Multifaceted brain networks reconfiguration in disorders of consciousness uncovered by co‐activation patterns

Given that recent research has shown that functional connectivity is not a static phenomenon, we aim to investigate the dynamic properties of the default mode network's (DMN) connectivity in patients with disorders of consciousness.

[1]  B. Sahakian,et al.  Default Mode Dynamics for Global Functional Integration , 2015, The Journal of Neuroscience.

[2]  Pablo Balenzuela,et al.  Criticality in Large-Scale Brain fMRI Dynamics Unveiled by a Novel Point Process Analysis , 2012, Front. Physio..

[3]  Jonathan E. Peelle,et al.  Adjusting for global effects in voxel-based morphometry: Gray matter decline in normal aging , 2012, NeuroImage.

[4]  Matteo Pardini,et al.  Functional connectivity and neuronal variability of resting state activity in bipolar disorder—reduction and decoupling in anterior cortical midline structures , 2015, Human brain mapping.

[5]  Stuart D. Washington,et al.  Anterior-Posterior Connectivity within the Default Mode Network Increases During Maturation. , 2015, International journal of medical and biological frontiers.

[6]  M. Boly,et al.  Default network connectivity reflects the level of consciousness in non-communicative brain-damaged patients. , 2010, Brain : a journal of neurology.

[7]  Liang Wang,et al.  Intrinsic connectivity between the hippocampus and posteromedial cortex predicts memory performance in cognitively intact older individuals , 2010, NeuroImage.

[8]  Thomas E. Nichols,et al.  Thresholding of Statistical Maps in Functional Neuroimaging Using the False Discovery Rate , 2002, NeuroImage.

[9]  Steven Laureys,et al.  Functional neuroanatomy of disorders of consciousness , 2014, Epilepsy & Behavior.

[10]  Habib Benali,et al.  Characteristics of the default mode functional connectivity in normal ageing and Alzheimer's disease using resting state fMRI with a combined approach of entropy-based and graph theoretical measurements , 2014, NeuroImage.

[11]  Justin L. Vincent,et al.  Intrinsic functional architecture in the anaesthetized monkey brain , 2007, Nature.

[12]  Marcus E. Raichle,et al.  The Restless Brain , 2011, Brain Connect..

[13]  Chin-Hui Lee,et al.  Evaluation of sliding window correlation performance for characterizing dynamic functional connectivity and brain states , 2016, NeuroImage.

[14]  Steven Laureys,et al.  Brain function in coma, vegetative state, and related disorders , 2004, The Lancet Neurology.

[15]  Gustavo Deco,et al.  Can sliding-window correlations reveal dynamic functional connectivity in resting-state fMRI? , 2016, NeuroImage.

[16]  Evan M. Gordon,et al.  On the Stability of BOLD fMRI Correlations , 2016, Cerebral cortex.

[17]  D. Menon,et al.  Changes in Resting Neural Connectivity during Propofol Sedation , 2010, PLoS ONE.

[18]  H. Blumenfeld Impaired consciousness in epilepsy , 2012, The Lancet Neurology.

[19]  Steven Laureys,et al.  Posterior Cingulate Cortex-Related Co-Activation Patterns: A Resting State fMRI Study in Propofol-Induced Loss of Consciousness , 2014, PloS one.

[20]  S. Rombouts,et al.  Consistent resting-state networks across healthy subjects , 2006, Proceedings of the National Academy of Sciences.

[21]  Maurizio Corbetta,et al.  The human brain is intrinsically organized into dynamic, anticorrelated functional networks. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[22]  Pascale Piolino,et al.  Patterns of hippocampal–neocortical interactions in the retrieval of episodic autobiographical memories across the entire life‐span of aged adults , 2009, Hippocampus.

[23]  Athena Demertzi,et al.  Thalamus, Brainstem and Salience Network Connectivity Changes During Propofol-Induced Sedation and Unconsciousness , 2013, Brain Connect..

[24]  M. Boly,et al.  Breakdown of within- and between-network Resting State Functional Magnetic Resonance Imaging Connectivity during Propofol-induced Loss of Consciousness , 2010, Anesthesiology.

[25]  Steven Laureys,et al.  Limbic hyperconnectivity in the vegetative state , 2013, Neurology.

