Review Article| Volume 30, ISSUE 1, P15-23, February 2020

Resting-State Functional Connectivity: Signal Origins and Analytic Methods

  • Kai Chen
    Affiliations
    The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, No.2006, Xiyuan Avenue, West Hi-Tech Zone, Chengdu, Sichuan 611731, China
    Search for articles by this author
  • Azeezat Azeez
    Affiliations
    Department of Biomedical Engineering, New Jersey Institute of Technology, 619 Fenster Hall, Newark, NJ 07102, USA
    Search for articles by this author
  • Donna Y. Chen
    Affiliations
    Department of Biomedical Engineering, New Jersey Institute of Technology, 619 Fenster Hall, Newark, NJ 07102, USA
    Search for articles by this author
  • Bharat B. Biswal
    Correspondence
    Corresponding author. The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, No.2006, Xiyuan Avenue, West Hi-Tech Zone, Chengdu, Sichuan 611731, China.
    Affiliations
    The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, Center for Information in Medicine, School of Life Science and Technology, University of Electronic Science and Technology of China, No.2006, Xiyuan Avenue, West Hi-Tech Zone, Chengdu, Sichuan 611731, China

    Department of Biomedical Engineering, New Jersey Institute of Technology, 619 Fenster Hall, Newark, NJ 07102, USA
    Search for articles by this author

      Keywords

      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'

      Subscribers receive full online access to your subscription and archive of back issues up to and including 2002.

      Content published before 2002 is available via pay-per-view purchase only.

      Subscribe:

      Subscribe to Neuroimaging Clinics
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect

      References

        • Lui S.
        • Zhou X.J.
        • Sweeney J.A.
        • et al.
        Psychoradiology: the frontier of neuroimaging in psychiatry.
        Radiology. 2016; 281: 357-372
        • Biswal B.
        • Yetkin F.Z.
        • Haughton V.M.
        • et al.
        Functional connectivity in the motor cortex of resting human brain using echo-planar MRI.
        Magn Reson Med. 1995; 34https://doi.org/10.1002/mrm.1910340409
        • Lowe M.J.
        • Rutecki P.
        • Turski P.
        • et al.
        Auditory cortex FMRI noise correlations in callosal agenesis.
        Neuroimage. 1997; 5: S194
        • Hampson M.
        • Peterson B.S.
        • Skuldarski P.
        • et al.
        Changes in functional connectivity using temporal correlations in MR images.
        Hum Brain Mapp. 2002; 15: 247
        • Hampson M.
        • Olson I.R.
        • Leung H.C.
        • et al.
        Changes in functional connectivity of human MT/V5 with visual motion input.
        Neuroreport. 2004; 7: 1315
      1. Xiong JP, Pu LM, Gao Y, et al. Improved interregional connectivity mapping by use of covariance analysis within rest condition. ISMRM Sixth Scientific Meeting & Exhibition. Sydney, Australia, April 18–24, 1998.

        • Xiong J.
        • Parsons L.M.
        • Gao J.H.
        • et al.
        Interregional connectivity to primary motor cortex revealed using MRI resting state images.
        Hum Brain Mapp. 1999; 8: 151-156
        • Zang Y.
        • Jiang T.
        • Lu Y.
        • et al.
        Regional homogeneity approach to fMRI data analysis.
        Neuroimage. 2004; 22: 394-400
        • Greicius M.D.
        • Srivastava G.
        • Reiss A.L.
        • et al.
        Default-mode network activity distinguishes Alzheimer's disease from healthy aging: evidence from functional MRI.
        Proc Natl Acad Sci U S A. 2004; 101: 4637-4642
        • Gusnard D.A.
        • Raichle M.E.
        Searching for a baseline: functional imaging and the resting human brain.
        Nat Rev Neurosci. 2001; 10: 685-694
        • Bressler S.
        Large-scale cortical networks and cognition.
        Brain Res Brain Res Rev. 1996; 20: 288-304
        • Friston K.J.
        • Frith C.D.
        • Liddle P.F.
        • et al.
        Functional connectivity: the principal component analysis of large (PET) data sets.
        J Cereb Blood Flow Metab. 1993; 13: 5
        • Cooper R.
        • Crow H.J.
        • Walter W.G.
        • et al.
        Regional control of cerebral vascular reactivity and oxygen supply in man.
        Brain Res. 1966; 3: 174
        • Hudetz A.G.
        • Roman R.J.
        • Harder D.R.
        Spontaneous flow oscillations in the cerebral cortex during acute changes in mean arterial pressure.
        J Cereb Blood Flow Metab. 1992; 12: 491
      2. Biswal B, Bandettini PA, Jesmanowicz A, et al. Time-frequency analysis of functional EPI time-course series. SMRM Twelfth Annual Scientific Meeting. New York, August 14–20, 1993.

