Working memory performance of early MS patients correlates inversely with modularity increases in resting state functional connectivity networks

NeuroImage

Volumn 94, Issue , 2014, Pages 385-395

  Gamboa, O L ^a   Tagliazucchi, E ^a   Von Wegner, F ^a   Jurcoane, A ^a   Wahl, M ^a   Laufs, H ^a,b   Ziemann, U ^a,c  

^a GOETHE UNIVERSITY   (Germany)

^b UNIVERSITY HOSPITAL SCHLESWIG HOLSTEIN   (Germany)

^c UNIVERSITY OF TÜBINGEN   (Germany)

Author keywords

FMRI; Functional networks; Modularity; Multiple sclerosis; Resting state; Working memory

Indexed keywords

ADULT; BEHAVIOR; BRAIN FUNCTION; CLINICAL ARTICLE; CONTROLLED STUDY; CORRELATION ANALYSIS; DISEASE COURSE; DISEASE MARKER; FEMALE; FUNCTIONAL CONNECTIVITY NETWORK; FUNCTIONAL MAGNETIC RESONANCE IMAGING; HUMAN; MALE; MIDDLE AGED; MULTIPLE SCLEROSIS; PRIORITY JOURNAL; REST; RESTING STATE; REVIEW; SUPPORT VECTOR MACHINE; TASK PERFORMANCE; WORKING MEMORY; YOUNG ADULT; BRAIN; COMPARATIVE STUDY; COMPLICATION; CONNECTOME; MEMORY DISORDERS; NERVE CELL NETWORK; NERVE CELL PLASTICITY; PATHOPHYSIOLOGY; PROCEDURES; RECALL; SHORT TERM MEMORY; STATISTICS;

BRAIN; CONNECTOME; HUMANS; MEMORY DISORDERS; MEMORY, SHORT-TERM; MENTAL RECALL; MULTIPLE SCLEROSIS; NERVE NET; NEURONAL PLASTICITY; REST; STATISTICS AS TOPIC; TASK PERFORMANCE AND ANALYSIS;

EID: 84900316618     PISSN: 10538119     EISSN: 10959572     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2013.12.008     Document Type: Review

References (74)