[26]  Dimitri Van De Ville,et al.  Transient brain activity disentangles fMRI resting-state dynamics in terms of spatially and temporally overlapping networks , 2015, Nature Communications.

[27]  Martin A. Lindquist,et al.  Evaluating dynamic bivariate correlations in resting-state fMRI: A comparison study and a new approach , 2014, NeuroImage.

[28]  John Ashburner,et al.  A fast diffeomorphic image registration algorithm , 2007, NeuroImage.

[29]  Yong He,et al.  Characterizing dynamic functional connectivity in the resting brain using variable parameter regression and Kalman filtering approaches , 2011, NeuroImage.

[30]  Vesa Kiviniemi,et al.  A Sliding Time-Window ICA Reveals Spatial Variability of the Default Mode Network in Time , 2011, Brain Connect..

[31]  Enrico Amico,et al.  Neural correlates of consciousness in patients who have emerged from a minimally conscious state: a cross-sectional multimodal imaging study , 2016, The Lancet Neurology.

[32]  Catie Chang,et al.  Decomposition of spontaneous brain activity into distinct fMRI co-activation patterns , 2013, Front. Syst. Neurosci..

[33]  P. Fransson Spontaneous low‐frequency BOLD signal fluctuations: An fMRI investigation of the resting‐state default mode of brain function hypothesis , 2005, Human brain mapping.

[34]  D. Sharp,et al.  Fractionating the Default Mode Network: Distinct Contributions of the Ventral and Dorsal Posterior Cingulate Cortex to Cognitive Control , 2011, The Journal of Neuroscience.

[35]  Gary H. Glover,et al.  BOLD fractional contribution to resting-state functional connectivity above 0.1Hz , 2015, NeuroImage.

[36]  J. Giacino,et al.  The JFK Coma Recovery Scale-Revised: measurement characteristics and diagnostic utility. , 2004, Archives of physical medicine and rehabilitation.

[37]  Jong-Hwan Lee,et al.  Hippocampus–precuneus functional connectivity as an early sign of Alzheimer's disease: A preliminary study using structural and functional magnetic resonance imaging data , 2013, Brain Research.

[38]  Walter G Sannita,et al.  Unresponsive wakefulness syndrome: a new name for the vegetative state or apallic syndrome , 2010, BMC medicine.

[39]  Steven Laureys The neural correlate of (un)awareness: lessons from the vegetative state , 2005, Trends in Cognitive Sciences.

[40]  C. Koch,et al.  Neural correlates of consciousness: progress and problems , 2016, Nature Reviews Neuroscience.

[41]  Steven Laureys,et al.  Looking for the Self in Pathological Unconsciousness , 2013, Front. Hum. Neurosci..

[42]  David A. Leopold,et al.  Dynamic functional connectivity: Promise, issues, and interpretations , 2013, NeuroImage.

[43]  Abraham Z. Snyder,et al.  Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion , 2012, NeuroImage.

[44]  Eswar Damaraju,et al.  Tracking whole-brain connectivity dynamics in the resting state. , 2014, Cerebral cortex.

[45]  M. Corbetta,et al.  Temporal dynamics of spontaneous MEG activity in brain networks , 2010, Proceedings of the National Academy of Sciences.

[46]  Athena Demertzi,et al.  Two Distinct Neuronal Networks Mediate the Awareness of Environment and of Self , 2011, Journal of Cognitive Neuroscience.

[47]  Jonathan D. Power,et al.  Recent progress and outstanding issues in motion correction in resting state fMRI , 2015, NeuroImage.

[48]  Steven Laureys,et al.  Disorders of consciousness after acquired brain injury: the state of the science , 2014, Nature Reviews Neurology.

[49]  Dimitri Van De Ville,et al.  On spurious and real fluctuations of dynamic functional connectivity during rest , 2015, NeuroImage.

[50]  Catie Chang,et al.  Time–frequency dynamics of resting-state brain connectivity measured with fMRI , 2010, NeuroImage.

[51]  J. Duyn,et al.  Time-varying functional network information extracted from brief instances of spontaneous brain activity , 2013, Proceedings of the National Academy of Sciences.