Assessing dynamic brain graphs of time-varying connectivity in fMRI data: Application to healthy controls and patients with schizophrenia

NeuroImage

Volumn 107, Issue , 2015, Pages 345-355

  Yu, Qingbao ^a   Erhardt, Erik B ^b   Sui, Jing ^a,c   Du, Yuhui ^a,d   He, Hao ^a,e   Hjelm, Devon ^a,e   Cetin, Mustafa S ^a,e   Rachakonda, Srinivas ^a   Miller, Robyn L ^a   Pearlson, Godfrey ^f,g   Calhoun, Vince D ^a,e,f,g  

^a MIND RESEARCH NETWORK   (United States)

^b UNIVERSITY OF NEW MEXICO   (United States)

^c INSTITUTE OF AUTOMATION   (China)

^d NORTH UNIVERSITY OF CHINA   (China)

^e MSC01 1070   (United States)

^f INSTITUTE OF LIVING   (United States)

^g YALE UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

Brain graph; Dynamic; ICA; R fMRI; Schizophrenia; Time varying

Indexed keywords

ADULT; ARTICLE; AUDITORY SYSTEM FUNCTION; BRAIN FUNCTION; BRAIN MAPPING; CONCEPTUAL FRAMEWORK; CONTROLLED STUDY; CORRELATIONAL STUDY; DATA ANALYSIS; DYNAMIC BRAIN GRAPH METRICS; EXECUTIVE FUNCTION; FEMALE; FUNCTIONAL ANATOMY; FUNCTIONAL MAGNETIC RESONANCE IMAGING; HISTOGRAM; HUMAN; IMAGE PROCESSING; IMAGING SOFTWARE; INDEPENDENT COMPONENT ANALYSIS; MAJOR CLINICAL STUDY; MALE; MATHEMATICAL COMPUTING; MATHEMATICAL MODEL; MIDDLE AGED; MORPHOMETRICS; NERVE CELL PLASTICITY; NEUROIMAGING; PREDICTIVE VALUE; RESTING STATE NETWORK; SCHIZOPHRENIA; SENSORIMOTOR FUNCTION; SYNAPTIC TRANSMISSION; YOUNG ADULT; ADOLESCENT; AGED; ALGORITHM; BRAIN; NERVE TRACT; NUCLEAR MAGNETIC RESONANCE IMAGING; PATHOLOGY; PROCEDURES; STATISTICS AND NUMERICAL DATA;

ADOLESCENT; ADULT; AGED; ALGORITHMS; BRAIN; BRAIN MAPPING; FEMALE; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; MAGNETIC RESONANCE IMAGING; MALE; MIDDLE AGED; NEURAL PATHWAYS; SCHIZOPHRENIA; YOUNG ADULT;

EID: 84920913022     PISSN: 10538119     EISSN: 10959572     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2014.12.020     Document Type: Article

References (128)