1. Alexander-Bloch A.F., Gogtay N., Meunier D., Birn R., Clasen L., Lalonde F., Lenroot R., Giedd J., Bullmore E.T. Disrupted modularity and local connectivity of brain functional networks in childhood-onset schizophrenia. Front. Syst. Neurosci. 2010, 4:147.
2. Alexander-Bloch A., Lambiotte R., Roberts B., Giedd J., Gogtay N., Bullmore E. The discovery of population differences in network community structure: new methods and applications to brain functional networks in schizophrenia. Neuroimage 2012, 59:3889-3900.
3. Audoin B., Ibarrola D., Ranjeva J.P., Confort-Gouny S., Malikova I., Ali-Cherif A., Pelletier J., Cozzone P. Compensatory cortical activation observed by fMRI during a cognitive task at the earliest stage of MS. Hum. Brain Mapp. 2003, 20:51-58.
4. Audoin B., Au Duong M.V., Ranjeva J.P., Ibarrola D., Malikova I., Confort-Gouny S., Soulier E., Viout P., Ali-Cherif A., Pelletier J., Cozzone P.J. Magnetic resonance study of the influence of tissue damage and cortical reorganization on PASAT performance at the earliest stage of multiple sclerosis. Hum. Brain Mapp. 2005, 24:216-228.
5. Baddeley A.D., Della Sala S., Gray C., Papagno C., Spinnler H. Testing central executive functioning with a pencil and paper test. Methodology of Frontal and Executive Functions 1997, 61-80. Psychology Press, Hove. P. Rabbitt (Ed.).
6. Balenzuela P., Chernomoretz A., Fraiman D., Cifre I., Sitges C., Montoya P., Chialvo D.R. Modular organization of brain resting state networks in chronic back pain patients. Front. Neuroinform. 2010, 4:116.
7. Bassett D.S., Bullmore E., Verchinski B.A., Mattay V.S., Weinberger D.R., Meyer-Lindenberg A. Hierarchical organization of human cortical networks in health and schizophrenia. J. Neurosci. 2008, 28:9239-9248.
8. 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.
9. Bellmann-Strobl J., Wuerfel J., Aktas O., Dorr J., Wernecke K.D., Zipp F., Paul F. Poor PASAT performance correlates with MRI contrast enhancement in multiple sclerosis. Neurology 2009, 73:1624-1627.
10. Blondel V.D., Guillaume J.L., Lambiotte R., Lefebvre E. Fast unfolding of communities in large networks. J. Stat. Mech. 2008, 2008:10008.
11. Bonavita S., Gallo A., Sacco R., Corte M.D., Bisecco A., Docimo R., Lavorgna L., Corbo D., Costanzo A.D., Tortora F., Cirillo M., Esposito F., Tedeschi G. Distributed changes in default-mode resting-state connectivity in multiple sclerosis. Mult. Scler. 2011, 17:411-422.
12. Bonzano L., Pardini M., Mancardi G.L., Pizzorno M., Roccatagliata L. Structural connectivity influences brain activation during PVSAT in multiple sclerosis. Neuroimage 2009, 44:9-15.
13. Brandes U., Delling D., Gaertler M., Goerke R., Hoefer M., Nikoloski Z., Wagner D. Maximizing Modularity is Hard. J ArXiv Physics e-prints 2006.
14. Buldu J.M., Bajo R., Maestu F., Castellanos N., Leyva I., Gil P., Sendina-Nadal I., Almendral J.A., Nevado A., del-Pozo F., Boccaletti S. Reorganization of functional networks in mild cognitive impairment. PLoS One 2011, 6:e19584.
15. Bullmore E., Sporns O. Complex brain networks: graph theoretical analysis of structural and functional systems. Nat. Rev. Neurosci. 2009, 10:186-198.
16. Cardinal K.S., Wilson S.M., Giesser B.S., Drain A.E., Sicotte N.L. A longitudinal fMRI study of the paced auditory serial addition task. Mult. Scler. 2008, 14:465-471.
17. Chang C.-C., Lin C.-J. LIBSVM: a library for support vector machines. ACM Trans. Intell. Syst. Technol. 2011, 2:27.
18. Chen Z.J., He Y., Rosa-Neto P., Germann J., Evans A.C. Revealing modular architecture of human brain structural networks by using cortical thickness from MRI. Cereb. Cortex 2008, 18:2374-2381.
19. Chen Z.J., He Y., Rosa-Neto P., Gong G., Evans A.C. Age-related alterations in the modular organization of structural cortical network by using cortical thickness from MRI. Neuroimage 2011, 56:235-245.
20. Cohen J.A., Fischer J.S., Bolibrush D.M., Jak A.J., Kniker J.E., Mertz L.A., Skaramagas T.T., Cutter G.R. Intrarater and interrater reliability of the MS functional composite outcome measure. Neurology 2000, 54:802-806.
21. Cordes D., Haughton V.M., Arfanakis K., Carew J.D., Turski P.A., Moritz C.H., Quigley M.A., Meyerand M.E. Frequencies contributing to functional connectivity in the cerebral cortex in "resting-state" data. AJNR Am. J. Neuroradiol. 2001, 22:1326-1333.
22. Cortes C., Vladimir V. Support-vector networks. Mach. Learn. 1995, 20:273-297.
23. Cover K.S., Vrenken H., Geurts J.J., van Oosten B.W., Jelles B., Polman C.H., Stam C.J., van Dijk B.W. Multiple sclerosis patients show a highly significant decrease in alpha band interhemispheric synchronization measured using MEG. Neuroimage 2006, 29:783-788.
