TY - JOUR
T1 - Resting network is composed of more than one neural pattern: An fMRI study
AU - Lee, Tien-Wen
AU - Northoff, Georg Franz Josef
AU - Wu, Y.-T.
N1 - Export Date: 11 May 2016
CODEN: NRSCD
Correspondence Address: Lee, T.-W.; Dajia Lee's General Hospital, Lee's Medical Corporation, Department of Psychiatry, No. 2, Bade Street, Dajia District, Taichung City 437, Taiwan; email: [email protected]
Tradenames: Tesla scanner, General Electric, United States
Manufacturers: General Electric, United States
References: 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 (2011) Proc Natl Acad Sci U S A, 108, pp. 7641-7646; Eickhoff, S.B., Stephan, K.E., Mohlberg, H., Grefkes, C., Fink, G.R., Amunts, K., Zilles, K., A new SPM toolbox for combining probabilistic cytoarchitectonic maps and functional imaging data (2005) Neuroimage, 25, pp. 1325-1335; Fransson, P., Spontaneous low-frequency BOLD signal fluctuations: an fMRI investigation of the resting-state default mode of brain function hypothesis (2005) Hum Brain Mapp, 26, pp. 15-29; Frey, U., Frey, S., Schollmeier, F., Krug, M., Influence of actinomycin D, a RNA synthesis inhibitor, on long-term potentiation in rat hippocampal neurons in vivo and in vitro (1996) J Physiol, 490 (PART 3), pp. 703-711; Friston, K.J., Modalities, modes, and models in functional neuroimaging (2009) Science, 326, pp. 399-403; Goldman-Rakic, P.S., The prefrontal landscape: implications of functional architecture for understanding human mentation and the central executive (1996) Philos Trans R Soc Lond B Biol Sci, 351, pp. 1445-1453; Good, B.H., de Montjoye, Y.A., Clauset, A., Performance of modularity maximization in practical contexts (2010) Phys Rev E, 81, p. 046106; Gray, J.R., Braver, T.S., Raichle, M.E., Integration of emotion and cognition in the lateral prefrontal cortex (2002) Proc Natl Acad Sci U S A, 99, pp. 4115-4120; Gusnard, D.A., Raichle, M.E., Searching for a baseline: functional imaging and the resting human brain (2001) Nat Rev Neurosci, 2, pp. 685-694; He, B.J., Spontaneous and task-evoked brain activity negatively interact (2013) J Neurosci, 33, pp. 4672-4682; He, Y., Wang, J., Wang, L., Chen, Z.J., Yan, C., Yang, H., Tang, H., Evans, A.C., Uncovering intrinsic modular organization of spontaneous brain activity in humans (2009) PLoS ONE, 4, pp. e5226; Jo, H.J., Saad, Z.S., Simmons, W.K., Milbury, L.A., Cox, R.W., Mapping sources of correlation in resting state FMRI, with artifact detection and removal (2010) Neuroimage, 52, pp. 571-582; Karnath, H.O., New insights into the functions of the superior temporal cortex (2001) Nat Rev Neurosci, 2, pp. 568-576; Kriegeskorte, N., Simmons, W.K., Bellgowan, P.S., Baker, C.I., Circular analysis in systems neuroscience: the dangers of double dipping (2009) Nat Neurosci, 12, pp. 535-540; Kringelbach, M.L., Rolls, E.T., The functional neuroanatomy of the human orbitofrontal cortex: evidence from neuroimaging and neuropsychology (2004) Prog Neurobiol, 72, pp. 341-372; Lancichinetti, A., Radicchi, F., Ramasco, J.J., Fortunato, S., Finding statistically significant communities in networks (2011) PLoS ONE, 6, pp. e18961; Langer, N., Pedroni, A., Jancke, L., The problem of thresholding in small-world network analysis (2013) PLoS ONE, 8, pp. e53199; Leicht, E.A., Newman, M.E., Community structure in directed networks (2008) Phys Rev Lett, 100, p. 118703; Logothetis, N.K., Pauls, J., Augath, M., Trinath, T., Oeltermann, A., Neurophysiological investigation of the basis of the fMRI signal (2001) Nature, 412, pp. 150-157; Lu, H., Zou, Q., Gu, H., Raichle, M.E., Stein, E.A., Yang, Y., Rat brains also have a default mode network (2012) Proc Natl Acad Sci U S A, 109, pp. 3979-3984; Mitchell, J.P., Heatherton, T.F., Macrae, C.N., Distinct neural systems subserve person and object knowledge (2002) Proc Natl Acad Sci U S A, 99, pp. 15238-15243; Moussa, M.N., Steen, M.R., Laurienti, P.J., Hayasaka, S., Consistency of network modules in resting-state FMRI connectome data (2012) PLoS ONE, 7, pp. e44428; Northoff, G., Bermpohl, F., Cortical midline structures and the self (2004) Trends Cogn Sci, 8, pp. 102-107; Northoff, G., Qin, P., Feinberg, T.E., Brain imaging of