliability, Convergent Validity and Time Invariance of Default Mode Network Deviations in Early Adult Major Depressive Disorder

Bessette, K. L., Jenkins, L. M., Skerrett, K. A., Gowins, J. R., DelDonno, S. R., Zubieta, J., McInnis, M. G., Jacobs, R. H., Ajilore, O., & Langenecker, S. A. (2018) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2018.00244 · Cited by 33

Short-Term Head-Out Whole-Body Cold-Water Immersion Facilitates Positive Affect and Increases Interaction between Large-Scale Brain Networks

Yankouskaya, A., Williamson, R., Stacey, C., Totman, J. J., & Massey, H. C. (2023) · Biology · doi:10.3390/biology12020211 · Cited by 44

Dynamic Functional Network Connectivity in Schizophrenia with Magnetoencephalography and Functional Magnetic Resonance Imaging: Do Different Timescales Tell a Different Story?

Sanfratello, L., Houck, J. M., & Calhoun, V. D. (2019) · Brain Connectivity · doi:10.1089/brain.2018.0608 · Cited by 34

Optimizing differential identifiability improves connectome predictive modeling of cognitive deficits from functional connectivity in Alzheimer's disease

Svaldi, D. O., Goñi, J., Abbas, K., Amico, E., Clark, D. G., Muralidharan, C., Džemidžić, M., West, J. D., Risacher, S. L., Saykin, A. J., et al. (2021) · Human Brain Mapping · doi:10.1002/hbm.25448 · Cited by 35

Disrupted prefrontal functional connectivity during post-stress adaption in high ruminators

Rosenbaum, D., Hilsendegen, P., Thomas, M., Haeussinger, F. B., Nuerk, H., Fallgatter, A. J., Nieratschker, V., Ehlis, A., & Metzger, F. G. (2018) · Scientific Reports · doi:10.1038/s41598-018-33777-1 · Cited by 32

Reliability modelling of resting-state functional connectivity

Teeuw, J., Pol, H. E. H., Boomsma, D. I., & Brouwer, R. M. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.117842 · Cited by 33

Individual Uniqueness in the Neonatal Functional Connectome

Wang, Q., Xu, Y., Zhao, T., Xu, Z., Yong He, A., & Liao, X. (2021) · Cerebral Cortex · doi:10.1093/cercor/bhab041 · Cited by 34

Test-retest reliability of pain-related functional brain connectivity compared with pain self-report

Letzen, J. E., Boissoneault, J., Sevel, L. S., & Robinson, M. E. (2015) · Pain · doi:10.1097/j.pain.0000000000000356 · Cited by 31

Reporting of Resting-State Functional Magnetic Resonance Imaging Preprocessing Methodologies

Waheed, S. H., Mirbagheri, S., Agarwal, S., Kamali, A., Yahyavi‐Firouz‐Abadi, N., Chaudhry, A. A., DiGianvittorio, M., Gujar, S. K., Pillai, J. J., & Sair, H. I. (2016) · Brain Connectivity · doi:10.1089/brain.2016.0446 · Cited by 31

Brain alterations in low-frequency fluctuations across multiple bands in obsessive compulsive disorder

Giménez, M., Guinea-Izquierdo, A., Villalta‐Gil, V., Martínez‐Zalacaín, I., Segalàs, C., Subirà, M., Real, E., Pujol, J., Harrison, B. J., Haro, J. M., et al. (2016) · Brain Imaging and Behavior · doi:10.1007/s11682-016-9601-y · Cited by 32

Default mode network anatomy and function is linked to pediatric concussion recovery

Iyer, K. K., Zalesky, A., Barlow, K. M., & Cocchi, L. (2019) · Annals of Clinical and Translational Neurology · doi:10.1002/acn3.50951 · Cited by 31

Associations between personality and whole‐brain functional connectivity at rest: Evidence across the adult lifespan

Simon, S. S., Varangis, E. M. L., & Stern, Y. (2020) · Brain and Behavior · doi:10.1002/brb3.1515 · Cited by 31

Prefrontal-amygdala connectivity in trait anxiety and generalized anxiety disorder: Testing the boundaries between healthy and pathological worries

Casteràs, D. P., Fullana, M. A., Tinoco, D. H., Martínez‐Zalacaín, I., Pujol, J., Vidal, D. P., Soriano‐Mas, C., Harrison, B. J., Via, E., & Cardoner, N. (2020) · Journal of Affective Disorders · doi:10.1016/j.jad.2020.02.029 · Cited by 34

Moving beyond the ‘CAP’ of the Iceberg: Intrinsic connectivity networks in fMRI are continuously engaging and overlapping

Iraji, A., Faghiri, A., Fu, Z., Kochunov, P. V., Adhikari, B. M., Belger, A., Ford, J. M., McEwen, S. C., Mathalon, D. H., Pearlson, G. D., et al. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119013 · Cited by 31

