Evaluation of ICA-AROMA and alternative strategies for motion artifact removal in resting state fMRI

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

Improved Optimization for the Robust and Accurate Linear Registration and Motion Correction of Brain Images

Jenkinson, M., Bannister, P., Brady, M., & Smith, S. (2002) · NeuroImage · doi:10.1006/nimg.2002.1132 · Cited by 11,888

FSL

Jenkinson, M., Beckmann, C. F., Behrens, T. E. J., Woolrich, M. W., & Smith, S. M. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.09.015 · Cited by 11,314

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

A global optimisation method for robust affine registration of brain images

Jenkinson, M., & Smith, S. M. (2001) · Medical Image Analysis · doi:10.1016/s1361-8415(01)00036-6 · Cited by 6,983

Correspondence of the brain's functional architecture during activation and rest

Smith, S. M., Fox, P. T., Miller, K. L., Glahn, D. C., Fox, P. M., Mackay, C. E., Filippini, N., Watkins, K. E., Toro, R., Laird, A. R., et al. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0905267106 · Cited by 5,150

A component based noise correction method (CompCor) for BOLD and perfusion based fMRI

Behzadi, Y., Restom, K., Liau, J., & Liu, T. T. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.04.042 · Cited by 4,502

Consistent resting-state networks across healthy subjects

Damoiseaux, J. S., Rombouts, S. A. R. B., Barkhof, F., Scheltens, P., Stam, C. J., Smith, S. M., & Beckmann, C. F. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0601417103 · Cited by 4,326

Movement‐Related effects in fMRI time‐series

Friston, K. J., Williams, S., Howard, R., Frackowiak, R. S. J., & Turner, R. (1996) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910350312 · Cited by 3,774

Methods to detect, characterize, and remove motion artifact in resting state fMRI

Power, J. D., Mitra, A., Laumann, T. O., Snyder, A. Z., Schlaggar, B. L., & Petersen, S. E. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2013.08.048 · Cited by 3,748

Reward anticipation and punishment anticipation are instantiated in the brain via opponent mechanisms

Lake, J. I., Spielberg, J. M., Infantolino, Z. P., Crocker, L. D., Yee, C. M., Heller, W., & Miller, G. A. (2019) · Psychophysiology · doi:10.1111/psyp.13381 · Cited by 21

Increased sensitivity to age-related differences in brain functional connectivity during continuous multiple object tracking compared to resting-state

Dørum, E. S., Kaufmann, T., Alnæs, D., Andreassen, O. A., Richard, G., Kolskår, K. K., Nordvik, J. E., & Westlye, L. T. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.01.048 · Cited by 20

Functional magnetic resonance brain imaging of imagined walking to study locomotor function after stroke

Boyne, P., Doren, S., Scholl, V., Staggs, E. J., Whitesel, D., Maloney, T., Awosika, O. O., D, B. M. K. M., Dunning, K. K., & Vannest, J. J. (2020) · Clinical Neurophysiology · doi:10.1016/j.clinph.2020.11.009 · Cited by 21

Mu-opioid receptor system modulates responses to vocal bonding and distress signals in humans

Sun, L., Lukkarinen, L., Putkinen, V., Karlsson, H. K., Hirvonen, J., Tiihonen, J., Lauerma, H., Scott, S. K., & Nummenmaa, L. (2022) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2021.0181 · Cited by 23

Secretin modulates appetite via brown adipose tissue-brain axis

Sun, L., Laurila, S., Lahesmaa, M., Rebelos, E., Virtanen, K. A., Schnabl, K., Klingenspor, M., Nummenmaa, L., & Nuutila, P. (2023) · European Journal of Nuclear Medicine and Molecular Imaging · doi:10.1007/s00259-023-06124-4 · Cited by 21

Organization of sensorimotor activity in anterior cruciate ligament reconstructed individuals: an fMRI conjunction analysis

Schnittjer, A. J., Kim, H., Lepley, A. S., Oñate, J. A., Criss, C. R., Simon, J. E., & Grooms, D. R. (2023) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2023.1263292 · Cited by 21

Resting State Functional Networks in Gliomas: Validation With Direct Electric Stimulation Using a New Tool for Planning Brain Resections

