BOLD fMRI complexity predicts changes in brain processes, interactions and patterns, in health and disease

[1]  Matio Bertolaccini,et al.  A Nonlinear Filtering Technique for the Identification of Biological Signals , 1978, IEEE Transactions on Biomedical Engineering.

[2]  R. Pool.  Is it healthy to be chaotic? , 1989, Science.

[3]  S M Pincus,et al.  Approximate entropy as a measure of system complexity. , 1991, Proceedings of the National Academy of Sciences of the United States of America.

[4]  S. Pincus.  Approximate entropy (ApEn) as a complexity measure. , 1995, Chaos.

[5]  Xu-Sheng Zhang,et al.  Derived fuzzy knowledge model for estimating the depth of anesthesia , 2001, IEEE Transactions on Biomedical Engineering.

[6]  Steven M. Pincus.  Assessing Serial Irregularity and Its Implications for Health , 2001, Annals of the New York Academy of Sciences.

[7]  K. Newell,et al.  Changing complexity in human behavior and physiology through aging and disease , 2002, Neurobiology of Aging.

[8]  Madalena Costa,et al.  Multiscale entropy analysis of complex physiologic time series. , 2002, Physical review letters.

[9]  Nikos K Logothetis,et al.  Interpreting the BOLD signal. , 2004, Annual review of physiology.

[10]  Madalena Costa,et al.  Multiscale entropy analysis of biological signals. , 2005, Physical review. E, Statistical, nonlinear, and soft matter physics.

[11]  D. Abásolo,et al.  Entropy analysis of the EEG background activity in Alzheimer's disease patients , 2006, Physiological measurement.

[12]  Wangxin Yu,et al.  Characterization of Surface EMG Signal Based on Fuzzy Entropy , 2007, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

[13]  Ki H. Chon,et al.  Automatic Selection of the Threshold Value $r$ for Approximate Entropy , 2008, IEEE Transactions on Biomedical Engineering.

[14]  Hong-Bo Xie,et al.  A comparative study of pattern synchronization detection between neural signals using different cross-entropy measures , 2010, Biological Cybernetics.

[15]  E. Bullmore,et al.  Human brain networks in health and disease , 2009, Current opinion in neurology.

[16]  O. Sporns.  Networks of the Brain , 2010 .

[17]  Hong-Bo Xie,et al.  Fuzzy Approximate Entropy Analysis of Chaotic and Natural Complex Systems: Detecting Muscle Fatigue Using Electromyography Signals , 2010, Annals of Biomedical Engineering.

[18]  Ian J. Deary,et al.  Inter-individual Differences in fMRI Entropy Measurements in Old Age , 2011, IEEE Transactions on Biomedical Engineering.

[19]  Maurizio Corbetta,et al.  Functional connectivity in resting-state fMRI: Is linear correlation sufficient? , 2011, NeuroImage.

[20]  M. Paluš,et al.  The role of nonlinearity in computing graph-theoretical properties of resting-state functional magnetic resonance imaging brain networks. , 2011, Chaos.

[21]  D. Abásolo,et al.  Brain oscillatory complexity across the life span , 2012, Clinical Neurophysiology.

[22]  D. Linden,et al.  Resting state fMRI entropy probes complexity of brain activity in adults with ADHD , 2013, Psychiatry Research: Neuroimaging.

[23]  Jeffery R. Alger,et al.  Complexity and synchronicity of resting state blood oxygenation level‐dependent (BOLD) functional MRI in normal aging and cognitive decline , 2013, Journal of magnetic resonance imaging : JMRI.

[24]  P. Tu,et al.  Complexity of spontaneous BOLD activity in default mode network is correlated with cognitive function in normal male elderly: a multiscale entropy analysis , 2013, Neurobiology of Aging.

[25]  O. Sporns.  Contributions and challenges for network models in cognitive neuroscience , 2014, Nature Neuroscience.

[26]  J. Detre,et al.  Brain Entropy Mapping Using fMRI , 2014, PloS one.

[27]  C. Peng,et al.  The APOE ɛ4 allele affects complexity and functional connectivity of resting brain activity in healthy adults , 2014, Human brain mapping.

[28]  Moses O. Sokunbi,et al.  Nonlinear Complexity Analysis of Brain fMRI Signals in Schizophrenia , 2014, PloS one.

[29]  C. Stam.  Modern network science of neurological disorders , 2014, Nature Reviews Neuroscience.

[30]  Moses O. Sokunbi,et al.  Sample entropy reveals high discriminative power between young and elderly adults in short fMRI data sets , 2014, Front. Neuroinform..

[31]  Paul J. Laurienti,et al.  Functional Brain Networks Formed Using Cross-Sample Entropy Are Scale Free , 2014, Brain Connect..

[32]  Kay Jann,et al.  Wavelet‐based regularity analysis reveals recurrent spatiotemporal behavior in resting‐state fMRI , 2015, Human brain mapping.

[33]  Moses O. Sokunbi,et al.  Fuzzy approximate entropy analysis of resting state fMRI signal complexity across the adult life span. , 2015, Medical engineering & physics.

[34]  C. Peng,et al.  Decreased resting‐state brain activity complexity in schizophrenia characterized by both increased regularity and randomness , 2015, Human brain mapping.

[35]  Dane Taylor,et al.  Causal Network Inference by Optimal Causation Entropy , 2014, SIAM J. Appl. Dyn. Syst..

[36]  M. Grossman,et al.  Resting State Brain Entropy Alterations in Relapsing Remitting Multiple Sclerosis , 2016, PloS one.