Cited by 191Functional Brain Connectivity StudiesAdvanced MRI Techniques and ApplicationsAdvanced Neuroimaging Techniques and Applications

The DOI matches its Crossref record; 29 of the 30 references it cites were found in a registry or an index.

Combining independent component analysis and correlation analysis to probe interregional connectivity in fMRI task activation datasets

Arfanakis, Konstantinos, Cordes, Dietmar, Haughton, Victor M, Moritz, Chad H, Quigley, Michelle A, Meyerand, Mary E·2000·Magnetic Resonance Imaging

DOI 10.1016/s0730-725x(00)00190-9

Open this paper in CoChat — free account

Abstract

A new approach in studying interregional functional connectivity using functional magnetic resonance imaging (fMRI) is presented. Functional connectivity may be detected by means of cross correlating time course data from functionally related brain regions. These data exhibit high temporal coherence of low frequency fluctuations due to synchronized blood flow changes. In the past, this fMRI technique for studying functional connectivity has been applied to subjects that performed no prescribed task ("resting" state). This paper presents the results of applying the same method to task-related activation datasets. Functional connectivity analysis is first performed in areas not involved with the task. Then a method is devised to remove the effects of activation from the data using independent component analysis (ICA) and functional connectivity analysis is repeated. Functional connectivity, which is demonstrated in the "resting brain," is not affected by tasks which activate unrelated brain regions. In addition, ICA effectively removes activation from the data and may allow us to study functional connectivity even in the activated regions.

Integrity signals

Registry

Crossref · 10.1016/s0730-725x(00)00190-9

Cites

29 of 29 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Independent Component Analysis
Hyvärinen, A., Karhunen, J., & Oja, E. (2001) · Encyclopedia of Biometrics · doi:10.1007/978-0-387-73003-5_305 · Cited by 10,459
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
Self-citation
An Information-Maximization Approach to Blind Separation and Blind Deconvolution
Bell, A. J., & Sejnowski, T. J. (1995) · Neural Computation · doi:10.1162/neco.1995.7.6.1129 · Cited by 8,986
Independent component analysis, A new concept?
Comon, P. (1994) · Signal Processing · doi:10.1016/0165-1684(94)90029-9 · Cited by 8,324
Dynamic magnetic resonance imaging of human brain activity during primary sensory stimulation.
Kwong, K. K., Belliveau, J. W., Chesler, D. A., Goldberg, I. E., Weisskoff, R. M., Poncelet, B. P., Kennedy, D. N., Hoppel, B. E., Cohen, M. S., & Turner, R. (1992) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.89.12.5675 · Cited by 4,212
Oscillatory responses in cat visual cortex exhibit inter-columnar synchronization which reflects global stimulus properties
Gray, C. M., König, P., Engel, A. K., & Singer, W. (1989) · Nature · doi:10.1038/338334a0 · Cited by 4,183
Intrinsic signal changes accompanying sensory stimulation: functional brain mapping with magnetic resonance imaging.
Ogawa, S., Tank, D. W., Menon, R., Ellermann, J. M., Kim, S. G., Merkle, H., & Ugurbil, K. (1992) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.89.13.5951 · Cited by 3,681
Functional Connectivity: The Principal-Component Analysis of Large (PET) Data Sets
Friston, K. J., Frith, C., Liddle, P. F., & Frackowiak, R. S. J. (1993) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1038/jcbfm.1993.4 · Cited by 1,997
Processing strategies for time‐course data sets in functional mri of the human brain
Bandettini, P. A., Jesmanowicz, A., Wong, E. C., & Hyde, J. S. (1993) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910300204 · Cited by 1,762
Functional connectivity in single and multislice echoplanar imaging using resting-state fluctuations
Lowe, M. J., Mock, B. J., & Sorenson, J. A. (1998) · NeuroImage · doi:10.1006/nimg.1997.0315 · Cited by 1,394