Moretto, M., Luciani, B. F., Zigiotto, L., Saviola, F., Tambalo, S., Cabalo, D. G., Annicchiarico, L., Venturini, M., Jovicich, J., & Sarubbo, S. (2024) · Neurosurgery · doi:10.1227/neu.0000000000003012 · Cited by 21

Pronounced Structural and Functional Damage in Early Adult Pediatric-Onset Multiple Sclerosis with No or Minimal Clinical Disability

Giorgio, A., Zhang, J., Stromillo, M. L., Rossi, F., Battaglini, M., Nichelli, L., Mortilla, M., Portaccio, E., Hakiki, B., Amato, M. P., et al. (2017) · Frontiers in Neurology · doi:10.3389/fneur.2017.00608 · Cited by 21

Preliminary analysis of resting state functional connectivity in young adults with subtypes of bipolar disorder

Thomas, S. A., Christensen, R. E., Schettini, E., Saletin, J., Ruggieri, A. L., MacPherson, H. A., Kim, K. L., & Dickstein, D. P. (2018) · Journal of Affective Disorders · doi:10.1016/j.jad.2018.12.068 · Cited by 22

Neural Correlates of Self-Reported Knee Function in Individuals After Anterior Cruciate Ligament Reconstruction

Criss, C. R., Lepley, A. S., Oñate, J. A., Simon, J. E., France, C. R., Clark, B. C., & Grooms, D. R. (2022) · Sports Health A Multidisciplinary Approach · doi:10.1177/19417381221079339 · Cited by 20

Functional connectivity of the sensorimotor cerebellum in autism: associations with sensory over-responsivity

Cakar, M. E., Okada, N. J., Cummings, K. K., Jung, J., Bookheimer, S. Y., Dapretto, M., & Green, S. A. (2024) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2024.1337921 · Cited by 24

Brain Network Architecture and Global Intelligence in Children with Focal Epilepsy

Paldino, M. J., Golriz, F., Chapieski, M. L., Zhang, W., & Chu, Z. D. (2016) · American Journal of Neuroradiology · doi:10.3174/ajnr.a4975 · Cited by 20

Mutual Information Better Quantifies Brain Network Architecture in Children with Epilepsy

Zhang, W., Muravina, V., Azencott, R., Chu, Z. D., & Paldino, M. J. (2018) · Computational and Mathematical Methods in Medicine · doi:10.1155/2018/6142898 · Cited by 24

Loss of Parietal Memory Network Integrity in Alzheimer’s Disease

Hu, Y., Du, W., Zhang, Y., Li, N., Han, Y., & Yang, Z. (2019) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2019.00067 · Cited by 20

First Trimester DEX Treatment Is Not Associated with Altered Brain Activity During Working Memory Performance in Adults

Westeinde, A. V., Zimmermann, M., Messina, V., Karlsson, L., Padilla, N., & Lajić, S. (2020) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/clinem/dgaa611 · Cited by 20

Distributed and Multifaceted Effects of Threat and Safety

Morrow, K., Murty, D. V. P. S., Kim, J., Song, S., Hu, K., & Pessoa, L. (2021) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_01807 · Cited by 18

Verbal working memory-related functional connectivity alterations in boys with attention-deficit/hyperactivity disorder and the effects of methylphenidate

Wu, Z.-M., Bralten, J., Li, A., Cao, Q., Cao, X., Sun, L., Liu, L., Yang, L., Mennes, M., Zang, Y., et al. (2017) · Journal of Psychopharmacology · doi:10.1177/0269881117715607 · Cited by 24

The Role of Cerebellum and Basal Ganglia Functional Connectivity in Altered Voluntary Movement Execution in Essential Tremor

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The cerebellum and learning of non-motor associations in individuals at clinical-high risk for psychosis

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ICA-based denoising for ASL perfusion imaging

Carone, D., Harston, G., Garrard, J., Angeli, F. D., Griffanti, L., Okell, T. W., Chappell, M. A., & Kennedy, J. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.07.002 · Cited by 19

Relationships between multiple dimensions of executive functioning and resting-state networks in adults

Roye, S., Castagna, P. J., Calamia, M. R., Vito, A. N. D., Lee, T., & Greening, S. G. (2020) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2020.107418 · Cited by 21

Association of Disinhibited Eating and Trait of Impulsivity With Insula and Amygdala Responses to Palatable Liquid Consumption

