Short-window spectral analysis of cortical event-related potentials by adaptive multivariate autoregressive modeling: data preprocessing, model validation, and variability assessment
Abstract
In this article we consider the application of parametric spectral analysis to multichannel event-related potentials (ERPs) during cognitive experiments. We show that with proper data preprocessing, Adaptive MultiVariate AutoRegressive (AMVAR) modeling is an effective technique for dealing with nonstationary ERP time series. We propose a bootstrap procedure to assess the variability in the estimated spectral quantities. Finally, we apply AMVAR spectral analysis to a visuomotor integration task, revealing rapidly changing cortical dynamics during different stages of task processing.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Algorithms have been developed for estimating functional connectivity from electrophysiological source signals derived from EEG or MEG, including directed transfer function, adaptive directed transfer function, direct directed transfer function, and partial directed coherence.
“Algorithms have been developed for estimating functional connectivity from electrophysiological source signals derived from EEG (or MEG), including directed transfer function (DTF) algorithm (98), the adaptive DTF (ADTF) (99–101), direct DTF (dDTF) (102), and partial directed coherence (PDC) (103).”
From Electrophysiological source imaging: A noninvasive window to brain dynamics (2018) · cites this paper as [99]
Cites
A new look at the statistical model identification
Akaike, H. (1974) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1974.1100705 · Cited by 51,879 · see citing works
The Jackknife, the Bootstrap and Other Resampling Plans
Efron, B. (1982) · Society for Industrial and Applied Mathematics eBooks · doi:10.1137/1.9781611970319 · Cited by 8,120 · see citing works
Random Data-Analysis and Measurement Procedures
Bendat, J. S., Piersol, A. G., & Saunders, H. (1989) · Journal of vibration and acoustics · doi:10.1115/1.3269865 · Cited by 6,401 · see citing works
Spectral Analysis and its Applications.
Freiberger, W. F., Jenkins, G. M., & Watts, D. G. (1969) · Journal of the American Statistical Association · doi:10.2307/2286100 · Cited by 5,022 · see citing works
Spectral Analysis for Physical Applications
Percival, D. B., & Walden, A. T. (1993) · Cambridge University Press eBooks · doi:10.1017/cbo9780511622762 · Cited by 2,148 · see citing works
Episodic multiregional cortical coherence at multiple frequencies during visual task performance
Bressler, S. L., Coppola, R., & Nakamura, R. (1993) · Nature · doi:10.1038/366153a0 · Cited by 533 · see citing works
Self-citationRecursive Multichannel Maximum Entropy Spectral Estimation
Morf, M., Vieira, A., Lee, D., & Kailath, T. (1978) · IEEE transactions on geoscience electronics · doi:10.1109/tge.1978.294569 · Cited by 259 · see citing works
Spectral analysis methods for neurological signals
Muthuswamy, J., & Thakor, N. V. (1998) · Journal of Neuroscience Methods · doi:10.1016/s0165-0270(98)00065-x · Cited by 196 · see citing works
Spectral analysis of EEG's by autoregressive decomposition of time series
Gersch, W. (1970) · Mathematical Biosciences · doi:10.1016/0025-5564(70)90049-0 · Cited by 150 · see citing works
Franaszczuk, P. J., Blinowska, K. J., & Kowalczyk, M. (1985) · Biological Cybernetics · doi:10.1007/bf00337149 · Cited by 138 · see citing works
Dynamic spectral analysis of event-related EEG data
Florian, G., & Pfurtscheller, G. (1995) · Electroencephalography and Clinical Neurophysiology · doi:10.1016/0013-4694(95)00198-8 · Cited by 86 · see citing works
Dynamic power and coherence analysis of ultra short-term cognitive processes ? A methodical study
Schack, B., & Krause, W. (1995) · Brain Topography · doi:10.1007/bf01199776 · Cited by 47 · see citing works