Show all 30 references

Research works printed but not linked: 5

Jezzard P, LeBihan D, Cuenod D, Pannier L, Prinster A, Turner R. An investigation of the contribution of physiologic noise in human functional MRI studies at 1.5 tesla and 4 tesla. In: Book of abstracts: twelfth annual meeting of the Society of Magnetic Resonance in Medicine, Vol. 3. New York, NY: SMRM, 1993. p. 1392.
Dora, 1980, Metabolic and vascular volume oscillation in the cat brain cortex, Acts Physiologica Acad Sci Hungaricae, 57, 261
Tomita, 1981, 4–6 cycle per minute fluctuation in cerebral blood volume of feline cortical tissue in situ, J Cereb Blood Flow Metab, 1, S443
Arfanakis K, Cordes D, Sorenson JA, Haughton VM, Quigley MA, Meyerand ME. Effects of task related activation on physiological noise using functional connectivity analysis. In: Book of abstracts: seventh annual meeting of the International Society of Magnetic Resonance in Medicine, Vol. 3. Philadelphia, PA: ISMRM; 1999. p. 1713.
Liu WC, Schulder M, Kalnin AJ, Holodny A, Gray A. Mixing task paradigm in fMRI for radiosurgery. In: Book of abstracts: seventh annual meeting of the International Society of Magnetic Resonance in Medicine, Vol. 3. Philadelphia, PA: ISMRM, 1999. p. 1692.