1. Abou Elseoud A., Littow H., Remes J., Starck T., Nikkinen J., Nissila J., Timonen M., Tervonen O., Kiviniemi V. Group-ICA model order highlights patterns of functional brain connectivity. Front. Syst. Neurosci. 2011, 5:37.
2. Abou-Elseoud A., Starck T., Remes J., Nikkinen J., Tervonen O., Kiviniemi V. The effect of model order selection in group PICA. Hum. Brain Mapp. 2010, 31:1207-1216.
3. Allen E.A., Erhardt E.B., Damaraju E., Gruner W., Segall J.M., Silva R.F., Havlicek M., Rachakonda S., Fries J., Kalyanam R., Michael A.M., Caprihan A., Turner J.A., Eichele T., Adelsheim S., Bryan A.D., Bustillo J., Clark V.P., Feldstein Ewing S.W., Filbey F., Ford C.C., Hutchison K., Jung R.E., Kiehl K.A., Kodituwakku P., Komesu Y.M., Mayer A.R., Pearlson G.D., Phillips J.P., Sadek J.R., Stevens M., Teuscher U., Thoma R.J., Calhoun V.D. A baseline for the multivariate comparison of resting-state networks. Front. Syst. Neurosci. 2011, 5:2.
4. Allen E.A., Erhardt E.B., Wei Y., Eichele T., Calhoun V.D. Capturing inter-subject variability with group independent component analysis of fMRI data: a simulation study. Neuroimage 2012, 59:4141-4159.
5. Allen E.A., Damaraju E., Plis S.M., Erhardt E.B., Eichele T., Calhoun V.D. Tracking whole-brain connectivity dynamics in the resting state. Cereb. Cortex 2014, 24:663-676.
6. Amft M., Bzdok D., Laird A.R., Fox P.T., Schilbach L., Eickhoff S.B. Definition and characterization of an extended social-affective default network. Brain Struct. Funct. 2014, (in press). 10.1007/s00429-013-0698-0.
7. Andreasen N.C., Pressler M., Nopoulos P., Miller D., Ho B.C. Antipsychotic dose equivalents and dose-years: a standardized method for comparing exposure to different drugs. Biol. Psychiatry 2010, 67:255-262.
8. Balsters J.H., Laird A.R., Fox P.T., Eickhoff S.B. Bridging the gap between functional and anatomical features of cortico-cerebellar circuits using meta-analytic connectivity modeling. Hum. Brain Mapp 2014, 35:3152-3169.
9. Bassett D.S., Gazzaniga M.S. Understanding complexity in the human brain. Trends Cogn. Sci. 2011, 15:200-209.
10. Bassett D.S., Wymbs N.F., Porter M.A., Mucha P.J., Carlson J.M., Grafton S.T. Dynamic reconfiguration of human brain networks during learning. Proc. Natl. Acad. Sci. U. S. A. 2011, 108:7641-7646.
11. Bassett D.S., Nelson B.G., Mueller B.A., Camchong J., Lim K.O. Altered resting state complexity in schizophrenia. Neuroimage 2012, 59:2196-2207.
12. Bell A.J., Sejnowski T.J. An information-maximization approach to blind separation and blind deconvolution. Neural Comput. 1995, 7:1129-1159.
13. Biswal B., Yetkin F.Z., Haughton V.M., Hyde J.S. Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magn. Reson. Med. 1995, 34:537-541.
14. Bockholt H.J., Scully M., Courtney W., Rachakonda S., Scott A., Caprihan A., Fries J., Kalyanam R., Segall J.M., de la Garza R., Lane S., Calhoun V.D. Mining the mind research network: a novel framework for exploring large scale, heterogeneous translational neuroscience research data sources. Front. Neuroinform. 2010, 3:36.
15. Bridwell D.A., Wu L., Eichele T., Calhoun V.D. The spatiospectral characterization of brain networks: fusing concurrent EEG spectra and fMRI maps. Neuroimage 2013, 69:101-111.
16. Buckner R.L., Andrews-Hanna J.R., Schacter D.L. The brain's default network: anatomy, function, and relevance to disease. Ann. N. Y. Acad. Sci. 2008, 1124:1-38.
17. Buckner R.L., Sepulcre J., Talukdar T., Krienen F.M., Liu H., Hedden T., Andrews-Hanna J.R., Sperling R.A., Johnson K.A. Cortical hubs revealed by intrinsic functional connectivity: mapping, assessment of stability, and relation to Alzheimer's disease. J. Neurosci. 2009, 29:1860-1873.