Weitkunat, R. (1991) · Elsevier eBooks · Cited by 42 · see citing works
Spectral Analysis of Short Series--A Simulation Study
Granger, C. W. J., & Hughes, A. O. (1968) · Journal of the Royal Statistical Society Series A (General) · doi:10.2307/2344088 · Cited by 33 · see citing works
Pfurtscheller, G., & Haring, G. (1972) · Electroencephalography and Clinical Neurophysiology · doi:10.1016/0013-4694(72)90034-x · Cited by 22 · see citing works
Bressler, S. L., Ding, M., & Yang, W. (1999) · Neurocomputing · doi:10.1016/s0925-2312(98)00162-3 · Cited by 19 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
The brainweb: phase synchronization and large-scale integration
Varela, F., Lachaux, J.-P., Rodriguez, E., & Martinerie, J. (2001) · Nature Reviews Neuroscience · doi:10.1038/35067550 · Cited by 4,761 · see citing works
Michel, C. M., & Koenig, T. W. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.11.062 · Cited by 1,370 · see citing works
The pulvinar regulates information transmission between cortical areas based on attention demands
Saalmann, Y. B., Pinsk, M. A., Wang, L., Li, X., & Kastner, S. (2012) · Science · doi:10.1126/science.1223082 · Cited by 1,016 · see citing works
Nonlinear multivariate analysis of neurophysiological signals
Pereda, E., Quiroga, R. Q., & Bhattacharya, J. (2005) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2005.10.003 · Cited by 1,066 · see citing works
Brovelli, A., Ding, M., Ledberg, A., Chen, Y., Nakamura, R., & Bressler, S. L. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0308538101 · Cited by 1,065 · see citing works
Self-citationThe MVGC multivariate Granger causality toolbox: A new approach to Granger-causal inference
Barnett, L., & Seth, A. K. (2013) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2013.10.018 · Cited by 1,017 · see citing works
Granger causality analysis in neuroscience and neuroimaging
Seth, A. K., Barrett, A. B., & Barnett, L. (2015) · The Journal of Neuroscience · doi:10.1523/jneurosci.4399-14.2015 · Cited by 928 · see citing works
Analyzing brain networks with PCA and conditional Granger causality
Zhou, Z., Chen, Y., Ding, M., Wright, P. K., Lu, Z., & Liu, Y. (2008) · Human Brain Mapping · doi:10.1002/hbm.20661 · Cited by 978 · see citing works
Self-citationWiener–Granger Causality: A well established methodology
Bressler, S. L., & Seth, A. K. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.02.059 · Cited by 845 · see citing works
Self-citationCortical coordination dynamics and cognition
Bressler, S. L., & Kelso, J. A. S. (2001) · Trends in Cognitive Sciences · doi:10.1016/s1364-6613(00)01564-3 · Cited by 789 · see citing works
Self-citationA MATLAB toolbox for Granger causal connectivity analysis
Seth, A. K. (2009) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2009.11.020 · Cited by 746 · see citing works
Analysing connectivity with Granger causality and dynamic causal modelling
Friston, K., Moran, R., & Seth, A. K. (2013) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2012.11.010 · Cited by 684 · see citing works
Thalamic amplification of cortical connectivity sustains attentional control
Schmitt, L. I., Wimmer, R. D., Nakajima, M., Happ, M., Mofakham, S., & Halassa, M. M. (2017) · Nature · doi:10.1038/nature22073 · Cited by 663 · see citing works
EEGLAB, SIFT, NFT, BCILAB, and ERICA: New Tools for Advanced EEG Processing
Arnaud Delorme, A., Mullen, T. R., Kothe, C. A., Acar, Z. A., Bigdely-Shamlo, N., Vankov, A., & Makeig, S. (2011) · Computational Intelligence and Neuroscience · doi:10.1155/2011/130714 · Cited by 643 · see citing works
Review of advanced techniques for the estimation of brain connectivity measured with EEG/MEG
Sakkalis, V. (2011) · Computers in Biology and Medicine · doi:10.1016/j.compbiomed.2011.06.020 · Cited by 637 · see citing works
Connectivity and complexity: the relationship between neuroanatomy and brain dynamics