Nakamura, Y., & Koike, S. (2021) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2021.647143 · Cited by 19

Hospitalisation for COVID-19 predicts long lasting cerebrovascular impairment: A prospective observational cohort study

Tsvetanov, K. A., Spindler, L. R. B., Stamatakis, E. A., Newcombe, V., Lupson, V. C., Chatfield, D. A., Manktelow, A. E., Outtrim, J. G., Elmer, A., Kingston, N., et al. (2022) · NeuroImage Clinical · doi:10.1016/j.nicl.2022.103253 · Cited by 20

Associations between thalamocortical functional connectivity and sensory over-responsivity in infants at high likelihood for ASD

Wagner, L., Banchik, M., Okada, N. J., McDonald, N. M., Jeste, S., Bookheimer, S. Y., Green, S. A., & Dapretto, M. (2023) · Cerebral Cortex · doi:10.1093/cercor/bhad100 · Cited by 24

Behavioral and neural concordance in parent-child dyadic sleep patterns

Lee, T., Miernicki, M. E., & Telzer, E. H. (2017) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2017.06.003 · Cited by 20

Investigating the neural correlates of smoking: Feasibility and results of combining electronic cigarettes with fMRI

Wall, M. B., Mentink, A., Lyons, G., Kowalczyk, O. S., Demetriou, L., & Newbould, R. D. (2017) · Scientific Reports · doi:10.1038/s41598-017-11872-z · Cited by 19

Quantifying patterns of brain activity: Distinguishing unaffected siblings from participants with ADHD and healthy individuals

Wolfers, T., van Rooij, D., Oosterlaan, J., Heslenfeld, D. J., Hartman, C. A., Hoekstra, P. J., Beckmann, C. F., Franke, B., Buitelaar, J. K., & Marquand, A. F. (2016) · NeuroImage Clinical · doi:10.1016/j.nicl.2016.06.020 · Cited by 19

A Chinese multi-modal neuroimaging data release for increasing diversity of human brain mapping

Gao, P., Dong, H.-M., Liu, S.-M., Fan, X.-R., Jiang, C., Wang, Y., Margulies, D. S., Li, H., & Zuo, X. (2022) · Scientific Data · doi:10.1038/s41597-022-01413-3 · Cited by 24

Relationship between central autonomic effective connectivity and heart rate variability: A Resting-state fMRI dynamic causal modeling study

Ma, L., Keen, L., Steinberg, J. L., Eddie, D., Tan, A. Y., Keyser‐Marcus, L., Abbate, A., & Moeller, F. G. (2024) · NeuroImage · doi:10.1016/j.neuroimage.2024.120869 · Cited by 20

A Neuroimaging Preparation Protocol Tailored for Autism

Tziraki, M., Garg, S., Harrison, E. L., Wright, N., Hawkes, R., Akhtar, K., Green, J., & Stivaros, S. M. (2020) · Autism Research · doi:10.1002/aur.2427 · Cited by 18

The Relation Between White Matter Microstructure and Network Complexity: Implications for Processing Efficiency

McDonough, I. M., & Siegel, J. T. (2018) · Frontiers in Integrative Neuroscience · doi:10.3389/fnint.2018.00043 · Cited by 19

Functional fractionation of default mode network in first episode schizophrenia

Fan, F., Tan, Y., Wang, Z., Yang, F., Fan, H., Xiang, H., Guo, H., Hong, L. E., Tan, S., & Zuo, X. (2019) · Schizophrenia Research · doi:10.1016/j.schres.2019.05.038 · Cited by 19

Effects of aerobic versus cognitively demanding exercise interventions on brain structure and function in healthy children—Results from a cluster randomized controlled trial

Meijer, A., Königs, M., Pouwels, P. J. W., Smith, J., Visscher, C., Bosker, R., Hartman, E., & Oosterlaan, J. (2022) · Psychophysiology · doi:10.1111/psyp.14034 · Cited by 20

Decoupling of large-scale brain networks supports the consolidation of durable episodic memories

Sneve, M. H., Grydeland, H., Amlien, I. K., Langnes, E., Walhovd, K. B., & Fjell, A. M. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.05.048 · Cited by 20