Sorted by citations

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
Spontaneous fluctuations in brain activity observed with functional magnetic resonance imaging
Fox, M. D., & Raichle, M. E. (2007) · Nature Reviews Neuroscience · doi:10.1038/nrn2201 · Cited by 6,700
Spontaneous neuronal activity distinguishes human dorsal and ventral attention systems
Fox, M. D., Corbetta, M., Snyder, A. Z., Vincent, J. L., & Raichle, M. E. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0604187103 · Cited by 2,101
Clinical applications of resting state functional connectivity
Fox, M. (2010) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2010.00019 · Cited by 1,219
Time for united action on depression: a Lancet–World Psychiatric Association Commission
Herrman, H., Patel, V., Kieling, C., Berk, M., Buchweitz, C., Cuijpers, P., Furukawa, T. A., Kessler, R. C., Kohrt, B. A., Maj, M., et al. (2022) · The Lancet · doi:10.1016/s0140-6736(21)02141-3 · Cited by 1,104
Groupwise whole-brain parcellation from resting-state fMRI data for network node identification
Shen, X., Tokoglu, F., Papademetris, X., & Constable, R. T. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.05.081 · Cited by 1,027
Coherent spontaneous activity identifies a hippocampal-parietal memory network
Vincent, J. L., Snyder, A. Z., Fox, M. D., Shannon, B. J., Andrews, J. R., Raichle, M. E., & Buckner, R. L. (2006) · Journal of Neurophysiology · doi:10.1152/jn.00048.2006 · Cited by 959
Disease and the brain's dark energy
Zhang, D., & Raichle, M. E. (2010) · Nature Reviews Neurology · doi:10.1038/nrneurol.2009.198 · Cited by 928
Activity and Connectivity of Brain Mood Regulating Circuit in Depression: A Functional Magnetic Resonance Study
Anand, A., Li, Y., Wang, Y., Wu, J., Gao, S., Bukhari, L., Mathews, V. P., Kalnin, A., & Lowe, M. J. (2005) · Biological Psychiatry · doi:10.1016/j.biopsych.2005.02.021 · Cited by 787
Dynamic reconfiguration of the default mode network during narrative comprehension
Simony, E., Honey, C. J., Chen, J., Lositsky, O., Yeshurun, Y., Wiesel, A., & Hasson, U. (2016) · Nature Communications · doi:10.1038/ncomms12141 · Cited by 588
Very Slow Activity Fluctuations in Monkey Visual Cortex: Implications for Functional Brain Imaging
Leopold, D. A. (2003) · Cerebral Cortex · doi:10.1093/cercor/13.4.422 · Cited by 675
Disrupted amygdalar subregion functional connectivity and evidence of a compensatory network in generalized anxiety disorder
Etkin, A., Prater, K. E., Schatzberg, A. F., Menon, V., & Greicius, M. D. (2009) · Archives of General Psychiatry · doi:10.1001/archgenpsychiatry.2009.104 · Cited by 664
Low frequency BOLD fluctuations during resting wakefulness and light sleep: A simultaneous EEG‐fMRI study
Horovitz, S. G., Fukunaga, M., de Zwart, J. A., van Gelderen, P., Fulton, S. C., Balkin, T. J., & Duyn, J. H. (2008) · Human Brain Mapping · doi:10.1002/hbm.20428 · Cited by 616
Imaging brain dynamics using independent component analysis
Jung, T., Makeig, S., McKeown, M. J., Bell, A. J., Lee, T.-W., & B, T. J. S. A. (2001) · Proceedings of the IEEE · doi:10.1109/5.939827 · Cited by 607
A method for using blocked and event-related fMRI data to study “resting state” functional connectivity
Fair, D. A., Schlaggar, B. L., Cohen, A. L., Miezin, F. M., Dosenbach, N. U. F., Wenger, K. K., Fox, M., Snyder, A. Z., Raichle, M. E., & Petersen, S. E. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2006.11.051 · Cited by 615
Modulation of temporally coherent brain networks estimated using ICA at rest and during cognitive tasks
Calhoun, V. D., Kiehl, K. A., & Pearlson, G. D. (2008) · Human Brain Mapping · doi:10.1002/hbm.20581 · Cited by 567
Functional connectivity as revealed by spatial independent component analysis of fMRI measurements during rest
van de Ven, V. G., Formisano, E., Prvulovic, D., Röder, C. H., & Linden, D. E. J. (2004) · Human Brain Mapping · doi:10.1002/hbm.20022 · Cited by 538
Study design in fMRI: Basic principles
Amaro, E., & Barker, G. J. (2006) · Brain and Cognition · doi:10.1016/j.bandc.2005.11.009 · Cited by 564
Partial correlation for functional brain interactivity investigation in functional MRI
Marrelec, G., Krainik, A., Duffau, H., Pélégrini-Issac, M., Lehéricy, S., Doyon, J., & Benali, H. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2005.12.057 · Cited by 488
Assessing functional connectivity in the human brain by fMRI
Rogers, B. P., Morgan, V. L., Newton, A. T., & Gore, J. C. (2007) · Magnetic Resonance Imaging · doi:10.1016/j.mri.2007.03.007 · Cited by 511
Unrest at rest: Default activity and spontaneous network correlations
Buckner, R. L., & Vincent, J. L. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.01.010 · Cited by 523
Functional connectivity in the cognitive control network and the default mode network in late-life depression
Alexopoulos, G. S., Hoptman, M. J., Kanellopoulos, D., Murphy, C. F., Lim, K. O., & Gunning, F. M. (2012) · Journal of Affective Disorders · doi:10.1016/j.jad.2011.12.002 · Cited by 437