the self-conceptual, anatomical and methodological issues (2011) Conscious Cogn, 20, pp. 52-63; Olejarczyk, E., Application of fractal dimension method of functional MRI time-series to limbic dysregulation in anxiety study (2007) Conf Proc IEEE Eng Med Biol Soc, 2007, pp. 3408-3410; Ongur, D., Price, J.L., The organization of networks within the orbital and medial prefrontal cortex of rats, monkeys and humans (2000) Cereb Cortex, 10, pp. 206-219; Rubinov, M., Sporns, O., Complex network measures of brain connectivity: uses and interpretations (2010) Neuroimage, 52, pp. 1059-1069; Schneider, F., Bermpohl, F., Heinzel, A., Rotte, M., Walter, M., Tempelmann, C., Wiebking, C., Northoff, G., The resting brain and our self: self-relatedness modulates resting state neural activity in cortical midline structures (2008) Neuroscience, 157, pp. 120-131; Schwarz, A.J., Gozzi, A., Bifone, A., Community structure and modularity in networks of correlated brain activity (2008) Magn Reson Imaging, 26, pp. 914-920; Shen, X., Liu, H., Hu, Z., Hu, H., Shi, P., The relationship between cerebral glucose metabolism and age: report of a large brain PET data set (2012) PLoS ONE, 7, pp. e51517; Shin, J., Tsui, W., Li, Y., Lee, S.Y., Kim, S.J., Cho, S.J., Kim, Y.B., de Leon, M.J., Resting-state glucose metabolism level is associated with the regional pattern of amyloid pathology in Alzheimer's disease (2011) Int J Alzheimer Dis, 2011, p. 759780; Sokoloff, L., Mangold, R., Wechsler, R.L., Kenney, C., Kety, S.S., The effect of mental arithmetic on cerebral circulation and metabolism (1955) J Clin Invest, 34, pp. 1101-1108; Steen, M., Hayasaka, S., Joyce, K., Laurienti, P., Assessing the consistency of community structure in complex networks (2011) Phys Rev E, 84, p. 016111; Tarjan, R., Depth-first search and linear graph algorithms (1972) SIAM J Comput, 1, pp. 146-160; Tomasi, D., Volkow, N.D., Functional connectivity hubs in the human brain (2011) Neuroimage, 57, pp. 908-917; Vul, E., Harris, C., Winkielman, P., Pashler, H., Puzzlingly high correlations in fMRI studies of emotion, personality, and social cognition (2009) Perspect Psychol Sci, 4, pp. 274-290
PY - 2014
Y1 - 2014
N2 - In resting state, the dynamics of blood oxygen level-dependent signals recorded by functional magnetic resonance imaging (fMRI) showed reliable modular structures. To explore the network property, previous research used to construct an adjacency matrix by Pearson's correlation and prune it using stringent statistical threshold. However, traditional analyses may lose useful information at middle to moderate high correlation level. This resting fMRI study adopted full connection as a criterion to partition the adjacency matrix into composite sub-matrices (neural patterns) and investigated the associated community organization and network features. Modular consistency across subjects was assessed using scaled inclusivity index. Our results disclosed two neural patterns with reliable modular structures. Concordant with the results of traditional intervention, community detection analysis showed that neural pattern 1, the sub-matrix at highest correlation level, was composed of sensory-motor, visual associative, default mode/midline, temporal limbic and basal ganglia structures. The neural pattern 2 was situated at middle to moderate high correlation level and comprised two larger modules, possibly associated with mental processing of outer world (such as visuo-associative, auditory and sensory-motor networks) and inner homeostasis (such as default-mode, midline and limbic systems). Graph theoretical analyses further demonstrated that the network feature of neural pattern 1 was more local and segregate, whereas that of neural pattern 2 was more global and integrative. Our results suggest that future resting fMRI research may take the neural pattern at middle to moderate high correlation range into consideration, which has long been ignored in extant literature. The variation of neural pattern 2 could be relevant to individual characteristics of self-regulatory functions, and the disruption in its topology may underlie the pathology of several neuropsychiatric illnesses. © 2014 IBRO.