Sporns, O., Tononi, G., & Edelman, G. M. (2000) · Neural Networks · doi:10.1016/s0893-6080(00)00053-8 · Cited by 538 · see citing works
Neuronal Mechanisms and Attentional Modulation of Corticothalamic Alpha Oscillations
Bollimunta, A., Mo, J., Schroeder, C. E., & Ding, M. (2011) · The Journal of Neuroscience · doi:10.1523/jneurosci.5580-10.2011 · Cited by 441 · see citing works
Self-citationHigh-frequency gamma oscillations and human brain mapping with electrocorticography
Crone, N. E., Sinai, A., & Korzeniewska, A. (2006) · Progress in Brain Research · doi:10.1016/s0079-6123(06)59019-3 · Cited by 526 · see citing works
Duann, J., Ide, J. S., Luo, X., & Li, C.-S. R. (2009) · Journal of Neuroscience · doi:10.1523/jneurosci.1300-09.2009 · Cited by 476 · see citing works
Neuronal Mechanisms of Cortical Alpha Oscillations in Awake-Behaving Macaques
Bollimunta, A., Chen, Y., Schroeder, C. E., & Ding, M. (2008) · The Journal of Neuroscience · doi:10.1523/jneurosci.2699-08.2008 · Cited by 434 · see citing works
Self-citationA note on the phase locking value and its properties
Aydöre, S., Pantazis, D., & Leahy, R. M. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.02.008 · Cited by 429 · see citing works
Analyzing information flow in brain networks with nonparametric Granger causality
Dhamala, M., Rangarajan, G., & Ding, M. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.02.020 · Cited by 386 · see citing works
Self-citationHesse, W., Möller, E., Arnold, M., & Schack, B. (2003) · Journal of Neuroscience Methods · doi:10.1016/s0165-0270(02)00366-7 · Cited by 382 · see citing works
Spatial spectra of scalp EEG and EMG from awake humans
Freeman, W., Holmes, M., Burke, B. C., & Vanhatalo, S. (2003) · Clinical Neurophysiology · doi:10.1016/s1388-2457(03)00045-2 · Cited by 370 · see citing works
Comparison of different cortical connectivity estimators for high‐resolution EEG recordings
Astolfi, L., Cincotti, F., Mattia, D., Marciani, M. G., Baccalá, L. A., Fallani, F. D. V., Salinari, S., Ursino, M., Zavaglia, M., Ding, L., et al. (2006) · Human Brain Mapping · doi:10.1002/hbm.20263 · Cited by 357 · see citing works
Chen, Y., Bressler, S. L., & Ding, M. (2005) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2005.06.011 · Cited by 344 · see citing works
Self-citationResponse preparation and inhibition: The role of the cortical sensorimotor beta rhythm
Zhang, Y., Chen, Y., Bressler, S. L., & Ding, M. (2008) · Neuroscience · doi:10.1016/j.neuroscience.2008.06.061 · Cited by 334 · see citing works
Self-citationDetermination of EEG Activity Propagation: Pair-Wise Versus Multichannel Estimate
Kuś, R., Kamiński, M., & Blinowska, K. J. (2004) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2004.827929 · Cited by 328 · see citing works
Electrophysiological source imaging: A noninvasive window to brain dynamics
He, B., Sohrabpour, A., Brown, E., & Liu, Z. (2018) · Annual Review of Biomedical Engineering · doi:10.1146/annurev-bioeng-062117-120853 · Cited by 297 · see citing works
Hwang, K., Velanova, K., & Luna, B. (2010) · The Journal of Neuroscience · doi:10.1523/jneurosci.2825-10.2010 · Cited by 314 · see citing works
Electrophysiological Imaging of Brain Activity and Connectivity—Challenges and Opportunities
He, B., Yang, L., Wilke, C., & Yuan, H. (2011) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2011.2139210 · Cited by 300 · see citing works
HERMES: Towards an Integrated Toolbox to Characterize Functional and Effective Brain Connectivity
Niso, G., Bruña, R., Pereda, E., Gutiérrez, R., Bajo, R., Maestú, F., & del-Pozo, F. (2013) · Neuroinformatics · doi:10.1007/s12021-013-9186-1 · Cited by 283 · see citing works
Large-scale cortical networks for hierarchical prediction and prediction error in the primate brain
Chao, Z. C., Takaura, K., Wang, L., Fujii, N., & Dehaene, S. (2018) · Neuron · doi:10.1016/j.neuron.2018.10.004 · Cited by 238 · see citing works