18. Cabral J., Kringelbach M.L., Deco G. Exploring the network dynamics underlying brain activity during rest. Prog. Neurobiol. 2014, 114:102-131.
19. Calhoun V.D., Adali T. Multisubject independent component analysis of fMRI: a decade of intrinsic networks, default mode, and neurodiagnostic discovery. IEEE Rev. Biomed. Eng. 2012, 5:60-73.
20. Calhoun V.D., Adali T., Pearlson G.D., Pekar J.J. A method for making group inferences from functional MRI data using independent component analysis. Hum. Brain Mapp. 2001, 14:140-151.
21. Calhoun V.D., Adali T., Kiehl K.A., Astur R., Pekar J.J., Pearlson G.D. A method for multitask fMRI data fusion applied to schizophrenia. Hum. Brain Mapp. 2006, 27:598-610.
22. Calhoun V.D., Kiehl K.A., Pearlson G.D. Modulation of temporally coherent brain networks estimated using ICA at rest and during cognitive tasks. Hum. Brain Mapp. 2008, 29:828-838.
23. Calhoun V.D., Eichele T., Pearlson G. Functional brain networks in schizophrenia: a review. Front. Hum. Neurosci. 2009, 3:17.
24. Calhoun V.D., Liu J., Adali T. A review of group ICA for fMRI data and ICA for joint inference of imaging, genetic, and ERP data. Neuroimage 2009, 45:S163-S172.
25. Calhoun V.D., Eichele T., Adali T., Allen E.A. Decomposing the brain: components and modes, networks and nodes. Trends Cogn. Sci. 2012, 16:255-256.
26. Chang C., Glover G.H. Time-frequency dynamics of resting-state brain connectivity measured with fMRI. Neuroimage 2010, 50:81-98.
27. Cordes D., Haughton V.M., Arfanakis K., Wendt G.J., Turski P.A., Moritz C.H., Quigley M.A., Meyerand M.E. Mapping functionally related regions of brain with functional connectivity MR imaging. AJNR Am. J. Neuroradiol. 2000, 21:1636-1644.
28. Craddock R.C., James G.A., Holtzheimer P.E., Hu X.P., Mayberg H.S. A whole brain fMRI atlas generated via spatially constrained spectral clustering. Hum. Brain Mapp. 2012, 33:1914-1928.
29. Cribben I., Haraldsdottir R., Atlas L.Y., Wager T.D., Lindquist M.A. Dynamic connectivity regression: determining state-related changes in brain connectivity. Neuroimage 2012, 61:907-920.
30. Damaraju E., Allen E., Calhoun V. Impact of head motion on ICA-derived functional connectivity measures. Fourth Biennial Conference on Resting State/Brain Connectivity Boston, MA 2014.
31. de Reus M.A., van den Heuvel M.P. The parcellation-based connectome: limitations and extensions. Neuroimage 2013, 80:397-404.
32. Du Y., Fan Y. Group information guided ICA for fMRI data analysis. Neuroimage 2013, 69:157-197.
33. Eguiluz V.M., Chialvo D.R., Cecchi G.A., Baliki M., Apkarian A.V. Scale-free brain functional networks. Phys. Rev. Lett. 2005, 94:018102.
34. Erhardt E.B., Rachakonda S., Bedrick E.J., Allen E.A., Adali T., Calhoun V.D. Comparison of multi-subject ICA methods for analysis of fMRI data. Hum. Brain Mapp. 2011, 32:2075-2095.
35. Esposito F., Bertolino A., Scarabino T., Latorre V., Blasi G., Popolizio T., Tedeschi G., Cirillo S., Goebel R., Di Salle F. Independent component model of the default-mode brain function: assessing the impact of active thinking. Brain Res. Bull. 2006, 70:263-269.
36. First M.B., Spitzer R.L., Gibbon M., Williams J.B.W. Structured Clinical Interview for DSM-IV Axis I Disorders-Patient Edition (SCID-I/P, Version 2.0) 1995, New York State Psychiatry Institute, New York.
37. Fornito A., Zalesky A., Bullmore E.T. Network scaling effects in graph analytic studies of human resting-state FMRI data. Front. Syst. Neurosci. 2010, 4:22.