Independent component analysis of functional MRI: what is signal and what is noise?
McKeown, M. J., Hansen, L. K., & Sejnowsk, T. J. (2003) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2003.09.012 · Cited by 421
Measuring interregional functional connectivity using coherence and partial coherence analyses of fMRI data
Sun, F. T., Miller, L. M., & D’Esposito, M. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2003.09.056 · Cited by 406
Measuring and manipulating brain connectivity with resting state functional connectivity magnetic resonance imaging (fcMRI) and transcranial magnetic stimulation (TMS)
Fox, M. D., Halko, M. A., Eldaief, M. C., & Pascual-Leone, A. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.03.035 · Cited by 395
Hierarchical clustering to measure connectivity in fMRI resting-state data
Cordes, D., Haughton, V. H., Carew, J. D., Arfanakis, K., & Maravilla, K. (2002) · Magnetic Resonance Imaging · doi:10.1016/s0730-725x(02)00503-9 · Cited by 367
Self-citation
Sleep deprivation reduces default mode network connectivity and anti-correlation during rest and task performance
De Havas, J. A., Parimal, S., Soon, C. S., & Chee, M. W. L. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2011.08.026 · Cited by 363
Why use a connectivity-based approach to study stroke and recovery of function?
Carter, A. R., Shulman, G. L., & Corbetta, M. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.02.070 · Cited by 333
General functional connectivity: Shared features of resting-state and task fMRI drive reliable and heritable individual differences in functional brain networks
Elliott, M. L., Knodt, A. R., Cooke, M. E., Kim, M. J., Melzer, T. R., Keenan, R. J., Ireland, D. R., Ramrakha, S., Poulton, R., Caspi, A., et al. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.01.068 · Cited by 308
Independent Component Analysis as a Tool to Eliminate Artifacts in EEG: A Quantitative Study
Iriarte, J., Urrestarazu, E., Valencia, M., Alegre, M., Malanda, A., Viteri, C., & Artieda, J. (2003) · Journal of Clinical Neurophysiology · doi:10.1097/00004691-200307000-00004 · Cited by 290
Review of methods for functional brain connectivity detection using fMRI
Li, K., Guo, L., Nie, J., Li, G., & Liu, T. (2008) · Computerized Medical Imaging and Graphics · doi:10.1016/j.compmedimag.2008.10.011 · Cited by 278
The left occipitotemporal system in reading: Disruption of focal fMRI connectivity to left inferior frontal and inferior parietal language areas in children with dyslexia
van der Mark, S., Klaver, P., Bücher, K., Maurer, U., Schulz, E., Brem, S., Martin, E., & Brandeis, D. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.10.002 · Cited by 274
Resting developments: a review of fMRI post-processing methodologies for spontaneous brain activity
Margulies, D. S., Böttger, J., Long, X., Lv, Y., Kelly, C. A. M., Schäfer, A., Goldhahn, D., Abbushi, A., Milham, M. P., Lohmann, G., et al. (2010) · Magnetic Resonance Materials in Physics Biology and Medicine · doi:10.1007/s10334-010-0228-5 · Cited by 256
Intrinsic brain activity sets the stage for expression of motivated behavior
Raichle, M. E., & Gusnard, D. A. (2005) · The Journal of Comparative Neurology · doi:10.1002/cne.20752 · Cited by 224
Single-Trial Variability in Event-Related BOLD Signals
Duann, J., Jung, T., Kuo, W., Yeh, T., Makeig, S., Hsieh, J., & B, T. J. S. A. (2002) · NeuroImage · doi:10.1006/nimg.2001.1049 · Cited by 215
Time lag dependent multimodal processing of concurrent fMRI and near-infrared spectroscopy (NIRS) data suggests a global circulatory origin for low-frequency oscillation signals in human brain
Tong, Y., & Frederick, B. B. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.06.049 · Cited by 208
On the relationship between seed‐based and ICA‐based measures of functional connectivity
Joel, S. E., Caffo, B. S., van Zijl, P. C. M., & Pekar, J. J. (2011) · Magnetic Resonance in Medicine · doi:10.1002/mrm.22818 · Cited by 218
The chronoarchitecture of the human brain—natural viewing conditions reveal a time-based anatomy of the brain
Bartels, A., & Zeki, S. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.01.007 · Cited by 207
PREOPERATIVE SENSORIMOTOR MAPPING IN BRAIN TUMOR PATIENTS USING SPONTANEOUS FLUCTUATIONS IN NEURONAL ACTIVITY IMAGED WITH FUNCTIONAL MAGNETIC RESONANCE IMAGING
Zhang, D., Johnston, J. M., Fox, M., Leuthardt, E. C., Grubb, R. L., Chicoine, M. R., Smyth, M. D., Snyder, A. Z., Raichle, M. E., & Shimony, J. S. (2009) · Operative Neurosurgery · doi:10.1227/01.neu.0000350868.95634.ca · Cited by 198
Aberrant functional connectivity in autism: Evidence from low-frequency BOLD signal fluctuations
Noonan, S. K., Haist, F., & Müller, R. (2009) · Brain Research · doi:10.1016/j.brainres.2008.12.076 · Cited by 208
Brain dynamics during natural viewing conditions—A new guide for mapping connectivity in vivo
Bartels, A., & Zeki, S. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.08.044 · Cited by 189