24. de Haan W., van der Flier W.M., Koene T., Smits L.L., Scheltens P., Stam C.J. Disrupted modular brain dynamics reflect cognitive dysfunction in Alzheimer's disease. Neuroimage 2012, 59:3085-3093.
25. Faivre A., Rico A., Zaaraoui W., Crespy L., Reuter F., Wybrecht D., Soulier E., Malikova I., Confort-Gouny S., Cozzone P.J., Pelletier J., Ranjeva J.P., Audoin B. Assessing brain connectivity at rest is clinically relevant in early multiple sclerosis. Mult. Scler. 2012, 18:1251-1258.
26. Ferrarini L., Veer I.M., Baerends E., van Tol M.J., Renken R.J., van der Wee N.J., Veltman D.J., Aleman A., Zitman F.G., Penninx B.W., van Buchem M.A., Reiber J.H., Rombouts S.A., Milles J. Hierarchical functional modularity in the resting-state human brain. Hum. Brain Mapp. 2009, 30:2220-2231.
27. Fischer J.S., Rudick R.A., Cutter G.R., Reingold S.C. The Multiple Sclerosis Functional Composite Measure (MSFC): an integrated approach to MS clinical outcome assessment. National MS Society Clinical Outcomes Assessment Task Force. Mult. Scler. 1999, 5:244-250.
28. Forn C., Barros-Loscertales A., Escudero J., Belloch V., Campos S., Parcet M.A., Avila C. Cortical reorganization during PASAT task in MS patients with preserved working memory functions. Neuroimage 2006, 31:686-691.
29. Fortunato S. Community detection in graphs. Phys. Rep. 2010, 486:75-174.
30. Genovese C.R., Lazar N.A., Nichols T.E. Thresholding of Statistical Maps in Functional Neuroimaging Using the False Discovery Rate 2002.
31. Glover G.H., Li T.Q., Ress D. Image-based method for retrospective correction of physiological motion effects in fMRI: RETROICOR. Magn. Reson. Med. 2000, 44:162-167.
32. Gratton C., Nomura E.M., Perez F., D'Esposito M. Focal brain lesions to critical locations cause widespread disruption of the modular organization of the brain. J. Cogn. Neurosci. 2012, 24:1275-1285.
33. Guye M., Bartolomei F., Ranjeva J.P. Imaging structural and functional connectivity: towards a unified definition of human brain organization?. Curr. Opin. Neurol. 2008, 21:393-403.
34. Guye M., Bettus G., Bartolomei F., Cozzone P.J. Graph theoretical analysis of structural and functional connectivity MRI in normal and pathological brain networks. MAGMA 2010, 23:409-421.
35. Hawellek D.J., Hipp J.F., Lewis C.M., Corbetta M., Engel A.K. Increased functional connectivity indicates the severity of cognitive impairment in multiple sclerosis. Proc. Natl. Acad. Sci. U. S. A. 2011, 108:19066-19071.
36. He B.J., Shulman G.L., Snyder A.Z., Corbetta M. The role of impaired neuronal communication in neurological disorders. Curr. Opin. Neurol. 2007, 20:655-660.
37. He Y., Chen Z., Evans A. Structural insights into aberrant topological patterns of large-scale cortical networks in Alzheimer's disease. J. Neurosci. 2008, 28:4756-4766.
38. Jenkinson M., Beckmann C.F., Behrens T.E., Woolrich M.W., Smith S.M. FSL. Neuroimage 2012, 62:782-790.
39. Lemieux L., Salek-Haddadi A., Lund T.E., Laufs H., Carmichael D. Modelling large motion events in fMRI studies of patients with epilepsy. Magn. Reson. Imaging 2007, 25:894-901.
40. Mainero C., Caramia F., Pozzilli C., Pisani A., Pestalozza I., Borriello G., Bozzao L., Pantano P. fMRI evidence of brain reorganization during attention and memory tasks in multiple sclerosis. Neuroimage 2004, 21:858-867.
41. Meunier D., Achard S., Morcom A., Bullmore E. Age-related changes in modular organization of human brain functional networks. Neuroimage 2009, 44:715-723.
42. Meunier D., Lambiotte R., Fornito A., Ersche K.D., Bullmore E.T. Hierarchical modularity in human brain functional networks. Front. Neuroinform. 2009, 3:37.
43. Newman M.E. Modularity and community structure in networks. Proc. Natl. Acad. Sci. U. S. A. 2006, 103:8577-8582.
44. Newman M.E., Girvan M. Finding and evaluating community structure in networks. Phys. Rev. E Stat. Nonlin. Soft Matter Phys. 2004, 69:026113.
45. Nichols T.E., Hayasaka S. Controlling the familywise error rate in functional neuroimaging: a comparative review. Stat. Methods Med. Res. 2003, 12:419-446.
46. Oldfield R. The assessment and analysis of handedness: the Edinburgh inventory. Neuropsychologia 1971, 9:97-113.
47. Pantano P., Iannetti G.D., Caramia F., Mainero C., Di Legge S., Bozzao L., Pozzilli C., Lenzi G.L. Cortical motor reorganization after a single clinical attack of multiple sclerosis. Brain 2002, 125:1607-1615.
48. Pantano P., Mainero C., Iannetti G.D., Caramia F., Di Legge S., Piattella M.C., Pozzilli C., Bozzao L., Lenzi G.L. Contribution of corticospinal tract damage to cortical motor reorganization after a single clinical attack of multiple sclerosis. Neuroimage 2002, 17:1837-1843.