Future directions for cognitive neuroscience in psychiatry: recommendations for biomarker design based on recent test re-test reliability work

Blair, J., Mathur, A., Haines, N., & Bajaj, S. (2022) · Current Opinion in Behavioral Sciences · doi:10.1016/j.cobeha.2022.101102 · Cited by 31

Socioeconomic resources are associated with distributed alterations of the brain’s intrinsic functional architecture in youth

Sripada, C., Gard, A. M., Angstadt, M., Taxali, A., Greathouse, T., McCurry, K. L., Hyde, L. W., Weigard, A. S., Walczyk, P., & Heitzeg, M. M. (2022) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2022.101164 · Cited by 33

Puberty contributes to adolescent development of fronto-striatal functional connectivity supporting inhibitory control

Ojha, A., Parr, A. C., Foran, W., Calabro, F. J., & Luna, B. (2022) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2022.101183 · Cited by 30

Diagnostic classification of unipolar depression based on resting-state functional connectivity MRI: effects of generalization to a diverse sample

Sundermann, B., Feder, S. C., Wersching, H., Teuber, A., Schwindt, W., Kugel, H., Heindel, W. L., Arolt, V., Berger, K., & Pfleiderer, B. (2016) · Journal of Neural Transmission · doi:10.1007/s00702-016-1673-8 · Cited by 34

Impact of automated ICA-based denoising of fMRI data in acute stroke patients

Carone, D., Licenik, R., Suri, S., Griffanti, L., Filippini, N., & Kennedy, J. M. (2017) · NeuroImage Clinical · doi:10.1016/j.nicl.2017.06.033 · Cited by 32

Regularized partial correlation provides reliable functional connectivity estimates while correcting for widespread confounding

Peterson, K. L., Sánchez-Romero, R., Mill, R. D., & Cole, M. W. (2025) · Imaging Neuroscience · doi:10.1162/imag.a.162 · Cited by 30

Cholinergic neuromodulation of inhibitory interneurons facilitates functional integration in whole-brain models

Coronel‐Oliveros, C., Cofré, R., & Orio, P. (2021) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1008737 · Cited by 29

Repetitive Transcranial Magnetic Stimulation for Adolescent Major Depressive Disorder: A Focus on Neurodevelopment

Oberman, L. M., Hynd, M., Nielson, D. M., Towbin, K. E., Lisanby, S. H., & Stringaris, A. K. (2021) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2021.642847 · Cited by 30

Association of acute depressive symptoms and functional connectivity of emotional processing regions following sport-related concussion

McCuddy, W. T., España, L. Y., Nelson, L. D., Birn, R. M., Mayer, A. R., & Meier, T. B. (2018) · NeuroImage Clinical · doi:10.1016/j.nicl.2018.05.011 · Cited by 30

Extended‐amygdala intrinsic functional connectivity networks: A population study

Berry, S. C., Wise, R. G., Lawrence, A. D., & Lancaster, T. M. (2020) · Human Brain Mapping · doi:10.1002/hbm.25314 · Cited by 29

Review: The use of functional magnetic resonance imaging (fMRI) in clinical trials and experimental research studies for depression

Kotoula, V., Evans, J. W., Punturieri, C., & Zarate, C. A. (2023) · Frontiers in Neuroimaging · doi:10.3389/fnimg.2023.1110258 · Cited by 39

Neural Correlates of Cognitive-Attentional Syndrome: An fMRI Study on Repetitive Negative Thinking Induction and Resting State Functional Connectivity

Kowalski, J., Wypych, M., Marchewka, A., & Dragan, M. (2019) · Frontiers in Psychology · doi:10.3389/fpsyg.2019.00648 · Cited by 30

Reliable local dynamics in the brain across sessions are revealed by whole‐brain modeling of resting state activity

Donnelly-Kehoe, P. A., Saenger, V. M., Lisofsky, N., Kühn, S., Kringelbach, M. L., Schwarzbach, J. V., Lindenberger, U., & Deco, G. (2019) · Human Brain Mapping · doi:10.1002/hbm.24572 · Cited by 30

Reliability of task-specific neuronal activation assessed with functional PET, ASL and BOLD imaging

Rischka, L., Godbersen, G. M., Pichler, V., Michenthaler, P., Klug, S., Klöbl, M., Ritter, V., Wadsak, W., Hacker, M., Kasper, S. F., et al. (2021) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1177/0271678x211020589 · Cited by 29

Intra-session test-retest reliability of functional connectivity in infants

Wang, Y., Hinds, W. A., Duarte, C. S., Lee, S., Monk, C. E., Wall, M. M., CANINO, G. J., Milani, A. C. C., Jackowski, A. P., Mamin, M. G., et al. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118284 · Cited by 29