Correlated Low-Frequency BOLD Fluctuations in the Resting Human Brain Are Modulated by Recent Experience in Category-Preferential Visual Regions
Stevens, W. D., Buckner, R. L., & Schacter, D. L. (2009) · Cerebral Cortex · doi:10.1093/cercor/bhp270 · Cited by 195
Dynamic reorganization of human resting-state networks during visuospatial attention
Spadone, S., Penna, S. D., Sestieri, C., Betti, V., Tosoni, A., Perrucci, M. G., Romani, G. L., & Corbetta, M. (2015) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1415439112 · Cited by 182
Natural Scenes Viewing Alters the Dynamics of Functional Connectivity in the Human Brain
Betti, V., Penna, S. D., de Pasquale, F., Mantini, D., Marzetti, L., Romani, G. L., & Corbetta, M. (2013) · Neuron · doi:10.1016/j.neuron.2013.06.022 · Cited by 191
Methods for analysis of brain connectivity: An IFCN-sponsored review
Rossini, P. M., Iorio, R. D., Bentivoglio, M., Bertini, G., Ferreri, F., Gerloff, C. P., Ilmoniemi, R. J., Miraglia, F., Nitsche, M. A., Pestilli, F., et al. (2019) · Clinical Neurophysiology · doi:10.1016/j.clinph.2019.06.006 · Cited by 169
Evolution of Cognitive Function Via Redeployment of Brain Areas
Anderson, M. L. (2006) · The Neuroscientist · doi:10.1177/1073858406294706 · Cited by 154
Automated regional behavioral analysis for human brain images
Lancaster, J. L., Laird, A. R., Eickhoff, S. B., Martinez, M. J., Fox, P. M., & Fox, P. T. (2012) · Frontiers in Neuroinformatics · doi:10.3389/fninf.2012.00023 · Cited by 150
The power of spectral density analysis for mapping endogenous BOLD signal fluctuations
Duff, E. P., Johnston, L. A., Xiong, J., Fox, P. T., Mareels, I., & Egan, G. F. (2008) · Human Brain Mapping · doi:10.1002/hbm.20601 · Cited by 145
Defining the Neural Circuitry of Depression: Toward a New Nosology With Therapeutic Implications
Mayberg, H. S. (2007) · Biological Psychiatry · doi:10.1016/j.biopsych.2007.01.013 · Cited by 145
Quantitative evaluation of interrelations between spontaneous low-frequency oscillations in cerebral hemodynamics and systemic cardiovascular dynamics
Katura, T., Tanaka, N., Obata, A. N., Sato, H. R., & Maki, A. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.02.010 · Cited by 144
The contributions of resting state and task-based functional connectivity studies to our understanding of adolescent brain network maturation
Stevens, M. C. G. (2016) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2016.07.027 · Cited by 145
Task fMRI paradigms may capture more behaviorally relevant information than resting-state functional connectivity
Zhao, W., Makowski, C., Hagler, D. J., Garavan, H., Thompson, W. K., Greene, D. J., Jernigan, T. L., & Dale, A. M. (2023) · NeuroImage · doi:10.1016/j.neuroimage.2023.119946 · Cited by 138
Functional disconnectivity in subjects at high genetic risk of schizophrenia
Whalley, H. C., Simonotto, E., Marshall, I., Owens, D. G. C., Goddard, N., Johnstone, E. C., & Lawrie, S. M. (2005) · Brain · doi:10.1093/brain/awh556 · Cited by 134
Spatial independent component analysis of functional MRI time‐series: To what extent do results depend on the algorithm used?
Esposito, F., Formisano, E., Seifritz, E., Goebel, R., Morrone, R., Tedeschi, G., & Salle, F. D. (2002) · Human Brain Mapping · doi:10.1002/hbm.10034 · Cited by 128
Functional Differentiation of Posterior Superior Temporal Sulcus in Autism: A Functional Connectivity Magnetic Resonance Imaging Study
Shih, P., Keehn, B., Oram, J. K., Leyden, K. M., Keown, C. L., & Müller, R. (2011) · Biological Psychiatry · doi:10.1016/j.biopsych.2011.03.040 · Cited by 136
Reduced connectivity of the auditory cortex in patients with auditory hallucinations: A resting state functional magnetic resonance imaging study
Gavrilescu, M., Rossell, S., Stuart, G. W., Shea, T. L., Innes-Brown, H., Henshall, K., McKay, C., Sergejew, A. A., Copolov, D., & Egan, G. F. (2010) · Psychological Medicine · doi:10.1017/s0033291709991632 · Cited by 121
Atypical network connectivity for imitation in autism spectrum disorder
Shih, P., Shen, M., Öttl, B., Keehn, B., Gaffrey, M. S., & Müller, R.-A. (2010) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2010.05.035 · Cited by 120
Cognitive state and connectivity effects of the genome-wide significant psychosis variant in ZNF804A
Esslinger, C., Kirsch, P., Haddad, L., Mier, D. U., Sauer, C., Erk, S., Schnell, K., Arnold, C., Witt, S. H., Rietschel, M., et al. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.10.012 · Cited by 121
Independent Component Analysis Removing Artifacts in Ictal Recordings
Urrestarazu, E., Iriarte, J., Alegre, M., Valencia, M., Viteri, C., & Artieda, J. (2004) · Epilepsia · doi:10.1111/j.0013-9580.2004.12104.x · Cited by 119
Functional network connectivity during rest and task conditions: A comparative study
Arbabshirani, M. R., Havlíček, M., Kiehl, K. A., Pearlson, G. D., & Calhoun, V. D. (2012) · Human Brain Mapping · doi:10.1002/hbm.22118 · Cited by 120