49. Polman C.H., Reingold S.C., Banwell B., Clanet M., Cohen J.A., Filippi M., Fujihara K., Havrdova E., Hutchinson M., Kappos L., Lublin F.D., Montalban X., O'Connor P., Sandberg-Wollheim M., Thompson A.J., Waubant E., Weinshenker B., Wolinsky J.S. Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. Ann. Neurol. 2011, 69:292-302.
50. Power J.D., Mitra A., Laumann T.O., Snyder A.Z., Schlaggar B.L., Petersen S.E. Methods to detect, characterize, and remove motion artifact in resting state fMRI. Neuroimage 2013, 84C:320-341.
51. Radicchi F., Castellano C., Cecconi F., Loreto V., Parisi D. Defining and identifying communities in networks. Proc. Natl. Acad. Sci. U. S. A. 2004, 101:2658-2663.
52. 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.
53. Rand W.M. Objective criteria for the evaluation of clustering methods. J. Am. Stat. Assoc. 1971, 66:846-850.
54. Reichardt J., Bornholdt S. When are networks truly modular?. Physica D 2006, 224:20-26.
55. Rocca M.A., Valsasina P., Absinta M., Riccitelli G., Rodegher M.E., Misci P., Rossi P., Falini A., Comi G., Filippi M. Default-mode network dysfunction and cognitive impairment in progressive MS. Neurology 2010, 74:1252-1259.
56. Roosendaal S.D., Schoonheim M.M., Hulst H.E., Sanz-Arigita E.J., Smith S.M., Geurts J.J., Barkhof F. Resting state networks change in clinically isolated syndrome. Brain 2010, 133:1612-1621.
57. Rorden C., Brett M. Stereotaxic display of brain lesions. Behav. Neurol. 2000, 12:191-200.
58. Rossi F., Giorgio A., Battaglini M., Stromillo M.L., Portaccio E., Goretti B., Federico A., Hakiki B., Amato M.P., De Stefano N. Relevance of brain lesion location to cognition in relapsing multiple sclerosis. PLoS One 2012, 7:e44826.
59. Rubinov M., Sporns O. Complex network measures of brain connectivity: uses and interpretations. Neuroimage 2010, 52:1059-1069.
60. Sanz-Arigita E.J., Schoonheim M.M., Damoiseaux J.S., Rombouts S.A., Maris E., Barkhof F., Scheltens P., Stam C.J. Loss of 'small-world' networks in Alzheimer's disease: graph analysis of FMRI resting-state functional connectivity. PLoS One 2010, 5:e13788.
61. Schoonheim M.M., Geurts J.J., Landi D., Douw L., van der Meer M.L., Vrenken H., Polman C.H., Barkhof F., Stam C.J. Functional connectivity changes in multiple sclerosis patients: a graph analytical study of MEG resting state data. Hum. Brain Mapp. 2013, 34:52-61.
62. Solari A., Radice D., Manneschi L., Motti L., Montanari E. The multiple sclerosis functional composite: different practice effects in the three test components. J. Neurol. Sci. 2005, 228:71-74.
63. Sporns O., Chialvo D.R., Kaiser M., Hilgetag C.C. Organization, development and function of complex brain networks. Trends Cogn. Sci. 2004, 8:418-425.
64. Steinley D. Properties of the Hubert-Arabie adjusted Rand index. Psychol. Methods 2004, 9:386-396.
65. Stevens A.A., Tappon S.C., Garg A., Fair D.A. Functional brain network modularity captures inter- and intra-individual variation in working memory capacity. PLoS One 2012, 7:e30468.
66. Tagliazucchi E., von Wegner F., Morzelewski A., Borisov S., Jahnke K., Laufs H. Automatic sleep staging using fMRI functional connectivity data. Neuroimage 2012, 63:63-72.
67. Tagliazucchi E., von Wegner F., Morzelewski A., Brodbeck V., Borisov S., Jahnke K., Laufs H. Large-scale brain functional modularity is reflected in slow electroencephalographic rhythms across the human non-rapid eye movement sleep cycle. Neuroimage 2013, 70:327-339.
68. Tecchio F., Zito G., Zappasodi F., Dell' Acqua M.L., Landi D., Nardo D., Lupoi D., Rossini P.M., Filippi M.M. Intra-cortical connectivity in multiple sclerosis: a neurophysiological approach. Brain 2008, 131:1783-1792.
69. 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.
70. Vaessen M.J., Braakman H.M., Heerink J.S., Jansen J.F., Debeij-van Hall M.H., Hofman P.A., Aldenkamp A.P., Backes W.H. Abnormal modular organization of functional networks in cognitively impaired children with frontal lobe epilepsy. Cereb. Cortex 2012, 23:1997-2006.
71. Wu K., Taki Y., Sato K., Kinomura S., Goto R., Okada K., Kawashima R., He Y., Evans A.C., Fukuda H. Age-related changes in topological organization of structural brain networks in healthy individuals. Hum. Brain Mapp. 2011, 33:552-568.
72. Wu K., Taki Y., Sato K., Sassa Y., Inoue K., Goto R., Okada K., Kawashima R., He Y., Evans A.C., Fukuda H. The overlapping community structure of structural brain network in young healthy individuals. PLoS One 2011, 6:e19608.
73. Zalesky A., Fornito A., Bullmore E. On the use of correlation as a measure of network connectivity. Neuroimage 2012, 60:2096-2106.
74. Zhou C., Zemanova L., Zamora G., Hilgetag C.C., Kurths J. Hierarchical organization unveiled by functional connectivity in complex brain networks. Phys. Rev. Lett. 2006, 97:238103.