van Mierlo, P., Papadopoulou, M., Carrette, E., Boon, P., Vandenberghe, S., Vonck, K., & Marinazzo, D. (2014) · Progress in neurobiology · doi:10.1016/j.pneurobio.2014.06.004 · Cited by 266 · see citing works
HERMES: Towards an Integrated Toolbox to Characterize Functional and Effective Brain Connectivity
Niso, G., Bruña, R., Pereda, E., Gutiérrez, R., Bajo, R., Maestú, F., & Pozo Guerrero, F. D. (2013) · UPM Digital Archive (Technical University of Madrid) · Cited by 265 · see citing works
Supervised Network-Based Fuzzy Learning of EEG Signals for Alzheimer's Disease Identification
Yu, H., Lei, X., Song, Z., Liu, C., & Wang, J. (2019) · IEEE Transactions on Fuzzy Systems · doi:10.1109/tfuzz.2019.2903753 · Cited by 248 · see citing works
Roebroeck, A. F., Formisano, E., & Goebel, R. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.09.036 · Cited by 237 · see citing works
Multivariate Granger causality analysis of fMRI data
Deshpande, G., LaConte, S., James, G. A., Peltier, S., & Hu, X. P. (2008) · Human Brain Mapping · doi:10.1002/hbm.20606 · Cited by 238 · see citing works
Electroencephalographic Motor Imagery Brain Connectivity Analysis for BCI: A Review
Hamedi, M., Salleh, S.-H., & Noor, A. M. (2016) · Neural Computation · doi:10.1162/neco_a_00838 · Cited by 238 · see citing works
Anderson, K. L., Rajagovindan, R., Ghacibeh, G. A., Meador, K. J., & Ding, M. (2010) · Cerebral Cortex · doi:10.1093/cercor/bhp223 · Cited by 222 · see citing works
Self-citationGourévitch, B., Jeannès, R. L. B., & Faucon, G. (2006) · Biological Cybernetics · doi:10.1007/s00422-006-0098-0 · Cited by 232 · see citing works
Truccolo, W., Ding, M., Knuth, K. H., Nakamura, R., & Bressler, S. L. (2002) · Clinical Neurophysiology · doi:10.1016/s1388-2457(01)00739-8 · Cited by 210 · see citing works
Self-citationBrockmann, M. D., Pöschel, B., Cichon, N., & Hanganu-Opatz, I. L. (2011) · Neuron · doi:10.1016/j.neuron.2011.05.041 · Cited by 186 · see citing works
Seth, A. K., Chorley, P., & Barnett, L. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.09.049 · Cited by 194 · see citing works
BSMART: A Matlab/C toolbox for analysis of multichannel neural time series
Cui, J., Xu, L., Bressler, S. L., Ding, M., & Liang, H. (2008) · Neural Networks · doi:10.1016/j.neunet.2008.05.007 · Cited by 193 · see citing works
Self-citationNeuroelectrical Hyperscanning Measures Simultaneous Brain Activity in Humans
Laura Astolfi, A., Toppi, J., Fallani, F. D. V., Vecchiato, G., Salinari, S., Donatella Mattia, A., Febo Cincotti, A., & Babiloni, F. (2010) · Brain Topography · doi:10.1007/s10548-010-0147-9 · Cited by 191 · see citing works
Tracking the Time-Varying Cortical Connectivity Patterns by Adaptive Multivariate Estimators
Astolfi, L., Cincotti, F., Mattia, D., De Vico Fallani, F., Tocci, A., Colosimo, A., Salinari, S., Marciani, M. G., Hesse, W., Witte, H., et al. (2008) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2007.905419 · Cited by 179 · see citing works
Behaviour of Granger causality under filtering: Theoretical invariance and practical application
Barnett, L., & Seth, A. K. (2011) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2011.08.010 · Cited by 180 · see citing works
Amygdala-hippocampal dynamics during salient information processing
Zheng, J., Anderson, K. L., Leal, S. L., Shestyuk, A. Y., Gülşen, G., Mnatsakanyan, L., Vadera, S., Hsu, F. P. K., Yassa, M. A., Knight, R. T., et al. (2017) · Nature Communications · doi:10.1038/ncomms14413 · Cited by 181 · see citing works
A cerebellar thalamic cortical circuit for error-related cognitive control
Ide, J. S., & Li, C. R. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.07.042 · Cited by 182 · see citing works
Cardiovascular and cardiorespiratory coupling analyses: a review