38. Fornito A., Harrison B.J., Zalesky A., Simons J.S. Competitive and cooperative dynamics of large-scale brain functional networks supporting recollection. Proc. Natl. Acad. Sci. U. S. A. 2012, 109:12788-12793.
39. Fornito A., Zalesky A., Pantelis C., Bullmore E.T. Schizophrenia, neuroimaging and connectomics. Neuroimage 2012, 62:2296-2314.
40. Fornito A., Zalesky A., Breakspear M. Graph analysis of the human connectome: promise, progress, and pitfalls. Neuroimage 2013, 80:426-444.
41. Fox M.D., Snyder A.Z., Vincent J.L., Corbetta M., Van Essen D.C., Raichle M.E. The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proc. Natl. Acad. Sci. U. S. A. 2005, 102:9673-9678.
42. Fox M.D., Corbetta M., Snyder A.Z., Vincent J.L., Raichle M.E. Spontaneous neuronal activity distinguishes human dorsal and ventral attention systems. Proc. Natl. Acad. Sci. U. S. A. 2006, 103:10046-10051.
43. Fransson P. How default is the default mode of brain function? Further evidence from intrinsic BOLD signal fluctuations. Neuropsychologia 2006, 44:2836-2845.
44. Freire L., Roche A., Mangin J.F. What is the best similarity measure for motion correction in fMRI time series?. IEEE Trans. Med. Imaging 2002, 21:470-484.
45. Friston K.J., Frith C.D. Schizophrenia: a disconnection syndrome?. Clin. Neurosci. 1995, 3:89-97.
46. Fu Z., Di X., Chan S.C., Hung Y.S., Biswal B.B., Zhang Z. Time-varying correlation coefficients estimation and its application to dynamic connectivity analysis of fMRI. IEEE Engineering in Medicine and Biology Society. Conference 2013 2013, 2944-2947.
47. Fusar-Poli P., Smieskova R., Kempton M.J., Ho B.C., Andreasen N.C., Borgwardt S. Progressive brain changes in schizophrenia related to antipsychotic treatment? A meta-analysis of longitudinal MRI studies. Neurosci. Biobehav. Rev. 2013, 37:1680-1691.
48. Garrett D.D., Kovacevic N., McIntosh A.R., Grady C.L. The modulation of BOLD variability between cognitive states varies by age and processing speed. Cereb. Cortex 2013, 23:684-693.
49. Golub G.H., Van Loan C.F. Matrix computations 1996, 21218-24319. Johns Hopkins University Press, 2715 North Charles Street, Baltimore, Maryland.
50. Greicius M.D., Krasnow B., Reiss A.L., Menon V. Functional connectivity in the resting brain: a network analysis of the default mode hypothesis. Proc. Natl. Acad. Sci. U. S. A. 2003, 100:253-258.
51. Hagmann P., Cammoun L., Gigandet X., Meuli R., Honey C.J., Wedeen V.J., Sporns O. Mapping the structural core of human cerebral cortex. PLoS Biol. 2008, 6:e159.
52. Handley R., Zelaya F.O., Reinders A.A., Marques T.R., Mehta M.A., O'Gorman R., Alsop D.C., Taylor H., Johnston A., Williams S., McGuire P., Pariante C.M., Kapur S., Dazzan P. Acute effects of single-dose aripiprazole and haloperidol on resting cerebral blood flow (rCBF) in the human brain. Hum. Brain Mapp. 2013, 34:272-282.
53. He H., Sui J., Yu Q., Turner J.A., Ho B.C., Sponheim S.R., Manoach D.S., Clark V.P., Calhoun V.D. Altered small-world brain networks in schizophrenia patients during working memory performance. PLoS One 2012, 7:e38195.
54. Heinrichs R.W., Zakzanis K.K. Neurocognitive deficit in schizophrenia: a quantitative review of the evidence. Neuropsychology 1998, 12:426-445.
55. Hennings K., Lelic D., Petrini L. An automated method for micro-state segmentation of evoked potentials. J. Neurosci. Methods 2009, 177:225-231.
56. Hermundstad A.M., Bassett D.S., Brown K.S., Aminoff E.M., Clewett D., Freeman S., Frithsen A., Johnson A., Tipper C.M., Miller M.B., Grafton S.T., Carlson J.M. Structural foundations of resting-state and task-based functional connectivity in the human brain. Proc. Natl. Acad. Sci. U. S. A. 2013, 110:6169-6174.
