Effective Connectivity Extracted from Resting-State fMRI Images Using Transfer Entropy

Glasser, 2016, A multi-modal parcellation of human cerebral cortex, Nature, 536, 171, 10.1038/nature18933 Li, 2020, Enhancing fNIRS analysis using EEG rhythmic signatures: an EEG-informed fNIRS analysis study, IEEE Trans Biomed Eng, 10.1109/TBME.2020.2971679 Rossini, 2019, Methods for analysis of brain connectivity: an IFCN-sponsored review, Clin Neurophysiol, 130, 1833, 10.1016/j.clinph.2019.06.006 Friston, 1994, Functional and effective connectivity in neuroimaging: a synthesis, Hum Brain Mapp, 2, 56, 10.1002/hbm.460020107 van den Heuvel, 2016, Functional connectivity of the human brain in utero, Trends Cogn Sci, 20, 931, 10.1016/j.tics.2016.10.001 Cai, 2018, Brain functional connectivity network studies of acupuncture: a systematic review on resting-state fMRI, J Integr Med, 16, 26, 10.1016/j.joim.2017.12.002 Wu, 2019, Construction of brain structural connectivity network using a novel integrated algorithm based on ensemble average propagator, Comput Biol Med, 112, 10.1016/j.compbiomed.2019.103384 Forkel Park, 2013, Structural and functional brain networks: from connections to cognition, Science, 342, 10.1126/science.1238411 Friston, 2011, Functional and effective connectivity: a review, Brain Connect, 1, 13, 10.1089/brain.2011.0008 Oestreich, 2019, Auditory white matter pathways are associated with effective connectivity of auditory prediction errors within a fronto-temporal network, NeuroImage, 195, 454, 10.1016/j.neuroimage.2019.04.008 Park, 2018, Dynamic effective connectivity in resting state fMRI, NeuroImage, 108, 594, 10.1016/j.neuroimage.2017.11.033 Mansoory, 2020, Resting-state effective connectivity in the motive circuit of methamphetamine users: a case controlled fMRI study, Behav Brain Res, 383, 10.1016/j.bbr.2020.112498 Hannes, 2018, Variability and reliability of effective connectivity within the core default mode network: a multi-site longitudinal spectral DCM study, NeuroImage, 183, 757, 10.1016/j.neuroimage.2018.08.053 Seth, 2015, Granger causality analysis in neuroscience and neuroimaging, J Neurosci, 35, 3293, 10.1523/JNEUROSCI.4399-14.2015 Stephan, 2010, Ten simple rules for dynamic causal modeling, NeuroImage, 49, 3099, 10.1016/j.neuroimage.2009.11.015 Rahimi, 2019, Comparison of brain effective connectivity in different states of attention and consciousness based on EEG signals, Biomed Signal Process Control, 51, 393, 10.1016/j.bspc.2019.02.002 Weber, 2017, The influence of filtering and downsampling on the estimation of transfer entropy, PLoS ONE, 12, 10.1371/journal.pone.0188210 Vicente, 2011, Transfer entropy: a model-free measure of effective connectivity for the neurosciences, J Comput Neurosci, 30, 45, 10.1007/s10827-010-0262-3 Lee, 2012, Transfer entropy estimation and directional coupling change detection in biomedical time series, Biomed Eng Online, 11, 19, 10.1186/1475-925X-11-19 Yu, 2017, Horizontal visibility graph transfer entropy (HVG-TE): a novel metric to characterize directed connectivity in large-scale brain networks, NeuroImage, 156, 249, 10.1016/j.neuroimage.2017.05.047 De La Pava Panche, 2019, A data-driven measure of effective connectivity based on Renyi's α-entropy, Front Neurosci, 13, 1277, 10.3389/fnins.2019.01277 Conti, 2019, Variability and reproducibility of directed and undirected functional MRI connectomes in the human brain, Entropy, 21, 661, 10.3390/e21070661 Van Essen, 2013, The WU-Minn Human Connectome Project: an overview, NeuroImage, 80, 62, 10.1016/j.neuroimage.2013.05.041 Smith, 2013, Resting-state fMRI in the human connectome project, NeuroImage, 80, 144, 10.1016/j.neuroimage.2013.05.039 Marcus, 2013, Human connectome project informatics: quality control, database services, and data visualization, NeuroImage, 80, 202, 10.1016/j.neuroimage.2013.05.077 Manjón, 2015, MRI noise estimation and denoising using non-local PCA, Med Image Anal, 22, 35, 10.1016/j.media.2015.01.004 Tustison, 2010, N4ITK: improved N3 bias correction, IEEE Trans Med Imaging, 29, 1310, 10.1109/TMI.2010.2046908 Tzouro-Mazoyer, 2002, Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain, NeuroImage, 15, 273, 10.1006/nimg.2001.0978 Meszlényi, 2017, Resting state fMRI functional connectivity analysis using dynamic time warping, Front Neurosci, 11, 75, 10.3389/fnins.2017.00075 Linke, 2020, Dynamic time warping outperforms Pearson correlation in detecting atypical functional connectivity in autism spectrum disorders, NeuroImage, 223, 10.1016/j.neuroimage.2020.117383 Schreiber, 2000, Measuring information transfer, Phys Rev Lett, 85, 461, 10.1103/PhysRevLett.85.461 Sharini, 2019, Identification of the pain process by cold stimulation: using dynamic causal modeling of effective connectivity in functional near-infrared spectroscopy (fNIRS), IRBM, 40, 86, 10.1016/j.irbm.2018.11.006 Van den Heuvel, 2017, Proportional thresholding in resting-state fMRI functional connectivity networks and consequences for patient-control connectome studies: issues and recommendations, NeuroImage, 152, 437, 10.1016/j.neuroimage.2017.02.005 Bordier, 2017, Graph analysis and modularity of brain functional connectivity networks: searching for the optimal threshold, Front Neurosci, 11, 441, 10.3389/fnins.2017.00441 Rubinov, 2010, Complex network measures of brain connectivity: uses and interpretations, NeuroImage, 52, 1059, 10.1016/j.neuroimage.2009.10.003 Rogers, 2007, Assessing functional connectivity in the human brain by fMRI, Magn Reson Imaging, 25, 1347, 10.1016/j.mri.2007.03.007 Smith, 2012, The future of FMRI connectivity, NeuroImage, 62, 1257, 10.1016/j.neuroimage.2012.01.022 Thibault, 2018, Neurofeedback with fMRI: a critical systematic review, NeuroImage, 172, 786, 10.1016/j.neuroimage.2017.12.071 Seguin, 2019, Inferring neural signalling directionality from undirected structural connectomes, Nat Commun, 10, 4289, 10.1038/s41467-019-12201-w Li, 2012, Task-dependent modulation of effective connectivity within the default mode network, Front Psychol, 3, 206, 10.3389/fpsyg.2012.00206 Ushakov, 2016, Dynamic causal modeling of hippocampal links within the human default mode network: lateralization and computational stability of effective connections, Front Human Neurosci, 10, 528, 10.3389/fnhum.2016.00528 Rolls, 2018, Effective connectivity in depression, Biol Psychiatry Cogn Neurosci Neuroimaging, 3, 187 Prando, 2020, Sparse DCM for whole-brain effective connectivity from resting-state fMRI data, NeuroImage, 208, 10.1016/j.neuroimage.2019.116367