Schulz, S., Adochiei, F., Edu, I.-R., Schroeder, R., Costin, H. N., Bär, K., & Voss, A. (2013) · Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences · doi:10.1098/rsta.2012.0191 · Cited by 181 · see citing works
Frequency-specific hippocampal-prefrontal interactions during associative learning
Brincat, S. L., & Miller, E. K. (2015) · Nature Neuroscience · doi:10.1038/nn.3954 · Cited by 168 · see citing works
Zavala, B., Tan, H., Little, S. J., Ashkan, K., Hariz, M. I., Foltynie, T., Zrinzo, L. U., Zaghloul, K. A., & Brown, P. (2014) · Journal of Neuroscience · doi:10.1523/jneurosci.1169-14.2014 · Cited by 169 · see citing works
Evolving Signal Processing for Brain–Computer Interfaces
Makeig, S., Kothe, C. A., Mullen, T. R., Bigdely-Shamlo, N., Zhang, Z., & Kreutz-Delgado, K. (2012) · Proceedings of the IEEE · doi:10.1109/jproc.2012.2185009 · Cited by 163 · see citing works
Top-down regulation of default mode activity in spatial visual attention
Wen, X., Liu, Y., Yao, L., & Ding, M. (2013) · The Journal of Neuroscience · doi:10.1523/jneurosci.4939-12.2013 · Cited by 150 · see citing works
Self-citationCausal Interactions in Attention Networks Predict Behavioral Performance
Wen, X., Yao, L., Liu, Y., & Ding, M. (2012) · Journal of Neuroscience · doi:10.1523/jneurosci.2817-11.2012 · Cited by 160 · see citing works
Self-citationConnectivity measures applied to human brain electrophysiological data
Greenblatt, R. E., Pflieger, M. E., & Ossadtchi, A. E. (2012) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2012.02.025 · Cited by 155 · see citing works
Sun, Y., Lim, J., Kwok, K., & Bezerianos, A. (2014) · Brain and Cognition · doi:10.1016/j.bandc.2013.12.011 · Cited by 154 · see citing works
Metastability, criticality and phase transitions in brain and its models
Werner, G. (2006) · Biosystems · doi:10.1016/j.biosystems.2006.12.001 · Cited by 154 · see citing works
Barrett, A. B., Murphy, M., Bruno, M., Noirhomme, Q., Boly, M., Laureys, S., & Seth, A. K. (2012) · PLoS ONE · doi:10.1371/journal.pone.0029072 · Cited by 149 · see citing works
Deshpande, G., Hu, X. P., Stilla, R. F., & Sathian, K. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.01.044 · Cited by 151 · see citing works
Supp, G. G., Schlögl, A., Trujillo‐Barreto, N. J., Müller, M. M., & Gruber, T. (2007) · PLoS ONE · doi:10.1371/journal.pone.0000684 · Cited by 147 · see citing works
Laura Astolfi, A., Febo Cincotti, A., Donatella Mattia, A., Marciani, M. G., Baccalá, L. A., Fallani, F. D. V., Salinari, S., Ursino, M., Zavaglia, M., & Babiloni, F. (2006) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2006.873692 · Cited by 144 · see citing works
Möller, E., Schack, B., Arnold, M., & Witte, H. (2001) · Journal of Neuroscience Methods · doi:10.1016/s0165-0270(00)00350-2 · Cited by 139 · see citing works
Neural Communication Patterns Underlying Conflict Detection, Resolution, and Adaptation
Oehrn, C. R., Hanslmayr, S., Fell, J., Deuker, L., Kremers, N. A. W., Lam, A. T. D., Elger, C. E., & Axmacher, N. (2014) · Journal of Neuroscience · doi:10.1523/jneurosci.3099-13.2014 · Cited by 131 · see citing works
Muthuraman, M., Heute, U., Arning, K., Anwar, A. R., Elble, R., Deuschl, G., & Raethjen, J. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.01.088 · Cited by 134 · see citing works
Efficient Transfer Entropy Analysis of Non-Stationary Neural Time Series
Wollstadt, P., Martínez‐Zarzuela, M., Vicente, R., Pernas, F. J. D., & Wibral, M. (2014) · PLoS ONE · doi:10.1371/journal.pone.0102833 · Cited by 133 · see citing works
Faes, L., Erla, S., & Nollo, G. (2012) · Computational and Mathematical Methods in Medicine · doi:10.1155/2012/140513 · Cited by 134 · see citing works
Understanding Cognition Through Large-Scale Cortical Networks
Bressler, S. L. (2002) · Current Directions in Psychological Science · doi:10.1111/1467-8721.00168 · Cited by 132 · see citing works