57. Horovitz S.G., Fukunaga M., de Zwart J.A., van Gelderen P., Fulton S.C., Balkin T.J., Duyn J.H. Low frequency BOLD fluctuations during resting wakefulness and light sleep: a simultaneous EEG-fMRI study. Hum. Brain Mapp. 2008, 29:671-682.
58. Horovitz S.G., Braun A.R., Carr W.S., Picchioni D., Balkin T.J., Fukunaga M., Duyn J.H. Decoupling of the brain's default mode network during deep sleep. Proc. Natl. Acad. Sci. U. S. A. 2009, 106:11376-11381.
59. Hutchison R.M., Womelsdorf T., Allen E.A., Bandettini P.A., Calhoun V.D., Corbetta M., Della Penna S., Duyn J.H., Glover G.H., Gonzalez-Castillo J., Handwerker D.A., Keilholz S., Kiviniemi V., Leopold D.A., de Pasquale F., Sporns O., Walter M., Chang C. Dynamic functional connectivity: promise, issues, and interpretations. Neuroimage 2013, 80:360-378.
60. Hutchison R.M., Womelsdorf T., Gati J.S., Everling S., Menon R.S. Resting-state networks show dynamic functional connectivity in awake humans and anesthetized macaques. Hum. Brain Mapp. 2013, 34:2154-2177.
61. Jafri M.J., Pearlson G.D., Stevens M., Calhoun V.D. A method for functional network connectivity among spatially independent resting-state components in schizophrenia. Neuroimage 2008, 39:1666-1681.
62. Jones D.T., Vemuri P., Murphy M.C., Gunter J.L., Senjem M.L., Machulda M.M., Przybelski S.A., Gregg B.E., Kantarci K., Knopman D.S., Boeve B.F., Petersen R.C., Jack C.R. Non-stationarity in the "resting brain's" modular architecture. PLoS One 2012, 7:e39731.
63. Kang J., Wang L., Yan C., Wang J., Liang X., He Y. Characterizing dynamic functional connectivity in the resting brain using variable parameter regression and Kalman filtering approaches. Neuroimage 2011, 56:1222-1234.
64. Kay S.R., Fiszbein A., Opler L.A. The positive and negative syndrome scale (PANSS) for schizophrenia. Schizophr. Bull. 1987, 13:261-276.
65. Keilholz S.D., Magnuson M.E., Pan W.J., Willis M., Thompson G.J. Dynamic properties of functional connectivity in the rodent. Brain Connect. 2013, 3:31-40.
66. Kiviniemi V., Starck T., Remes J., Long X., Nikkinen J., Haapea M., Veijola J., Moilanen I., Isohanni M., Zang Y.F., Tervonen O. Functional segmentation of the brain cortex using high model order group PICA. Hum. Brain Mapp. 2009, 30:3865-3886.
67. Kiviniemi V., Vire T., Remes J., Elseoud A.A., Starck T., Tervonen O., Nikkinen J. A sliding time-window ICA reveals spatial variability of the default mode network in time. Brain Connect. 2011, 1:339-347.
68. Koenig T., Prichep L., Lehmann D., Sosa P.V., Braeker E., Kleinlogel H., Isenhart R., John E.R. Millisecond by millisecond, year by year: normative EEG microstates and developmental stages. Neuroimage 2002, 16:41-48.
69. Kohn N., Eickhoff S.B., Scheller M., Laird A.R., Fox P.T., Habel U. Neural network of cognitive emotion regulation-an ALE meta-analysis and MACM analysis. Neuroimage 2014, 87:345-355.
70. Lehmann D., Skrandies W. Spatial-analysis of evoked-potentials in man-a review. Prog. Neurobiol. 1984, 23:227-250.
71. Lehmann D., Strik W.K., Henggeler B., Koenig T., Koukkou M. Brain electric microstates and momentary conscious mind states as building blocks of spontaneous thinking: I. Visual imagery and abstract thoughts. Int. J. Psychophysiol. 1998, 29:1-11.
72. Leonardi N., Richiardi J., Gschwind M., Simioni S., Annoni J.M., Schluep M., Vuilleumier P., Van De Ville D. Principal components of functional connectivity:a new approach to study dynamic brain connectivity during rest. Neuroimage 2013, 83:937-950.
73. Leucht S., Samara M., Heres S., Patel M.X., Woods S.W., Davis J.M. Dose equivalents for second-generation antipsychotics: the minimum effective dose method. Schizophr. Bull. 2014, 40:314-326.