AB - In resting state, the dynamics of blood oxygen level-dependent signals recorded by functional magnetic resonance imaging (fMRI) showed reliable modular structures. To explore the network property, previous research used to construct an adjacency matrix by Pearson's correlation and prune it using stringent statistical threshold. However, traditional analyses may lose useful information at middle to moderate high correlation level. This resting fMRI study adopted full connection as a criterion to partition the adjacency matrix into composite sub-matrices (neural patterns) and investigated the associated community organization and network features. Modular consistency across subjects was assessed using scaled inclusivity index. Our results disclosed two neural patterns with reliable modular structures. Concordant with the results of traditional intervention, community detection analysis showed that neural pattern 1, the sub-matrix at highest correlation level, was composed of sensory-motor, visual associative, default mode/midline, temporal limbic and basal ganglia structures. The neural pattern 2 was situated at middle to moderate high correlation level and comprised two larger modules, possibly associated with mental processing of outer world (such as visuo-associative, auditory and sensory-motor networks) and inner homeostasis (such as default-mode, midline and limbic systems). Graph theoretical analyses further demonstrated that the network feature of neural pattern 1 was more local and segregate, whereas that of neural pattern 2 was more global and integrative. Our results suggest that future resting fMRI research may take the neural pattern at middle to moderate high correlation range into consideration, which has long been ignored in extant literature. The variation of neural pattern 2 could be relevant to individual characteristics of self-regulatory functions, and the disruption in its topology may underlie the pathology of several neuropsychiatric illnesses. © 2014 IBRO.
KW - Community detection
KW - Functional connectivity
KW - Functional magnetic resonance imaging (fMRI)
KW - Graph theory
KW - Resting fMRI
KW - Scaled inclusivity
KW - adult
KW - article
KW - association cortex
KW - auditory cortex
KW - basal ganglion
KW - BOLD signal
KW - brain function
KW - brain region
KW - functional magnetic resonance imaging
KW - human
KW - human experiment
KW - limbic cortex
KW - normal human
KW - nuclear magnetic resonance scanner
KW - priority journal
KW - resting state network
KW - sensorimotor cortex
KW - biological model
KW - brain
KW - brain mapping
KW - female
KW - image processing
KW - male
KW - nerve cell network
KW - nuclear magnetic resonance imaging
KW - physiology
KW - procedures
KW - statistical analysis
KW - young adult
KW - Adult
KW - Brain
KW - Brain Mapping
KW - Data Interpretation, Statistical
KW - Female
KW - Humans
KW - Image Processing, Computer-Assisted
KW - Magnetic Resonance Imaging
KW - Male
KW - Models, Neurological
KW - Nerve Net
KW - Young Adult
U2 - 10.1016/j.neuroscience.2014.05.035
DO - 10.1016/j.neuroscience.2014.05.035
M3 - Article
C2 - 24881572
SN - 0306-4522
VL - 274
SP - 198
EP - 208
JO - Neuroscience
JF - Neuroscience
ER -