Functional connectivity in the first year of life in infants at-risk for autism: a preliminary near-infrared spectroscopy study
Keehn, B., Wagner, J., Tager-Flusberg, H. B., & Nelson, C. A. (2013) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2013.00444 · Cited by 125
Modulation of steady state functional connectivity in the default mode and working memory networks by cognitive load
Newton, A. T., Morgan, V. L., Rogers, B. P., & Gore, J. C. (2010) · Human Brain Mapping · doi:10.1002/hbm.21138 · Cited by 116
Time‐varied characteristics of acupuncture effects in fMRI studies
Bai, L., Qin, W., Tian, J., Liu, P., Li, L., Chen, P., Dai, J., Craggs, J. G., von Deneen, K. M., & Liu, Y. (2009) · Human Brain Mapping · doi:10.1002/hbm.20769 · Cited by 110
Altered functional connectivity of the default mode network in diffuse gliomas measured with pseudo-resting state fMRI
Harris, R. J., Bookheimer, S. Y., Cloughesy, T. F., Kim, H. J., Pope, W. B., Lai, A., Nghiemphu, P. L., Liau, L. M., & Ellingson, B. M. (2013) · Journal of Neuro-Oncology · doi:10.1007/s11060-013-1304-2 · Cited by 107
Connective field modeling
Haak, K. V., Winawer, J. A., Harvey, B. M., Renken, R. J., Dumoulin, S. O., Wandell, B. A., & Cornelissen, F. W. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.10.037 · Cited by 102
Working memory‐related changes in functional connectivity persist beyond task disengagement
Gordon, E. M., Breeden, A. L., Bean, S. E., & Vaidya, C. J. (2012) · Human Brain Mapping · doi:10.1002/hbm.22230 · Cited by 103
Resting‐state functional connectivity MRI reveals active processes central to cognition
Stevens, W. D., & Spreng, R. N. (2014) · Wiley Interdisciplinary Reviews Cognitive Science · doi:10.1002/wcs.1275 · Cited by 108
The contribution of electrophysiology to functional connectivity mapping
Schölvinck, M. L., Leopold, D. A., Brookes, M. J., & Khader, P. H. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.04.010 · Cited by 101
Aberrant localization of synchronous hemodynamic activity in auditory cortex reliably characterizes schizophrenia
Calhoun, V. D., Kiehl, K. A., Liddle, P. F., & Pearlson, G. D. (2004) · Biological Psychiatry · doi:10.1016/j.biopsych.2004.01.011 · Cited by 91
Spinal Cord–Midbrain Functional Connectivity Is Related to Perceived Pain Intensity: A Combined Spino-Cortical fMRI Study
Sprenger, C., Finsterbusch, J., & Büchel, C. (2015) · Journal of Neuroscience · doi:10.1523/jneurosci.4897-14.2015 · Cited by 92
Functional Connectivity and Brain Activation: A Synergistic Approach
Tomasi, D. G., Wang, R., Wang, G., & Volkow, N. D. (2013) · Cerebral Cortex · doi:10.1093/cercor/bht119 · Cited by 92
Comparison of Two Exploratory Data Analysis Methods for fMRI: Unsupervised Clustering Versus Independent Component Analysis
Meyer‐Baese, A., Wismueller, A., & Lange, O. (2004) · IEEE Transactions on Information Technology in Biomedicine · doi:10.1109/titb.2004.834406 · Cited by 74
Functional connectivity by cross-correlation clustering
Dodel, S., Herrmann, J. M., & Geisel, T. (2002) · Neurocomputing · doi:10.1016/s0925-2312(02)00416-2 · Cited by 74
A neural measure of behavioral engagement: Task-residual low-frequency blood oxygenation level-dependent activity in the precuneus
Zhang, S., & Li, C. R. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.09.004 · Cited by 67
Cerebral gray matter volumes and low-frequency fluctuation of BOLD signals in cocaine dependence: Duration of use and gender difference
Ide, J. S., Zhang, S., Hu, S., Sinha, R., Mazure, C. M., & Li, C. R. (2013) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2013.09.004 · Cited by 68
Removing the effects of task-related motion using independent-component analysis
Kochiyama, T., Morita, T., Okada, T., Yonekura, Y., Matsumura, M., & Sadato, N. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2004.12.027 · Cited by 62
A Hierarchical Method for Removal of Baseline Drift from Biomedical Signals: Application in ECG Analysis
Luo, Y., Hargraves, R. H., Belle, A., Bai, O., Qi, X., Ward, K. R., Pfaffenberger, M. P., & Najarian, K. (2013) · The Scientific World JOURNAL · doi:10.1155/2013/896056 · Cited by 58
The Decline in Intrinsic Connectivity Between the Salience Network and Locus Coeruleus in Older Adults: Implications for Distractibility
Lee, T., Kim, S. H., Katz, B., & Mather, M. (2020) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2020.00002 · Cited by 58
Task‐evoked functional connectivity does not explain functional connectivity differences between rest and task conditions
Lynch, L. K., Lu, K., Wen, H., Zhang, Y., Saykin, A. J., & Liu, Z. (2018) · Human Brain Mapping · doi:10.1002/hbm.24335 · Cited by 54
Atypical modulation of distant functional connectivity by cognitive state in children with Autism Spectrum Disorders
You, X., Norr, M. E., Murphy, E. R., Kuschner, E. S., Bal, E., Gaillard, W. D., Kenworthy, L. E., & Vaidya, C. J. (2013) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2013.00482 · Cited by 55