Self-citationGerjets, P., Walter, C., Rosenstiel, W., Bogdan, M., & Zander, T. (2014) · Frontiers in Neuroscience · doi:10.3389/fnins.2014.00385 · Cited by 139 · see citing works
Causal density and integrated information as measures of conscious level
Seth, A. K., Barrett, A. B., & Barnett, L. (2011) · Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences · doi:10.1098/rsta.2011.0079 · Cited by 127 · see citing works
THE WAVE PACKET: AN ACTION POTENTIAL FOR THE 21st CENTURY
Freeman, W. J. (2003) · Journal of Integrative Neuroscience · doi:10.1142/s0219635203000214 · Cited by 132 · see citing works
Laura Astolfi, A., Febo Cincotti, A., Donatella Mattia, A., Babiloni, C., Carducci, F., Basilisco, A., Rossini, P. M., Salinari, S., Ding, L., Ni, Y., et al. (2004) · Clinical Neurophysiology · doi:10.1016/j.clinph.2004.10.012 · Cited by 128 · see citing works
Emotional valence modulates the topology of the parent-infant inter-brain network
Santamaria, L., Noreika, V., Georgieva, S., Clackson, K., Wass, S. V., & Leong, V. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.116341 · Cited by 127 · see citing works
Wang, C., Rajagovindan, R., Han, S.-M., & Ding, M. (2016) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2016.00015 · Cited by 130 · see citing works
Self-citationDynamics of event‐related causality in brain electrical activity
Korzeniewska, A., Crainiceanu, C. M., Kuś, R., Franaszczuk, P. J., & Crone, N. E. (2007) · Human Brain Mapping · doi:10.1002/hbm.20458 · Cited by 121 · see citing works
Phase Synchronization Analysis of EEG Signals: An Evaluation Based on Surrogate Tests
Sun, J., Hong, X., & Tong, S. (2012) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2012.2199490 · Cited by 123 · see citing works
Attentional Modulation of Alpha Oscillations in Macaque Inferotemporal Cortex
Mo, J., Schroeder, C. E., & Ding, M. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.5295-10.2011 · Cited by 119 · see citing works
Self-citationPrestimulus Cortical Activity is Correlated with Speed of Visuomotor Processing
Zhang, Y., Wang, X., Bressler, S. L., Chen, Y., & Ding, M. (2008) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.2008.20132 · Cited by 114 · see citing works
Self-citationZhang, Y., & Ding, M. (2009) · Journal of Cognitive Neuroscience · doi:10.1162/jocn.2009.21247 · Cited by 114 · see citing works
Self-citationThe Reorganization of Human Brain Networks Modulated by Driving Mental Fatigue
Zhao, C., Zhao, M., Yang, Y., Gao, J., Rao, N., & Lin, P. (2016) · IEEE Journal of Biomedical and Health Informatics · doi:10.1109/jbhi.2016.2544061 · Cited by 113 · see citing works
Restless ‘rest’: intrinsic sensory hyperactivity and disinhibition in post-traumatic stress disorder
Clancy, K. J., Ding, M., Bernat, E. M., Schmidt, N. B., & Li, W. (2017) · Brain · doi:10.1093/brain/awx116 · Cited by 109 · see citing works
Self-citationA short history of causal modeling of fMRI data
Stephan, K. E., & Roebroeck, A. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.01.034 · Cited by 112 · see citing works
Functional Connectivity from the Amygdala to the Hippocampus Grows Stronger after Stress
Ghosh, S., Laxmi, T. R., & Chattarji, S. (2013) · Journal of Neuroscience · doi:10.1523/jneurosci.0638-13.2013 · Cited by 107 · see citing works
Synchronized activity in prefrontal cortex during anticipation of visuomotor processing
Liang, H., Bressler, S. L., Ding, M., Truccolo, W., & Nakamura, R. (2002) · Neuroreport · doi:10.1097/00001756-200211150-00004 · Cited by 109 · see citing works
Self-citationGroup-level cortical and muscular connectivity during perturbations to walking and standing balance
Peterson, S. M., & Ferris, D. P. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.05.038 · Cited by 96 · see citing works
Witham, C. L. (2010) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2010.00038 · Cited by 96 · see citing works