74. Li X., Lim C., Li K., Guo L., Liu T. Detecting brain state changes via fiber-centered functional connectivity analysis. Neuroinformatics 2013, 11:193-210.
75. Li X., Zhu D., Jiang X., Jin C., Zhang X., Guo L., Zhang J., Hu X., Li L., Liu T. Dynamic functional connectomics signatures for characterization and differentiation of PTSD patients. Hum. Brain Mapp. 2014, 35:1761-1778.
76. Liang X., Zou Q., He Y., Yang Y. Coupling of functional connectivity and regional cerebral blood flow reveals a physiological basis for network hubs of the human brain. Proc. Natl. Acad. Sci. U. S. A. 2013, 110:1929-1934.
77. Liu Y., Liang M., Zhou Y., He Y., Hao Y., Song M., Yu C., Liu H., Liu Z., Jiang T. Disrupted small-world networks in schizophrenia. Brain 2008, 131:945-961.
78. Lynall M.E., Bassett D.S., Kerwin R., McKenna P.J., Kitzbichler M., Muller U., Bullmore E. Functional connectivity and brain networks in schizophrenia. J. Neurosci. 2010, 30:9477-9487.
79. Ma S., Calhoun V.D., Phlypo R., Adali T. Dynamic changes of spatial functional network connectivity in healthy individuals and schizophrenia patients using independent vector analysis. Neuroimage 2014, 90:196-206.
80. Madhyastha T.M., Askren M.K., Boord P., Grabowski T.J. Dynamic connectivity at rest predicts attention task performance. Brain Connect. 2014, (in press). 10.1089/brain.2014.0248.
81. Marin O. Interneuron dysfunction in psychiatric disorders. Nat. Rev. Neurosci. 2012, 13:107-120.
82. Mason M.J., Fan G., Plath K., Zhou Q., Horvath S. Signed weighted gene co-expression network analysis of transcriptional regulation in murine embryonic stem cells. BMC Genomics 2009, 10:327.
83. McKeown M.J., Makeig S., Brown G.G., Jung T.P., Kindermann S.S., Bell A.J., Sejnowski T.J. Analysis of fMRI data by blind separation into independent spatial components. Hum. Brain Mapp. 1998, 6:160-188.
84. Meda S.A., Gill A., Stevens M.C., Lorenzoni R.P., Glahn D.C., Calhoun V.D., Sweeney J.A., Tamminga C.A., Keshavan M.S., Thaker G., Pearlson G.D. Differences in resting-state functional magnetic resonance imaging functional network connectivity between schizophrenia and psychotic bipolar probands and their unaffected first-degree relatives. Biol. Psychiatry 2012, 71:881-889.
85. Mulert C. Simultaneous EEG and fMRI: towards the characterization of structure and dynamics of brain networks. Dialogues Clin. Neurosci. 2013, 15:381-386.
86. Mumford J.A., Horvath S., Oldham M.C., Langfelder P., Geschwind D.H., Poldrack R.A. Detecting network modules in fMRI time series: a weighted network analysis approach. Neuroimage 2010, 52:1465-1476.
87. Mutlu A.Y., Bernat E., Aviyente S. A signal-processing-based approach to time-varying graph analysis for dynamic brain network identification. Comput. Math. Methods Med. 2012, 2012:451516.
88. Nejad A.B., Ebdrup B.H., Glenthoj B.Y., Siebner H.R. Brain connectivity studies in schizophrenia: unravelling the effects of antipsychotics. Curr. Neuropharmacol. 2012, 10:219-230.
89. Newman M.E. Modularity and community structure in networks. Proc. Natl. Acad. Sci. U. S. A. 2006, 103:8577-8582.
90. Pascualmarqui R.D., Michel C.M., Lehmann D. Segmentation of brain electrical-activity into microstates-model estimation and validation. IEEE Trans. Biomed. Eng. 1995, 42:658-665.
91. Patel M.X., Arista I.A., Taylor M., Barnes T.R. How to compare doses of different antipsychotics: a systematic review of methods. Schizophr. Res. 2013, 149:141-148.
92. Ptak R. The frontoparietal attention network of the human brain: action, saliency, and a priority map of the environment. Neuroscientist 2012, 18:502-515.