Disentangling common from specific processing across tasks using task potency

Chauvin, R. J., Mennes, M., Llera, A., Buitelaar, J. K., & Beckmann, C. F. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.09.059 · Cited by 19

Cognition’s dependence on functional network integrity with age is conditional on structural network integrity

Liu, X., TYLER, L. K., Cam‐CAN, Davis, S. W., Rowe, J. B., & Tsvetanov, K. A. (2023) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2023.06.001 · Cited by 17

Neuroimaging and behavioral evidence that violent video games exert no negative effect on human empathy for pain and emotional reactivity to violence

Lengersdorff, L. L., Wagner, I. C., Mittmann, G., Sastre-Yagüe, D., Lüttig, A., Olsson, A., Petrovic, P., & Lamm, C. (2023) · eLife · doi:10.7554/elife.84951 · Cited by 10

Serotonin transporter occupancy by the SSRI citalopram predicts default-mode network connectivity

Schrantee, A., Lucassen, P. J., Booij, J., & Reneman, L. (2018) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2018.07.099 · Cited by 17

Functional connectomes linking child-parent relationships with psychological problems in adolescence

Itahashi, T., Okada, N., Ando, S., Yamasaki, S., Koshiyama, D., Morita, K., Yahata, N., Koike, S., Nishida, A., Kasai, K., et al. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117013 · Cited by 22

fMRI network correlates of predisposing risk factors for delirium: A cross-sectional study

van Montfort, S. J. T., Slooter, A. J. C., Kant, I. M. J., van de Leur, R. R., Spies, C., de Bresser, J., Witkamp, T. D., Hendrikse, J., & van Dellen, E. (2020) · NeuroImage Clinical · doi:10.1016/j.nicl.2020.102347 · Cited by 17

Resting-State Directional Connectivity and Anxiety and Depression Symptoms in Adult Cannabis Users

Ma, L., Hettema, J. M., Cousijn, J., Bjork, J. M., Steinberg, J. L., Keyser‐Marcus, L., Woisard, K., Lu, Q., Roberson‐Nay, R., Abbate, A., et al. (2020) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2020.09.015 · Cited by 17

Multimodal fusion analysis of functional, cerebrovascular and structural neuroimaging in healthy aging subjects

Liu, X., TYLER, L. K., Cam‐CAN, Rowe, J. B., & Tsvetanov, K. A. (2022) · Human Brain Mapping · doi:10.1002/hbm.26025 · Cited by 17

Temporal reliability of ultra-high field resting-state MRI for single-subject sensorimotor and language mapping

Branco, P., Seixas, D., & Castro, S. L. (2016) · NeuroImage · doi:10.1016/j.neuroimage.2016.11.029 · Cited by 17

A randomized controlled trial investigating the effect of liraglutide on self-reported liking and neural responses to food stimuli in participants with obesity

Coppin, G., Tord, D. M., Pool, E. R., Locatelli, L., Achaïbou, A., Erdemli, A., Pérez, L. L., Wuensch, L., Cereghetti, D. M., Golay, A., et al. (2023) · International Journal of Obesity · doi:10.1038/s41366-023-01370-w · Cited by 16

Impaired response inhibition during a stop-signal task in children with Tourette syndrome is related to ADHD symptoms: A functional magnetic resonance imaging study

Openneer, T. J. C., van der Meer, D., Marsman, J.-B. C., Forde, N. J., Akkermans, S. E. A., Naaijen, J., Buitelaar, J. K., Hoekstra, P. J., & Dietrich, A. (2020) · The World Journal of Biological Psychiatry · doi:10.1080/15622975.2020.1813329 · Cited by 17

Personality network neuroscience: Promises and challenges on the way toward a unifying framework of individual variability

Hilger, K., & Markett, S. A. (2021) · Network Neuroscience · doi:10.1162/netn_a_00198 · Cited by 14

Submaximal Exercise Provokes Increased Activation of the Anterior Default Mode Network During the Resting State as a Biomarker of Postexertional Malaise in Myalgic Encephalomyelitis/Chronic Fatigue Syndrome

Rayhan, R. U., & Baraniuk, J. N. (2021) · Frontiers in Neuroscience · doi:10.3389/fnins.2021.748426 · Cited by 16

Evaluating denoising strategies in resting‐state functional magnetic resonance in traumatic brain injury (EpiBioS4Rx)