      3. Weisskoff RM, Baker J, Belliveau J, et al. Poser spectrum analysis of functionally-weighted MR data: what’s in the noise? SMRM Twelfth Annual Scientific Meeting. New York, August 14–20, 1993.

        • Zonta M.
        • Angulo M.C.
        • Gobbo S.
        • et al.
        Neuron-to-astrocyte signaling is central to the dynamic control of brain microcirculation.
        Nat Neurosci. 2003; 6: 43-50
        • Biswal B.B.
        • Kannurpatti S.S.
        • Rypma B.
        Hemodynamic scaling of fMRI-BOLD signal: validation of low-frequency spectral amplitude as a scalability factor.
        Magn Reson Imaging. 2007; 25: 1358-1369
        • Mateo C.
        • Knutsen P.M.
        • Tsai P.S.
        • et al.
        Entrainment of arteriole vasomotor fluctuations by neural activity is a basis of blood-oxygenation-level-dependent "resting-state" connectivity.
        Neuron. 2017; 96 (936–948.e3)
        • Biswal B.B.
        • Van Kylen J.
        • Hyde J.S.
        Simultaneous assessment of flow and BOLD signals in resting-state functional connectivity maps.
        NMR Biomed. 1997; 10: 165-170
        • Biswal B.
        • Hudetz A.G.
        • Yetkin F.Z.
        • et al.
        Hypercapnia reversibly suppresses low-frequency fluctuations in the human motor cortex during rest using echo-planar MRI.
        J Cereb Blood Flow Metab. 1997; 17: 301
        • Gong Q.
        • Lui S.
        • Sweeney J.A.
        A selective review of cerebral abnormalities in patients with first-episode schizophrenia before and after treatment.
        Am J Psychiatry. 2016; 173: 232-243
        • Lui S.
        • Deng W.
        • Huang X.
        • et al.
        Association of cerebral deficits with clinical symptoms in antipsychotic-naive first-episode schizophrenia: an optimized voxel-based morphometry and resting state functional connectivity study.
        Am J Psychiatry. 2009; 166: 196-205
        • Tregellas J.
        Connecting brain structure and function in schizophrenia.
        Am J Psychiatry. 2009; 166: 134-136
        • Huang X.
        • Gong Q.
        • Sweeney J.A.
        • et al.
        Progress in psychoradiology, the clinical application of psychiatric neuroimaging.
        Br J Radiol. 2019; 92 (20181000)
        • Smitha K.A.
        • Akhil Raja K.
        • Arun K.M.
        • et al.
        Resting state fMRI: a review on methods in resting state connectivity analysis and resting state networks.
        Neuroradiol J. 2017; 30: 305-317
        • Azeez A.K.
        • Biswal B.B.
        A review of resting-state analysis methods.
        Neuroimaging Clin N Am. 2017; 27: 581-592
        • Huettel S.A.
        • Song A.W.
        • McCarthy G.
        Functional magnetic resonance imaging. vol. 1. Sinauer Associates, Sunderland (MA)2004
        • Beckmann C.F.
        • DeLuca M.
        • Devlin J.T.
        • et al.
        Investigations into resting-state connectivity using independent component analysis.
        Philos Trans R Soc Lond B Biol Sci. 2005; 360: 1001-1013
        • Zou Q.H.
        • Zhu C.Z.
        • Yang Y.
        • et al.
        An improved approach to detection of amplitude of low-frequency fluctuation (ALFF) for resting-state fMRI: fractional ALFF.
        J Neurosci Methods. 2008; 172: 137-141
        • Zuo X.N.
        • Di Martino A.
        • Kelly C.
        • et al.
        The oscillating brain: complex and reliable.
        Neuroimage. 2010; 49: 1432-1445
        • Li K.
        • Guo L.
        • Nie J.
        • et al.
        Review of methods for functional brain connectivity detection using fMRI.
        Comput Med Imaging Graph. 2009; 33: 131-139
        • Skudlarski P.
        • Gore J.C.
        Changes in the correlations in the FMRI physiological fluctuations may reveal functional connectivity within the brain.
        Neuroimage. 1998; 3: S600
      4. Biswal BB, Hyde JS. Functional connectivity during continuous task activation. ISMRM Sixth Scientific Meeting & Exhibition. Sydney, Australia, April 18–24, 1998. p. 2132.