A longitudinal human phantom reliability study of multi-center T1-weighted, DTI, and resting state fMRI data

Hawco, C. S., Viviano, J. D., Chavez, S., Dickie, E. W., Calarco, N., Kochunov, P. V., Árgyelán, M., Turner, J. A., Malhotra, A. K., Buchanan, R. W., et al. (2018) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2018.06.004 · Cited by 29

Alterations in resting-state functional connectivity in patients with Crohn’s disease in remission

Hou, J., Mohanty, R., Nair, V. A., Dodd, K. C., Beniwal-Patel, P. M., Saha, S., & Prabhakaran, V. (2019) · Scientific Reports · doi:10.1038/s41598-019-43878-0 · Cited by 29

On the Reliability of Individual Brain Activity Networks

Cassidy, B., Bowman, F. D., Rae, C. D., & Solo, V. (2017) · IEEE Transactions on Medical Imaging · doi:10.1109/tmi.2017.2774364 · Cited by 26

The Profiles of Non-stationarity and Non-linearity in the Time Series of Resting-State Brain Networks

Guan, S., Jiang, R., Bian, H., Yuan, J., Xu, P., Meng, C., & Biswal, B. B. (2020) · Frontiers in Neuroscience · doi:10.3389/fnins.2020.00493 · Cited by 27

Low-motion fMRI data can be obtained in pediatric participants undergoing a 60-minute scan protocol

Horien, C. L., Fontenelle, S., Joseph, K., Powell, N., Nutor, C., Fortes, D., Butler, M., Powell, K. K., Macris, D. M., Lee, K., et al. (2020) · Scientific Reports · doi:10.1038/s41598-020-78885-z · Cited by 31

Changes in patterns of age-related network connectivity are associated with risk for schizophrenia

Passiatore, R., Antonucci, L. A., DeRamus, T. P., Fazio, L., Stolfa, G., Sportelli, L., Kikidis, G. C., Blasi, G., Chen, Q., Dukart, J., et al. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2221533120 · Cited by 27

Impact of digital screen media activity on functional brain organization in late childhood: Evidence from the ABCD study

Miller, J. W., Mills, K. L., Vuorre, M., Orben, A. C., & Przybylski, A. K. (2023) · Cortex · doi:10.1016/j.cortex.2023.09.009 · Cited by 37

Frontal corticostriatal functional connectivity reveals task positive and negative network dysregulation in relation to ADHD, sex, and inhibitory control

Nikolaidis, A., He, X., Pekar, J., Rosch, K., & Mostofsky, S. H. (2022) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2022.101101 · Cited by 28

The promise of precision functional mapping for neuroimaging in psychiatry

Demeter, D. V., & Greene, D. J. (2024) · Neuropsychopharmacology · doi:10.1038/s41386-024-01941-z · Cited by 29

Comparison of continuously acquired resting state and extracted analogues from active tasks

Ganger, S., Hahn, A., Küblböck, M., Kranz, G. S., Spies, M., Vanicek, T., Seiger, R., Sladky, R., Windischberger, C., Kasper, S. F., et al. (2015) · Human Brain Mapping · doi:10.1002/hbm.22897 · Cited by 25

Test-retest reliability of regression dynamic causal modeling

Frässle, S., & Stephan, K. E. (2021) · Network Neuroscience · doi:10.1162/netn_a_00215 · Cited by 27

Connectome‐based predictive modelling of cognitive reserve using task‐based functional connectivity

Boyle, R. T., Connaughton, M., McGlinchey, E., Knight, S. P., Looze, C. D., Carey, D., Stern, Y., Robertson, I. H., Kenny, R. A., & Whelan, R. (2022) · European Journal of Neuroscience · doi:10.1111/ejn.15896 · Cited by 27

Applications of Resting State Functional MR Imaging to Traumatic Brain Injury

O’Neill, T. J., Davenport, E. M., Murugesan, G. K., Montillo, A., & Maldjian, J. A. (2017) · Neuroimaging Clinics of North America · doi:10.1016/j.nic.2017.06.006 · Cited by 27

Effect of scanning duration and sample size on reliability in resting state fMRI dynamic causal modeling analysis

Ma, L., Braun, S. E., Steinberg, J. L., Bjork, J. M., Martin, C. E., Keen, L., & Moeller, F. G. (2024) · NeuroImage · doi:10.1016/j.neuroimage.2024.120604 · Cited by 33

Leveraging ultra-high field (7T) MRI in psychiatric research

Calabro, F. J., Parr, A. C., Sydnor, V. J., Hetherington, H. P., Prasad, K. M. R., Ibrahim, T. S., Sarpal, D. K., Famalette, A., Verma, P., & Luna, B. (2024) · Neuropsychopharmacology · doi:10.1038/s41386-024-01980-6 · Cited by 29