Weiler, M., Casseb, R. F., de Campos, B. M., Crone, J. S., Lutkenhoff, E. S., Vespa, P. M., Monti, M. M., & for the EpiBioS4Rx Study Group (2022) · Human Brain Mapping · doi:10.1002/hbm.25979 · Cited by 16

Reprint of ‘Noise contributions to the fMRI signal: An Overview'

Liu, T. T. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.05.031 · Cited by 16

Age-Related Differences in Functional Asymmetry During Memory Retrieval Revisited: No Evidence for Contralateral Overactivation or Compensation

Roe, J. M., Dídac Vidal-piñeiro, A., Sneve, M. H., Kompus, K., Greve, D. N., Walhovd, K. B., Fjell, A. M., & Westerhausen, R. (2019) · Cerebral Cortex · doi:10.1093/cercor/bhz153 · Cited by 17

Hybrid brain model accurately predict human procrastination behavior

Chen, Z., Zhang, R., Xie, J., Liu, P., Zhang, C., Zhao, J. L., Laplante, J. P., & Feng, T. (2022) · Cognitive Neurodynamics · doi:10.1007/s11571-021-09765-z · Cited by 19

Dwelling in prolonged grief: Resting state functional connectivity during oxytocin and placebo administration

Seeley, S. H., Andrews‐Hanna, J. R., Allen, J. J. B., & O'Connor, M. (2022) · Human Brain Mapping · doi:10.1002/hbm.26071 · Cited by 14

Evaluation of noise regression techniques in resting-state fMRI studies using data of 434 older adults

Scheel, N., Keller, J. N., Binder, E. F., Vidoni, E. D., Burns, J. M., Thomas, B. P., Stowe, A. M., Hynan, L. S., Kerwin, D. R., Vongpatanasin, W., et al. (2022) · Frontiers in Neuroscience · doi:10.3389/fnins.2022.1006056 · Cited by 15

The multiverse of data preprocessing and analysis in graph-based fMRI: A systematic literature review of analytical choices fed into a decision support tool for informed analysis

Kristanto, D., Burkhardt, M., Thiel, C. M., Debener, S., Gießing, C., & Hildebrandt, A. (2024) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2024.105846 · Cited by 16

Peripherally acting anti-CGRP monoclonal antibodies attenuate cortical resting-state connectivity in migraine patients

Szabó, E., Bolo, N. R., Borsook, D., Burstein, R., & Ashina, S. (2025) · Cephalalgia · doi:10.1177/03331024241313377 · Cited by 14

Intrinsic functional connectivity in families genetically enriched for social anxiety disorder – an endophenotype study

Bas‐Hoogendam, J. M., van Steenbergen, H., Kadosh, K. C., Westenberg, P. M., & van der Wee, N. J. A. (2021) · EBioMedicine · doi:10.1016/j.ebiom.2021.103445 · Cited by 14

Connectivity networks in gambling disorder: a resting-state fMRI study

van Timmeren, T., Zhutovsky, P., van Holst, R. J., & Goudriaan, A. E. (2018) · International Gambling Studies · doi:10.1080/14459795.2018.1449884 · Cited by 17

Functional neural correlates of facial affect recognition impairment following TBI

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Recreational use of GHB is associated with alterations of resting state functional connectivity of the central executive and default mode networks

Pereira, F. R., Zhutovsky, P., McMaster, M. T. B., Polderman, N., de Vries, Y. D. A. T., van den Brink, W., & van Wingen, G. A. (2019) · Human Brain Mapping · doi:10.1002/hbm.24532 · Cited by 15

Placebo-induced pain reduction is associated with negative coupling between brain networks at rest

Wagner, I. C., Rütgen, M., Hummer, A., Windischberger, C., & Lamm, C. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117024 · Cited by 16

Benchmarking confound regression strategies for the control of motion artifact in studies of functional connectivityPreprint

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Motor performance and functional connectivity between the posterior cingulate cortex and supplementary motor cortex in bipolar and unipolar depression

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Defining the r factor for post-trauma resilience and its neural predictors

van Rooij, S. J. H., Santos, J. L., Hinojosa, C. A., Ely, T. D., Harnett, N. G., Murty, V. P., Lebois, L. A. M., Jovanović, T., House, S. L., Bruce, S. E., et al. (2024) · Nature Mental Health · doi:10.1038/s44220-024-00242-0 · Cited by 16