        • Di X.
        • Gohel S.
        • Kim E.H.
        • et al.
        Task vs. rest-different network configurations between the coactivation and the resting-state brain networks.
        Front Hum Neurosci. 2013; 7: 493
        • Smith S.M.
        • Fox P.T.
        • Miller K.L.
        • et al.
        Correspondence of the brain's functional architecture during activation and rest.
        Proc Natl Acad Sci U S A. 2009; 106: 13040-13045
        • Grady C.L.
        • McIntosh A.R.
        • Horwitz B.
        • et al.
        Age-related reductions in human recognition memory due to impaired encoding.
        Science. 1995; 269: 218-221
        • Rypma B.
        • D'Esposito M.
        Isolating the neural mechanisms of age-related changes in human working memory.
        Nat Neurosci. 2000; 3: 509-515
        • Rypma B.
        • Prabhakaran V.
        • Desmond J.E.
        • et al.
        Age differences in prefrontal cortical activity in working memory.
        Psychol Aging. 2001; 16: 371-384
        • Satterthwaite T.D.
        • Elliott M.A.
        • Gerraty R.T.
        • et al.
        An improved framework for confound regression and filtering for control of motion artifact in the preprocessing of resting-state functional connectivity data.
        Neuroimage. 2013; 64: 240-256
        • Cabeza R.
        Hemispheric asymmetry reduction in older adults: the HAROLD model.
        Psychol Aging. 2002; 17: 85-100
        • Rypma B.
        • Berger J.S.
        • Genova H.
        • et al.
        Dissociating age-related changes in cognitive strategy and neural efficiency using event-related fMRI.
        Cortex. 2005; 41: 582-594
        • Hasher L.
        • Stoltzfus E.R.
        • Zacks R.T.
        • et al.
        Age and inhibition.
        J Exp Psychol Learn Mem Cogn. 1991; 17: 163-169
        • Buchel C.
        • Friston K.
        Assessing interactions among neuronal systems using functional neuroimaging.
        Neural Netw. 2000; 13: 871-882
        • Goebel R.
        • Roebroeck A.
        • Kim D.S.
        • et al.
        Investigating directed cortical interactions in time-resolved fMRI data using vector autoregressive modeling and Granger causality mapping.
        Magn Reson Imaging. 2003; 21: 1251-1261
        • McIntosh A.R.
        • Rajah M.N.
        • Lobaugh N.J.
        Interactions of prefrontal cortex in relation to awareness in sensory learning.
        Science. 1999; 284: 1531-1533
        • Posner M.I.
        • Petersen S.E.
        The attention system of the human brain.
        Annu Rev Neurosci. 1990; 13: 25-42
        • Corbetta M.
        • Shulman G.L.
        Human cortical mechanisms of visual attention during orienting and search.
        Philos Trans R Soc Lond B Biol Sci. 1998; 353: 1353-1362
        • Bunge S.A.
        • Dudukovic N.M.
        • Thomason M.E.
        • et al.
        Immature frontal lobe contributions to cognitive control in children: evidence from fMRI.
        Neuron. 2002; 33: 301-311
        • Vaidya C.J.
        • Bunge S.A.
        • Dudukovic N.M.
        • et al.
        Altered neural substrates of cognitive control in childhood ADHD: evidence from functional magnetic resonance imaging.
        Am J Psychiatry. 2005; 162: 1605-1613
        • Vaidya C.J.
        • Austin G.
        • Kirkorian G.
        • et al.
        Selective effects of methylphenidate in attention deficit hyperactivity disorder: a functional magnetic resonance study.
        Proc Natl Acad Sci U S A. 1999; 95: 14494-14499
        • Aman C.J.
        • Roberts R.J.
        • Pennington B.F.
        A neuropsychological examination of the underlying deficit in attention deficit hyperactivity disorder: frontal lobe versus right parietal lobe theories.
        Dev Psychol. 1998; 34: 956-969
        • Backman L.
        • Jones S.
        • Berger A.K.
        • et al.
        Cognitive impairment in preclinical Alzheimer’s disease: a meta-analysis.
        Neuropsychology. 2005; 19: 520-531
        • Drzezga A.
        • Grimmer T.
        • Peller M.
        • et al.
        Impaired cross-modal inhibition in Alzheimer’s Disease.
        PLoS Med. 2005; 2: 288
        • Rosler A.
        • Mapstone M.
        • Hays-Wicklund A.
        • et al.
        The "zoom lens" of focal attention in visual search: changes in aging and Alzheimer's disease.
        Cortex. 2005; 41: 512-519
        • Power J.D.
        • Barnes K.A.
        • Snyder A.Z.
        • et al.
        Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion.