Functional connectivity of the cortical swallowing network in humans
Babaei, A., Ward, B. D., Siwiec, R. M., Ahmad, S., Kern, M., Nencka, A. S., Li, S., & Shaker, R. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.01.037 · Cited by 52
Frontolimbic brain networks predict depressive symptoms in temporal lobe epilepsy
Kemmotsu, N., Kucukboyaci, N. E., Leyden, K. M., Cheng, C. E., Girard, H. M., Iragui, V. J., Tecoma, E. S., & McDonald, C. R. (2014) · Epilepsy Research · doi:10.1016/j.eplepsyres.2014.08.018 · Cited by 48
Functional connectivity estimation in fMRI data: Influence of preprocessing and time course selection
Gavrilescu, M. C., Stuart, G. W., Rossell, S. L., Henshall, K. R., McKay, C. M., Sergejew, A. A., Copolov, D., & Egan, G. F. (2007) · Human Brain Mapping · doi:10.1002/hbm.20446 · Cited by 45
Task‐dependent reorganization of functional connectivity networks during visual semantic decision making
Desalvo, M. N., Douw, L., Takaya, S., Liu, H., & Stufflebeam, S. M. (2014) · Brain and Behavior · doi:10.1002/brb3.286 · Cited by 46
Functional Near-Infrared Spectroscopy Reveals Reduced Interhemispheric Cortical Communication after Pediatric Concussion
Urban, K. J., Barlow, K. M., Jimenez, J. J., Goodyear, B. G., & Dunn, J. F. (2014) · Journal of Neurotrauma · doi:10.1089/neu.2014.3577 · Cited by 50
Spatio-temporal information analysis of event-related BOLD responses
Alpert, G. F., Sun, F. T., Handwerker, D. A., D’Esposito, M., & Knight, R. T. (2006) · NeuroImage · doi:10.1016/j.neuroimage.2006.10.020 · Cited by 46
Confounding effect of large vessels on MR perfusion images analyzed with independent component analysis.
Carroll, T. J., Haughton, V. M., Rowley, H. A., & Cordes, D. (2002) · PubMed Central · Cited by 45
Self-citation
Transition from rest to movement: Brain correlates revealed by functional connectivity
Treserras, S., Boulanouar, K., Conchou, F., Simonetta‐Moreau, M., Berry, I., Celsis, P., Chollet, F., & Loubinoux, I. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.06.016 · Cited by 45
Effect of Dopamine Transporter Genotype on Intrinsic Functional Connectivity Depends on Cognitive State
Gordon, E. M., Stollstorff, M., Devaney, J. M., Bean, S. E., & Vaidya, C. J. (2011) · Cerebral Cortex · doi:10.1093/cercor/bhr305 · Cited by 44
Disrupted amygdalar subregion functional connectivity and evidence for a compensatory network in generalized anxiety disorder
Etkin, A., Keller, K., Schatzberg, A. F., Menon, V., & Greicius, M. D. (2009) · NeuroImage · doi:10.1016/s1053-8119(09)70428-8 · Cited by 42
MODEL-FREE FUNCTIONAL MRI ANALYSIS USING TOPOGRAPHIC INDEPENDENT COMPONENT ANALYSIS
Meyer‐Baese, A., LANGE, O., Wismüller, A., & RITTER, H. (2004) · International Journal of Neural Systems · doi:10.1142/s0129065704002017 · Cited by 39
Aging and brain activation with working memory tasks: an fMRI study of connectivity
Cook, I. A., Bookheimer, S. Y., Mickes, L., Leuchter, A. F., & Kumar, A. (2007) · International Journal of Geriatric Psychiatry · doi:10.1002/gps.1678 · Cited by 39
Task-related, low-frequency task-residual, and resting state activity in the default mode network brain regions
Zhang, S., & Li, C.-S. R. (2012) · Frontiers in Psychology · doi:10.3389/fpsyg.2012.00172 · Cited by 37
Conditional correlation as a measure of mediated interactivity in fMRI and MEG/EEG
Marrelec, G., Jean Daunizeau, A., Pélégrini‐Issac, M., Doyon, J., & Benali, H. (2005) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2005.853211 · Cited by 38
Error-related functional connectivity of the thalamus in cocaine dependence
Zhang, S., Hu, S., Bednarski, S. R., Erdman, E., & Li, C. R. (2014) · NeuroImage Clinical · doi:10.1016/j.nicl.2014.01.015 · Cited by 37
Convergent approaches for defining functional imaging endophenotypes in schizophrenia
Pearlson, G. D. (2009) · Frontiers in Human Neuroscience · doi:10.3389/neuro.09.037.2009 · Cited by 35
A historical perspective on the evolution of resting-state functional connectivity with MRI
Lowe, M. J. (2010) · Magnetic Resonance Materials in Physics Biology and Medicine · doi:10.1007/s10334-010-0230-y · Cited by 38
Application of magnetic resonance imaging in animal models of perinatal hypoxic‐ischemic cerebral injury
Lodygensky, G. A., Inder, T. E., & Neil, J. J. (2007) · International Journal of Developmental Neuroscience · doi:10.1016/j.ijdevneu.2007.08.018 · Cited by 34
Parallel Alterations of Functional Connectivity during Execution and Imagination after Motor Imagery Learning
Zhang, H., Xu, L., Zhang, R., Hui, M., Long, Z., Zhao, X., & Yao, L. (2012) · PLoS ONE · doi:10.1371/journal.pone.0036052 · Cited by 33
Adolescent Gender Differences in Cognitive Control Performance and Functional Connectivity Between Default Mode and Fronto-Parietal Networks Within a Self-Referential Context
Alarcón, G., Pfeifer, J. H., Fair, D. A., & Nagel, B. J. (2018) · Frontiers in Behavioral Neuroscience · doi:10.3389/fnbeh.2018.00073 · Cited by 31