Clinical progression and genetic pathways in body-first and brain-first Parkinson’s disease

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The Role of Social Reward and Corticostriatal Connectivity in Substance Use

Sazhin, D., Frazier, A. M., Haynes, C. R., Johnston, C. R., Chat, I. K.-Y., Dennison, J. B., Bart, C. P., McCloskey, M., Chein, J. M., Fareri, D. S., et al. (2020) · Journal of Psychiatry and Brain Science · doi:10.20900/jpbs.20200024 · Cited by 15

Globally Aging Cortical Spontaneous Activity Revealed by Multiple Metrics and Frequency Bands Using Resting-State Functional MRI

Xing, X.-X. (2021) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2021.803436 · Cited by 14

Increased sensorimotor network connectivity associated with clozapine eligibility in people with schizophrenia

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Sex differences in brain correlates of STEM anxiety

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Topological network properties of resting-state functional connectivity patterns are associated with metal mixture exposure in adolescents

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Repeatability of graph theoretical metrics derived from resting-state functional networks in paediatric epilepsy patients

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The relationship between performance in a theory of mind task and intrinsic functional connectivity in youth with early onset psychosis

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Effects of social and emotional context on neural activation and synchrony during movie viewing

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Large‐scale brain network activation during emotional inhibitory control: Associations with alcohol misuse in college freshmen

Cohen‐Gilbert, J. E., Nickerson, L. D. H., Seraikas, A. M., Oot, E. N., Rieselbach, M. M., Schuttenberg, E. M., Sneider, J. T., & Silveri, M. M. (2022) · Alcoholism Clinical and Experimental Research · doi:10.1111/acer.14782 · Cited by 13

Aberrant motor contagion of emotions in psychopathy and high-functioning autism

Sun, L., Lukkarinen, L., Noppari, T., Nazari‐Farsani, S., Putkinen, V., Seppälä, K., Hudson, M., Tani, P., Lindberg, N., Karlsson, H. K., et al. (2022) · Cerebral Cortex · doi:10.1093/cercor/bhac072 · Cited by 16

Uncovering shape signatures of resting‐state functional connectivity by geometric deep learning on Riemannian manifold

Dan, T., Huang, Z., Cai, H., Lyday, R. G., Laurienti, P. J., & Guorong Wu, A. (2022) · Human Brain Mapping · doi:10.1002/hbm.25897 · Cited by 13

A comparison of multiband and multiband multiecho gradient‐echo EPI for task fMRI at 3 T

Fazal, Z., Gomez, D. E. P., Llera, A., Marques, J. P., Beck, T., Poser, B. A., & Norris, D. G. (2022) · Human Brain Mapping · doi:10.1002/hbm.26081 · Cited by 11

Quality control in resting-state fMRI: the benefits of visual inspection

Lepping, R. J., Yeh, H., McPherson, B., Brucks, M. G., Sabati, M., Karcher, R. T., Brooks, W. M., Habiger, J., Papa, V. B., & Martin, L. E. (2023) · Frontiers in Neuroscience · doi:10.3389/fnins.2023.1076824 · Cited by 16

Antisocial behavior is associated with reduced frontoparietal network efficiency in youth

Tillem, S., Dotterer, H. L., Goetschius, L. G., Lopez‐Duran, N. L., Mitchell, C. M., Monk, C. S., & Hyde, L. W. (2023) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsad026 · Cited by 14

Assessing age-dependent multi-task functional co-activation changes using measures of task-potency

Chauvin, R. J., Mennes, M., Buitelaar, J. K., & Beckmann, C. F. (2017) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2017.11.011 · Cited by 13

Brain responses to anticipating and receiving beer: Comparing light, at‐risk, and dependent alcohol users

Groefsema, M. M., Engels, R. C. M. E., Voon, V., Schellekens, A., Luijten, M., & Sescousse, G. (2019) · Addiction Biology · doi:10.1111/adb.12766 · Cited by 12

Nucleus accumbens connectivity at rest is associated with alcohol consumption in young male adults

