Dynamic functional connectivity analysis reveals transient states of dysconnectivity in schizophrenia

被引:788
作者
Damaraju, E. [1 ]
Allen, E. A. [1 ,2 ]
Belger, A. [3 ]
Ford, J. M. [4 ,5 ]
McEwen, S. [6 ]
Mathalon, D. H. [4 ,5 ]
Mueller, B. A. [7 ]
Pearlson, G. D. [8 ]
Potkin, S. G. [9 ]
Preda, A. [9 ]
Turner, J. A. [10 ]
Vaidya, J. G. [11 ]
van Erp, T. G. [9 ]
Calhoun, V. D. [1 ,12 ]
机构
[1] Mind Res Network, Albuquerque, NM USA
[2] Univ Bergen, KG Jebsen Ctr Res Neuropsychiat Disorders, Bergen, Norway
[3] Univ N Carolina, Dept Psychiat, Chapel Hill, NC USA
[4] Univ Calif San Francisco, Dept Psychiat, San Francisco, CA USA
[5] San Francisco VA Med Ctr, San Francisco, CA USA
[6] Univ Calif Los Angeles, Dept Psychiat & Behav Sci, Los Angeles, CA USA
[7] Univ Minnesota, Dept Psychiat, Minneapolis, MN 55455 USA
[8] Yale Univ, Sch Med, New Haven, CT USA
[9] Univ Calif Irvine, Dept Psychiat & Human Behav, Irvine, CA 92717 USA
[10] Georgia State Univ, Dept Psychol, Atlanta, GA 30303 USA
[11] Univ Iowa, Dept Psychiat, Iowa City, IA 52242 USA
[12] Univ New Mexico, Dept ECE, Albuquerque, NM 87131 USA
关键词
RESTING-STATE; BRAIN ACTIVITY; NETWORK; FLUCTUATIONS; DYSFUNCTION; REGRESSION;
D O I
10.1016/j.nicl.2014.07.003
中图分类号
R445 [影像诊断学];
学科分类号
100207 ;
摘要
Schizophrenia is a psychotic disorder characterized by functional dysconnectivity or abnormal integration between distant brain regions. Recent functional imaging studies have implicated large-scale thalamo-cortical connectivity as being disrupted in patients. However, observed connectivity differences in schizophrenia have been inconsistent between studies, with reports of hyperconnectivity and hypoconnectivity between the same brain regions. Using resting state eyes-closed functional imaging and independent component analysis on a multi-site data that included 151 schizophrenia patients and 163 age- and gender matched healthy controls, we decomposed the functional brain data into 100 components and identified 47 as functionally relevant intrinsic connectivity networks. We subsequently evaluated group differences in functional network connectivity, both in a static sense, computed as the pairwise Pearson correlations between the full network time courses (5.4 minutes in length), and a dynamic sense, computed using sliding windows (44 s in length) and k-means clustering to characterize five discrete functional connectivity states. Static connectivity analysis revealed that compared to healthy controls, patients show significantly stronger connectivity, i.e., hyperconnectivity, between the thalamus and sensory networks (auditory, motor and visual), as well as reduced connectivity (hypoconnectivity) between sensory networks from all modalities. Dynamic analysis suggests that (1), on average, schizophrenia patients spend much less time than healthy controls in states typified by strong, large-scale connectivity, and (2), that abnormal connectivity patterns are more pronounced during these connectivity states. In particular, states exhibiting cortical-subcortical antagonism (anti-correlations) and strong positive connectivity between sensory networks are those that show the group differences of thalamic hyperconnectivity and sensory hypoconnectivity. Group differences are weak or absent during other connectivity states. Dynamic analysis also revealed hypoconnectivity between the putamen and sensory networks during the same states of thalamic hyperconnectivity; notably, this finding cannot be observed in the static connectivity analysis. Finally, in post-hoc analyses we observed that the relationships between sub-cortical low frequency power and connectivity with sensory networks is altered in patients, suggesting different functional interactions between sub-cortical nuclei and sensorimotor cortex during specific connectivity states. While important differences between patients with schizophrenia and healthy controls have been identified, one should interpret the results with caution given the history of medication in patients. Taken together, our results support and expand current knowledge regarding dysconnectivity in schizophrenia, and strongly advocate the use of dynamic analyses to better account for and understand functional connectivity differences. (C) 2014 The Authors. Published by Elsevier Inc.
引用
收藏
页码:298 / 308
页数:11
相关论文
共 55 条
  • [1] Allen E.A., 2013, EEG SIGNATURE FUNCTI
  • [2] Allen E.A., 2011, FRONTIERS SYSTEMS NE
  • [3] Tracking Whole-Brain Connectivity Dynamics in the Resting State
    Allen, Elena A.
    Damaraju, Eswar
    Plis, Sergey M.
    Erhardt, Erik B.
    Eichele, Tom
    Calhoun, Vince D.
    [J]. CEREBRAL CORTEX, 2014, 24 (03) : 663 - 676
  • [4] Anticevic A., 2013, CEREBRAL CORTEX
  • [5] AN INFORMATION MAXIMIZATION APPROACH TO BLIND SEPARATION AND BLIND DECONVOLUTION
    BELL, AJ
    SEJNOWSKI, TJ
    [J]. NEURAL COMPUTATION, 1995, 7 (06) : 1129 - 1159
  • [6] Bleuler E, 1950, Dementia praecox or the group of schizophrenias
  • [7] Hierarchical clustering of brain activity during human nonrapid eye movement sleep
    Boly, Melanie
    Perlbarg, Vincent
    Marrelec, Guillaume
    Schabus, Manuel
    Laureys, Steven
    Doyon, Julien
    Pelegrini-Issac, Melanie
    Maquet, Pierre
    Benali, Habib
    [J]. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2012, 109 (15) : 5856 - 5861
  • [8] A disturbance of nonlinear interdependence in scalp EEG of subjects with first episode schizophrenia
    Breakspear, M
    Terry, JR
    Friston, KJ
    Harris, AWF
    Williams, LM
    Brown, K
    Brennan, J
    Gordon, E
    [J]. NEUROIMAGE, 2003, 20 (01) : 466 - 478
  • [9] The thalamus and schizophrenia: current status of research
    Byne, William
    Hazlett, Erin A.
    Buchsbaum, Monte S.
    Kemether, Eileen
    [J]. ACTA NEUROPATHOLOGICA, 2009, 117 (04) : 347 - 368
  • [10] A method for making group inferences from functional MRI data using independent component analysis
    Calhoun, VD
    Adali, T
    Pearlson, GD
    Pekar, JJ
    [J]. HUMAN BRAIN MAPPING, 2001, 14 (03) : 140 - 151