93. Raichle M.E., MacLeod A.M., Snyder A.Z., Powers W.J., Gusnard D.A., Shulman G.L. A default mode of brain function. Proc. Natl. Acad. Sci. U. S. A. 2001, 98:676-682.
94. Rehme A.K., Eickhoff S.B., Rottschy C., Fink G.R., Grefkes C. Activation likelihood estimation meta-analysis of motor-related neural activity after stroke. Neuroimage 2012, 59:2771-2782.
95. Rottschy C., Langner R., Dogan I., Reetz K., Laird A.R., Schulz J.B., Fox P.T., Eickhoff S.B. Modelling neural correlates of working memory: a coordinate-based meta-analysis. Neuroimage 2012, 60:830-846.
96. Rubinov M., Sporns O. Complex network measures of brain connectivity: uses and interpretations. Neuroimage 2010, 52:1059-1069.
97. Sakoglu U., Pearlson G.D., Kiehl K.A., Wang Y.M., Michael A.M., Calhoun V.D. A method for evaluating dynamic functional network connectivity and task-modulation: application to schizophrenia. MAGMA 2010, 23:351-366.
98. Seeley W.W., Menon V., Schatzberg A.F., Keller J., Glover G.H., Kenna H., Reiss A.L., Greicius M.D. Dissociable intrinsic connectivity networks for salience processing and executive control. J. Neurosci. 2007, 27:2349-2356.
99. Shirer W.R., Ryali S., Rykhlevskaia E., Menon V., Greicius M.D. Decoding subject-driven cognitive states with whole-brain connectivity patterns. Cereb. Cortex 2012, 22:158-165.
100. 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., Beckmann C.F. Correspondence of the brain's functional architecture during activation and rest. Proc. Natl. Acad. Sci. U. S. A. 2009, 106:13040-13045.
101. Smith S.M., Miller K.L., Salimi-Khorshidi G., Webster M., Beckmann C.F., Nichols T.E., Ramsey J.D., Woolrich M.W. Network modelling methods for FMRI. Neuroimage 2011, 54:875-891.
102. Spreng R.N., Schacter D.L. Default network modulation and large-scale network interactivity in healthy young and old adults. Cereb. Cortex 2012, 22:2610-2621.
103. Stephan K.E., Baldeweg T., Friston K.J. Synaptic plasticity and dysconnection in schizophrenia. Biol. Psychiatry 2006, 59:929-939.
104. Sui J., Huster R., Yu Q., Segall J.M., Calhoun V.D. Function-structure associations of the brain: evidence from multimodal connectivity and covariance studies. Neuroimage 2014, 102:11-23.
105. Telesford Q.K., Simpson S.L., Burdette J.H., Hayasaka S., Laurienti P.J. The brain as a complex system: using network science as a tool for understanding the brain. Brain Connect. 2011, 1:295-308.
106. Thompson G.J., Magnuson M.E., Merritt M.D., Schwarb H., Pan W.J., McKinley A., Tripp L.D., Schumacher E.H., Keilholz S.D. Short-time windows of correlation between large-scale functional brain networks predict vigilance intraindividually and interindividually. Hum. Brain Mapp. 2013, 34:3280-3298.
107. Thompson G.J., Merritt M.D., Pan W.J., Magnuson M.E., Grooms J.K., Jaeger D., Keilholz S.D. Neural correlates of time-varying functional connectivity in the rat. Neuroimage 2013, 83:826-836.
108. Thompson G.J., Pan W.J., Magnuson M.E., Jaeger D., Keilholz S.D. Quasi-periodic patterns (QPP): large-scale dynamics in resting state fMRI that correlate with local infraslow electrical activity. Neuroimage 2014, 84:1018-1031.
109. Tzourio-Mazoyer N., Landeau B., Papathanassiou D., Crivello F., Etard O., Delcroix N., Mazoyer B., Joliot M. Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. Neuroimage 2002, 15:273-289.
110. Uddin L.Q., Supekar K.S., Ryali S., Menon V. Dynamic reconfiguration of structural and functional connectivity across core neurocognitive brain networks with development. J. Neurosci. 2011, 31:18578-18589.