Veer, I. M., Jetzschmann, P., Garbusow, M., Nebe, S., Frank, R., Kuitunen‐Paul, S., Sebold, M., Ripke, S., Heinz, A., Friedel, E., et al. (2019) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2019.10.008 · Cited by 14

The interacting brain: Dynamic functional connectivity among canonical brain networks dissociates cooperative from competitive social interactions

Shaw, D. J., Czekóová, K., Mareček, R., Špiláková, B., & Brázdil, M. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.119933 · Cited by 15

Decoding brain basis of laughter and crying in natural scenes

Nummenmaa, L., Malén, T., Nazari‐Farsani, S., Seppälä, K., Sun, L., Santavirta, S., Karlsson, H. K., Hudson, M., Hirvonen, J., Sams, M. E., et al. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.120082 · Cited by 16

Disrupted resting-sate brain network dynamics in children born extremely preterm

Padilla, N., Escrichs, A., del Agua, E., Kringelbach, M. L., Donaire, A., Deco, G., & Ådén, U. (2023) · Cerebral Cortex · doi:10.1093/cercor/bhad101 · Cited by 12

Multilayer meta-matching: Translating phenotypic prediction models from multiple datasets to small data

Chen, P., An, L., Wulan, N., Zhang, C., Zhang, S., Ooi, L. Q. R., Kong, R., Chen, J., Wu, J., Chopra, S., et al. (2024) · Imaging Neuroscience · doi:10.1162/imag_a_00233 · Cited by 14

Reciprocal causation relationship between rumination thinking and sleep quality: a resting-state fMRI study

Yang, S., & Lei, X. (2025) · Cognitive Neurodynamics · doi:10.1007/s11571-025-10223-3 · Cited by 12

Differential Effects of Sustained Manual Pressure Stimulation According to Site of Action

Hok, P., Opavsky, J., Labounek, R., Kutín, M., Šlachtová, M., Tüdös, Z., Kaňovský, P., & Hluštı́k, P. (2019) · Frontiers in Neuroscience · doi:10.3389/fnins.2019.00722 · Cited by 12

Co‐activation pattern alterations in autism spectrum disorder–A volume‐wise hierarchical clustering fMRI study

Paakki, J., Rahko, J. S., Kotila, A., Mattila, M., Miettunen, H., Hurtig, T. M., Jussila, K. K., Kuusikko‐Gauffin, S., Moilanen, I. K., Tervonen, O. A., et al. (2021) · Brain and Behavior · doi:10.1002/brb3.2174 · Cited by 12

Sex-specific frontal-striatal connectivity differences among adolescents with externalizing disorders

Chai, Y., Chimelis-Santiago, J. R., Bixler, K., Aalsma, M. C., Yu, M., & Hulvershorn, L. A. (2021) · NeuroImage Clinical · doi:10.1016/j.nicl.2021.102789 · Cited by 13

Shared atypical brain anatomy and intrinsic functional architecture in male youth with autism spectrum disorder and their unaffected brothers

Lin, H., Tseng, W. I., Lai, M., Chang, Y.-T., & Gau, S. S. (2016) · Psychological Medicine · doi:10.1017/s0033291716002695 · Cited by 12

Investigating the impact of overnight fasting on intrinsic functional connectivity: a double-blind fMRI study

Orfanos, S., Toygar, T., Berthold‐Losleben, M., Chechko, N., Durst, A., Laoutidis, Z. G., Vocke, S., Weidenfeld, C., Schneider, F. W., Karges, W., et al. (2017) · Brain Imaging and Behavior · doi:10.1007/s11682-017-9777-9 · Cited by 12

Effects of Bergen 4-Day Treatment on Resting-State Graph Features in Obsessive-Compulsive Disorder

Thorsen, A. L., Vriend, C., de Wit, S. J., Ousdal, O. T., Hagen, K., Hansen, B. K. A., Kvale, G., & van den Heuvel, O. A. (2020) · Biological Psychiatry Cognitive Neuroscience and Neuroimaging · doi:10.1016/j.bpsc.2020.01.007 · Cited by 13

The virtual aging brain: a model-driven explanation for cognitive decline in older subjectsPreprint

Lavanga, M., Stumme, J., Yalçınkaya, B. H., Fousek, J., Jockwitz, C., Sheheitli, H., Bittner, N., Hashemi, M., Petkoski, S., Caspers, S., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.02.17.480902 · Cited by 12