Authors: Arfanakis, K., Cordes, D., Haughton, V. M., Moritz, C. H., Quigley, M. A., & Meyerand, M. E.
Affiliations: University of Wisconsin–Madison (US)
Corresponding author: Arfanakis, Konstantinos
ORCID: Arfanakis, Konstantinos
Cordes, Dietmar
Haughton, Victor M
Moritz, Chad H
Meyerand, Mary E
Venue: Magnetic Resonance Imaging
Publisher: Elsevier BV
Published: 2000-10
Volume: 18
Issue: 8
Pages: 921-930
ISSN: 0730-725X (ISSN-L)
DOI: 10.1016/s0730-725x(00)00190-9
OpenAlex: W2066906403
Cited by: 191
References: 30
Citations by year: 2026: 1 · 2025: 2 · 2024: 2 · 2023: 2 · 2022: 4 · 2021: 4 · 2020: 3 · 2019: 2 · 2018: 6 · 2017: 3 · 2016: 4 · 2015: 7 · 2014: 15 · 2013: 16 · 2012: 9
FWCI: 2.68
Type: journal article
Language: en
Open access: closed
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations: Magnetic Resonance Imaging (publishedVersion)
PubMed (publishedVersion)
Topics: Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
Keywords: independent component analysis, correlation analysis, task-related brain activation, resting state, low-frequency fluctuations
MeSH terms: Adult, Auditory Cortex, Brain, Brain Mapping, Hemodynamics, Humans, Magnetic Resonance Imaging, Models, Neurological, Motor Cortex, Research, Time Factors, Visual Cortex, Databases as Topic

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Combining independent component analysis and correlation analysis to probe interregional connectivity in fMRI task activation datasets

Abstract

Overview

Integrity signals

Verification

Claims the paper makes

Claims other papers make about this one

Citations

Cites

Cited by

Related

Metadata

Record

About these checks