111. van den Heuvel M.P., Fornito A. Brain networks in schizophrenia. Neuropsychol. Rev. 2014, 24:32-48.
112. van den Heuvel M.P., Sporns O. An anatomical substrate for integration among functional networks in human cortex. J. Neurosci. 2013, 33:14489-14500.
113. van den Heuvel M.P., Stam C.J., Boersma M., Hulshoff Pol H.E. Small-world and scale-free organization of voxel-based resting-state functional connectivity in the human brain. Neuroimage 2008, 43:528-539.
114. van den Heuvel M.P., Sporns O., Collin G., Scheewe T., Mandl R.C., Cahn W., Goni J., Hulshoff Pol H.E., Kahn R.S. Abnormal rich club organization and functional brain dynamics in schizophrenia. JAMA Psychiatry 2013, 70:783-792.
115. Vincent J.L., Kahn I., Snyder A.Z., Raichle M.E., Buckner R.L. Evidence for a frontoparietal control system revealed by intrinsic functional connectivity. J. Neurophysiol. 2008, 100:3328-3342.
116. Viviani R. Emotion regulation, attention to emotion, and the ventral attentional network. Front. Hum. Neurosci. 2013, 7:746.
117. Volkow N.D., Wolf A.P., Brodie J.D., Cancro R., Overall J.E., Rhoades H., Van Gelder P. Brain interactions in chronic schizophrenics under resting and activation conditions. Schizophr. Res. 1988, 1:47-53.
118. Wee C.Y., Yang S., Yap P.T., Shen D.G. Temporally dynamic resting-state functional connectivity networks for early MCI identification. Mach. Learn. Med. Imaging 2013, 8184:139-146. (Mlmi 2013).
119. Weinberger D.R., Berman K.F., Suddath R., Torrey E.F. Evidence of dysfunction of a prefrontal-limbic network in schizophrenia: a magnetic resonance imaging and regional cerebral blood flow study of discordant monozygotic twins. Am. J. Psychiatry 1992, 149:890-897.
120. Xia M., He Y. Magnetic resonance imaging and graph theoretical analysis of complex brain networks in neuropsychiatric disorders. Brain Connect. 2011, 1:349-365.
121. Yang Z., Craddock R.C., Margulies D., Yan C.G., Milham M.P. Common intrinsic connectivity states among posteromedial cortex subdivisions: Insights from analysis of temporal dynamics. Neuroimage 2014, 93:124-137.
122. Yu Q., Plis S.M., Erhardt E.B., Allen E.A., Sui J., Kiehl K.A., Pearlson G., Calhoun V.D. Modular organization of functional network connectivity in healthy controls and patients with schizophrenia during the resting state. Front. Syst. Neurosci. 2011, 5:103.
123. Yu Q., Sui J., Rachakonda S., He H., Gruner W., Pearlson G., Kiehl K.A., Calhoun V.D. Altered topological properties of functional network connectivity in schizophrenia during resting state: a small-world brain network study. PLoS One 2011, 6:e25423.
124. Yu Q., Sui J., Rachakonda S., He H., Pearlson G., Calhoun V.D. Altered small-world brain networks in temporal lobe in patients with schizophrenia performing an auditory oddball task. Front. Syst. Neurosci. 2011, 5:7.
125. Yu Q., Allen E.A., Sui J., Arbabshirani M.R., Pearlson G., Calhoun V.D. Brain connectivity networks in schizophrenia underlying resting state functional magnetic resonance imaging. Curr. Top. Med. Chem. 2012, 12:2415-2425.
126. Yu Q., Sui J., Kiehl K.A., Pearlson G., Calhoun V.D. State-related functional integration and functional segregation brain networks in schizophrenia. Schizophr. Res. 2013, 150:450-458.
127. Yu Q., Sui J., Liu J., Plis S.M., Kiehl K.A., Pearlson G., Calhoun V.D. Disrupted correlation between low frequency power and connectivity strength of resting state brain networks in schizophrenia. Schizophr. Res. 2013, 143:165-171.
128. Zalesky A., Fornito A., Bullmore E. On the use of correlation as a measure of network connectivity. Neuroimage 2012, 60:2096-2106.