Delineating disorder-general and disorder-specific dimensions of psychopathology from functional brain networks in a developmental clinical sample

Voldsbekk, I., Kjelkenes, R., Dahl, A., Holm, M. C., Lund, M. J., Kaufmann, T., Tamnes, C. K., Andreassen, O. A., Westlye, L. T., & Alnæs, D. (2023) · Developmental Cognitive Neuroscience · doi:10.1016/j.dcn.2023.101271 · Cited by 14

Comparing data-driven physiological denoising approaches for resting-state fMRI: implications for the study of aging

Golestani, A., & Chen, J. J. (2024) · Frontiers in Neuroscience · doi:10.3389/fnins.2024.1223230 · Cited by 11

Treating dissociative post-traumatic stress disorder presenting as a functional movement disorder with transcranial magnetic stimulation targeting the cingulate gyrus

Blades, R. B., Jordan, S., Becerra, S. A., Eusebio, B., Heatwole, M., Iovine, J., Mahdavi, K. D., Mamoun, M. S., Nicodemus, N., Packham, H., et al. (2020) · Neurological Sciences · doi:10.1007/s10072-020-04433-2 · Cited by 11

The role of maternal BMI on brain food cue reactivity in children: a preliminary study

LUO, S. H., ANGELO, B. C., Chow, T., Monterosso, J. R., Xiang, A. H., Thompson, P. M., & Page, K. A. (2021) · Brain Imaging and Behavior · doi:10.1007/s11682-021-00466-z · Cited by 11

Patterns of connectome variability in autism across five functional activation tasks: findings from the LEAP project

Looden, T., Floris, D. L., Llera, A., Chauvin, R. J., Charman, T., Banaschewski, T., Murphy, D., Marquand, A. F., Buitelaar, J. K., Beckmann, C. F., et al. (2022) · Molecular Autism · doi:10.1186/s13229-022-00529-y · Cited by 12

MRgFUS of the nucleus ventralis intermedius in essential tremor modulates functional connectivity within the classical tremor network and beyond

Kindler, C., Upadhyay, N., Purrer, V., Schmeel, F. C., Borger, V., Scheef, L., Wüllner, U., & Boecker, H. (2023) · Parkinsonism & Related Disorders · doi:10.1016/j.parkreldis.2023.105845 · Cited by 10

Motor Signature Differences Between Autism Spectrum Disorder and Developmental Coordination Disorder, and Their Neural Mechanisms

Butera, C. D., Delafield‐Butt, J. T., Lu, S., Sobota, K., McGowan, T., Harrison, L., Kilroy, E., Jayashankar, A., & Aziz‐Zadeh, L. (2023) · Journal of Autism and Developmental Disorders · doi:10.1007/s10803-023-06171-8 · Cited by 15

ICA-AROMA: A robust ICA-based strategy for removing motion artifacts from fMRI data

Pruim, R. H. R., Mennes, M., van Rooij, D., Llera, A., Buitelaar, J. K., & Beckmann, C. F. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2015.02.064 · Cited by 1,684

The optimized combination of aCompCor and ICA-AROMA to reduce motion and physiologic noise in task fMRI data

Schuerbeek, P. V., Wandel, L. D., & Baeken, C. (2022) · Biomedical Physics & Engineering Express · doi:10.1088/2057-1976/ac63f0 · Cited by 5

Methods to detect, characterize, and remove motion artifact in resting state fMRI

Power, J. D., Mitra, A., Laumann, T. O., Snyder, A. Z., Schlaggar, B. L., & Petersen, S. E. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2013.08.048 · Cited by 3,748

Reduction of motion-related artifacts in resting state fMRI using aCompCor

Muschelli, J., Nebel, M. B., Caffo, B. S., Barber, A. D., Pekar, J. J., & Mostofsky, S. H. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.03.028 · Cited by 431

Comparing resting state fMRI de-noising approaches using multi- and single-echo acquisitions

Dipasquale, O., Sethi, A., Laganà, M. M., Baglio, F., Baselli, G., Kundu, P., Harrison, N. A., & Cercignani, M. (2017) · PLoS ONE · doi:10.1371/journal.pone.0173289 · Cited by 96