Error-Related Functional Connectivity of the Habenula in Humans
Ide, J. S., & Li, C. R. (2011) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2011.00025 · Cited by 89 · see citing works
Faes, L., & Nollo, G. (2010) · Biological Cybernetics · doi:10.1007/s00422-010-0406-6 · Cited by 89 · see citing works
Analyzing multiple spike trains with nonparametric granger causality
Nedungadi, A. G., Rangarajan, G., Jain, N., & Ding, M. (2009) · Journal of Computational Neuroscience · doi:10.1007/s10827-008-0126-2 · Cited by 92 · see citing works
Self-citationKorzeniewska, A., Franaszczuk, P. J., Crainiceanu, C. M., Kuś, R., & Crone, N. E. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.03.030 · Cited by 87 · see citing works
Yi, W., Qiu, S., Wang, K., Qi, H., Zhang, L., Zhou, P., He, F., & Ming, D. (2014) · PLoS ONE · doi:10.1371/journal.pone.0114853 · Cited by 86 · see citing works
Causal Measures of Structure and Plasticity in Simulated and Living Neural Networks
Cadotte, A. J., DeMarse, T. B., He, P., & Ding, M. (2008) · PLoS ONE · doi:10.1371/journal.pone.0003355 · Cited by 87 · see citing works
Self-citationKayser, C. (2009) · Frontiers in Integrative Neuroscience · doi:10.3389/neuro.07.007.2009 · Cited by 87 · see citing works
Kocsis, B., & Kamiński, M. (2006) · Hippocampus · doi:10.1002/hipo.20180 · Cited by 86 · see citing works
Identifying true cortical interactions in MEG using the nulling beamformer
Hui, H. B., Pantazis, D., Bressler, S. L., & Leahy, R. M. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.10.078 · Cited by 85 · see citing works
Self-citationvan Mierlo, P., Carrette, E., Hallez, H., Vonck, K. E. J., Roost, D. V., Boon, P., & Staelens, S. G. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.02.009 · Cited by 83 · see citing works
Analysis of functional brain connections for positive–negative emotions using phase locking value
Daşdemir, Y., Yıldırım, E., & Yıldırım, S. (2017) · Cognitive Neurodynamics · doi:10.1007/s11571-017-9447-z · Cited by 85 · see citing works
Phase and amplitude analysis in time–frequency space—application to voluntary finger movement
Ginter, J., Blinowska, K. J., Kamiński, M., & Durka, P. J. (2001) · Journal of Neuroscience Methods · doi:10.1016/s0165-0270(01)00424-1 · Cited by 84 · see citing works
Estimating Granger causality after stimulus onset: A cautionary note
Wang, X., Chen, Y., & Ding, M. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.03.025 · Cited by 83 · see citing works
Self-citation
- Authors
- Ding, M., Bressler, S. L., Yang, W., & Liang, H.
- Affiliations
- Florida Atlantic University (US)
- Venue
- Biological Cybernetics
- Published
- 2000-06-21
- Volume
- 83
- Issue
- 1
- Pages
- 35-45
- ISSN
- 0340-1200 (ISSN-L)
- 1432-0770
- OpenAlex
- W2074501647
- Cited by
- 582
- References
- 16
- Citations by year
- 2026: 6 · 2025: 9 · 2024: 12 · 2023: 19 · 2022: 24 · 2021: 20 · 2020: 25 · 2019: 36 · 2018: 32 · 2017: 22 · 2016: 32 · 2015: 31 · 2014: 37 · 2013: 36 · 2012: 33
- FWCI
- 5.26
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Biological Cybernetics (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (5r03mh058190-02)
- National Institute of Mental Health (MH-58190-02)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › EEG and Brain-Computer Interfaces
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Physical Sciences › Engineering › Control and Systems Engineering › Control Systems and Identification
- Keywords
- event-related potentials, parametric spectral estimation, non-stationary time series, data preprocessing, model validation, cortical dynamics
- MeSH terms
- Animals, Cerebral Cortex, Cognition, Evoked Potentials, Macaca, Models, Neurological, Pattern Recognition, Visual, Psychomotor Performance, Reproducibility of Results, Multivariate Analysis
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review