        Neuroimage. 2012; 59: 2142-2154
        • Power J.D.
        • Mitra A.
        • Laumann T.O.
        • et al.
        Methods to detect, characterize, and remove motion artifact in resting state fMRI.
        Neuroimage. 2014; 84: 320-341
        • Van Dijk K.R.
        • Sabuncu M.R.
        • Buckner R.L.
        The influence of head motion on intrinsic functional connectivity MRI.
        Neuroimage. 2012; 59: 431-438
        • Satterthwaite T.D.
        • Wolf D.H.
        • Ruparel K.
        • et al.
        Heterogeneous impact of motion on fundamental patterns of developmental changes in functional connectivity during youth.
        Neuroimage. 2013; 83: 45-57
        • Murphy K.
        • Fox M.D.
        Towards a consensus regarding global signal regression for resting state functional connectivity MRI.
        Neuroimage. 2017; 154: 169-173
        • Scholvinck M.L.
        • Maier A.
        • Ye F.Q.
        • et al.
        Neural basis of global resting-state fMRI activity.
        Proc Natl Acad Sci U S A. 2010; 107: 10238-10243
        • Wen H.
        • Liu Z.
        Broadband electrophysiological dynamics contribute to global resting-state fMRI signal.
        J Neurosci. 2016; 36: 6030-6040
        • Han Y.
        • Wang J.
        • Zhao Z.
        • et al.
        Frequency-dependent changes in the amplitude of low-frequency fluctuations in amnestic mild cognitive impairment: a resting-state fMRI study.
        Neuroimage. 2011; 55: 287-295
        • Zuo X.N.
        • Anderson J.S.
        • Bellec P.
        • et al.
        An open science resource for establishing reliability and reproducibility in functional connectomics.
        Sci Data. 2014; 1: 140049
        • Birn R.M.
        • Molloy E.K.
        • Patriat R.
        • et al.
        The effect of scan length on the reliability of resting-state fMRI connectivity estimates.
        Neuroimage. 2013; 83: 550-558
        • Van Dijk K.R.
        • Hedden T.
        • Venkataraman A.
        • et al.
        Intrinsic functional connectivity as a tool for human connectomics: theory, properties, and optimization.
        J Neurophysiol. 2010; 103: 297-321
        • Drysdale A.T.
        • Grosenick L.
        • Downar J.
        • et al.
        Resting-state connectivity biomarkers define neurophysiological subtypes of depression.
        Nat Med. 2017; 23: 28-38
        • Sun H.
        • Lui S.
        • Yao L.
        • et al.
        Two patterns of white matter abnormalities in medication-naive patients with first-episode schizophrenia revealed by diffusion tensor imaging and cluster analysis.
        JAMA Psychiatry. 2015; 72: 678-686
        • Fox M.D.
        • Greicius M.
        Clinical applications of resting state functional connectivity.
        Front Syst Neurosci. 2010; 4: 19
        • Boubela R.N.
        • Kalcher K.
        • Huf W.
        • et al.
        Beyond noise: using temporal ICA to extract meaningful information from high-frequency fMRI signal fluctuations during rest.
        Front Hum Neurosci. 2013; 7: 168
        • Cordes D.
        • Haughton V.M.
        • Arfanakis K.
        • et al.
        Frequencies contributing to functional connectivity in the cerebral cortex in "resting-state" data.
        AJNR Am J Neuroradiol. 2001; 22: 1326-1333
        • Gohel S.R.
        • Biswal B.B.
        Functional integration between brain regions at rest occurs in multiple-frequency bands.
        Brain Connect. 2015; 5: 23-34
        • Lee H.-L.
        • Zahneisen B.
        • Hugger T.
        • et al.
        Tracking dynamic resting-state networks at higher frequencies using MR-encephalography.
        Neuroimage. 2013; 65: 216-222
        • Wu C.W.
        • Gu H.
        • Lu H.
        • et al.
        Frequency specificity of functional connectivity in brain networks.
        Neuroimage. 2008; 42: 1047-1055
        • Gong Q.
        • Response to Sarpal
        • et al.
        Importance of neuroimaging biomarkers for treatment development and clinical practice.
        Am J Psychiatry. 2016; 173: 733-734
        • Kressel H.Y.
        Setting Sail 2017.
        Radiology. 2017; 282: 4-6
        • Port J.D.
        Diagnosis of attention deficit hyperactivity disorder by using mr imaging and radiomics: a potential tool for clinicians.
        Radiology. 2018; 287: 631-632
        • van Beek E.J.R.
        • Kuhl C.
        • Anzai Y.
        • et al.
        Value of MRI in medicine: More than just another test? J Magn Reson Imaging. 2019; 49: e14-e25