Effect of Acupuncture Stimulation of Hegu (LI4) and Taichong (LR3) on the Resting-State Networks in Alzheimer’s Disease: Beyond the Default Mode Network

Ji, S., Zhang, H., Qin, W., Liu, M., Zheng, W., Han, Y., Song, H., Li, K., Lu, J., & Wang, Z. (2021) · Neural Plasticity · doi:10.1155/2021/8876873 · Cited by 26

Reliability and clinical utility of spatially constrained estimates of intrinsic functional networks from very short fMRI scans

Duda, M., Iraji, A., Ford, J. M., Lim, K. O., Mathalon, D. H., Mueller, B. A., Potkin, S. G., Preda, A., van Erp, T. G. M., & Calhoun, V. D. (2023) · Human Brain Mapping · doi:10.1002/hbm.26234 · Cited by 26

Neighborhood poverty during childhood prospectively predicts adolescent functional brain network architecture

Michael, C., Tillem, S., Sripada, C., Burt, S. A., Klump, K. L., & Hyde, L. W. (2023) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2023.101316 · Cited by 30

Using Edge Voxel Information to Improve Motion Regression for rs-fMRI Connectivity Studies

Patriat, R., Molloy, E. K., & Birn, R. M. (2015) · Brain Connectivity · doi:10.1089/brain.2014.0321 · Cited by 26

Gender transition affects neural correlates of empathy: A resting state functional connectivity study with ultra high-field 7T MR imaging

Spies, M., Hahn, A., Kranz, G. S., Sladky, R., Kaufmann, U., Hummer, A., Ganger, S., Kraus, C., Winkler, D., Seiger, R., et al. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.05.060 · Cited by 28

Replication in Imaging Genetics: The Case of Threat-Related Amygdala Reactivity

Avinun, R., Nevo, A., Knodt, A. R., Elliott, M. L., & Hariri, A. R. (2017) · Biological Psychiatry · doi:10.1016/j.biopsych.2017.11.010 · Cited by 25

Recommended Resting-State fMRI Acquisition and Preprocessing Steps for Preoperative Mapping of Language and Motor and Visual Areas in Adult and Pediatric Patients with Brain Tumors and Epilepsy

Kumar, V. A., Lee, J., Liu, H., Allen, J. W., Filippi, C. G., Holodny, A. I., Hsu, K. A., Jain, R., McAndrews, M. P., Peck, K. K., et al. (2023) · American Journal of Neuroradiology · doi:10.3174/ajnr.a8067 · Cited by 29

Brain network disintegration during sedation is mediated by the complexity of sparsely connected regions

Pappas, I., Adapa, R., Menon, D. K., & Stamatakis, E. A. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.10.078 · Cited by 27

Test-Retest Reliability of Neural Correlates of Response Inhibition and Error Monitoring: An fMRI Study of a Stop-Signal Task

Korucuoglu, O., Harms, M. P., Astafiev, S. V., Golosheykin, S., Kennedy, J. T., Barch, D. M., & Anokhin, A. P. (2021) · Frontiers in Neuroscience · doi:10.3389/fnins.2021.624911 · Cited by 25

Test-retest reliability of resting-state fMRI functional connectivity: impact of scan length and number of participantsPreprint

Vale, B., Correia, M., & Figueiredo, P. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.03.31.715533 · Cited by 1

Effects of Scan Length and Shrinkage on Reliability of Resting-State Functional Connectivity in the Human Connectome ProjectPreprint

Mejia, A. F., Nebel, M. B., Barber, A. D., Choe, A. S., & Lindquist, M. A. (2016) · arXiv (Cornell University) · doi:10.48550/arxiv.1606.06284 · Cited by 1

Advance Access publication February 16, 2009 The Resting Brain: Unconstrained yet Reliable

Shehzad, Z., Kelly, A., Reiss, P. T., Gee, G., Gotimer, K., Uddin, L. Q., Lee, S. H., Margulies, D. S., Roy, A. K., Biswal, B. B., et al. (2016)

The Resting Brain: Unconstrained yet Reliable

Shehzad, Z. E., Kelly, C. A. M., Reiss, P. T., Gee, D. G., Gotimer, K., Uddin, L. Q., Lee, S. H., Margulies, D. S., Roy, A. K., Biswal, B. B., et al. (2009) · Cerebral Cortex · doi:10.1093/cercor/bhn256 · Cited by 948

The Effect of Choice of Metric and Scan Length on Reliability in Resting-State fMRIPreprint

Huang, Y., Reiss, P. T., Lee, S., & Ogden, R. T. (2026) · arXiv (Cornell University) · doi:10.48550/arxiv.2606.00767