Investigating Causal Relations by Econometric Models and Cross-Spectral Methods

Testing for Granger non-causality in heterogeneous panels

Dumitrescu, E.-I., & Hurlin, C. (2012) · Economic Modelling · doi:10.1016/j.econmod.2012.02.014 · Cited by 5,922 · see citing works

Giving content to investor sentiment: The role of media in the stock market

TETLOCK, P. C. (2007) · The Journal of Finance · doi:10.1111/j.1540-6261.2007.01232.x · Cited by 4,827 · see citing works

Functional and Effective Connectivity: A Review

Friston, K. J. (2011) · Brain Connectivity · doi:10.1089/brain.2011.0008 · Cited by 3,415 · see citing works

The human orbitofrontal cortex: linking reward to hedonic experience

Kringelbach, M. L. (2005) · Nature Reviews Neuroscience · doi:10.1038/nrn1747 · Cited by 2,180 · see citing works

Modelling and analysis of local field potentials for studying the function of cortical circuits

Einevoll, G. T., Kayser, C., Logothetis, N. K., & Panzeri, S. (2013) · Nature Reviews Neuroscience · doi:10.1038/nrn3599 · Cited by 857 · see citing works

Learning sculpts the spontaneous activity of the resting human brain

Lewis, C. M., Baldassarre, A., Committeri, G., Romani, G. L., & Corbetta, M. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0902455106 · Cited by 777 · see citing works

Alpha-Beta and Gamma Rhythms Subserve Feedback and Feedforward Influences among Human Visual Cortical Areas

Michalareas, G., Vezoli, J., van Pelt, S., Schoffelen, J.-M., Kennedy, H., & Fries, P. (2016) · Neuron · doi:10.1016/j.neuron.2015.12.018 · Cited by 696 · see citing works

Ten simple rules for dynamic causal modeling

Stephan, K. E., Penny, W. D., Moran, R. J., den Ouden, H. E. M., Daunizeau, J., & Friston, K. J. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.11.015 · Cited by 803 · see citing works

Tools of the trade: psychophysiological interactions and functional connectivity

O’Reilly, J. X., Woolrich, M. W., Behrens, T. E. J., Smith, S. M., & Johansen-Berg, H. (2012) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nss055 · Cited by 765 · 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

The regulation of negative and positive affect in daily life.

Brans, K., Koval, P., Verduyn, P., Lim, Y. L., & Kuppens, P. (2013) · Emotion · doi:10.1037/a0032400 · Cited by 567 · see citing works

Converging Intracranial Markers of Conscious Access

Gaillard, R., Dehaene, S., Adam, C., Clémenceau, S., Hasboun, D., Baulac, M., Cohen, L., & Naccache, L. (2009) · PLoS Biology · doi:10.1371/journal.pbio.1000061 · Cited by 440 · see citing works

Imaging human connectomes at the macroscale

Craddock, R. C., Jbabdi, S., Yan, C.-G., Vogelstein, J. T., Castellanos, F. X., Di Martino, A., Kelly, C., Heberlein, K., Colcombe, S., & Milham, M. P. (2013) · Nature Methods · doi:10.1038/nmeth.2482 · Cited by 419 · see citing works

The relationship of sugar to population-level diabetes prevalence: an econometric analysis of repeated cross-sectional data

Basu, S., Yoffe, P., Hills, N., & Lustig, R. H. (2013) · PLoS ONE · doi:10.1371/journal.pone.0057873 · Cited by 435 · see citing works

Estimation of the cortical functional connectivity with the multimodal integration of high-resolution EEG and fMRI data by directed transfer function

Babiloni, F., Cincotti, F., Babiloni, C., Carducci, F., Mattia, D., Astolfi, L., Basilisco, A., Rossini, P. M., Ding, L., Ni, Y., et al. (2005) · NeuroImage · doi:10.1016/j.neuroimage.2004.09.036 · Cited by 412 · see citing works

The Dynamic Relationship Between Protest and Repression

Carey, S. C. (2006) · Political Research Quarterly · doi:10.1177/106591290605900101 · Cited by 405 · see citing works

The Effects of Twitter Sentiment on Stock Price Returns

Ranco, G., Aleksovski, D., Caldarelli, G., Grčar, M., & Mozetič, I. (2015) · PLoS ONE · doi:10.1371/journal.pone.0138441 · Cited by 395 · see citing works

Considerations in the assessment of heart rate variability in biobehavioral research

Quintana, D. S., & Heathers, J. A. J. (2014) · Frontiers in Psychology · doi:10.3389/fpsyg.2014.00805 · Cited by 395 · see citing works

Revealing the dynamic network structure of the Beck Depression Inventory-II

Bringmann, L. F., Lemmens, L. H. J. M., Huibers, M. J. H., Borsboom, D., & Tuerlinckx, F. (2015) · Psychological Medicine · doi:10.1017/s0033291714001809 · Cited by 371 · 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

Network discovery with DCM

Friston, K. J., Li, B., Daunizeau, J., & Stephan, K. E. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2010.12.039 · Cited by 283 · see citing works

Cardiac and Respiratory Patterns Synchronize between Persons during Choir Singing

Müller, V., & Lindenberger, U. (2011) · PLoS ONE · doi:10.1371/journal.pone.0024893 · Cited by 256 · see citing works

Theta oscillations mediate interaction between prefrontal cortex and medial temporal lobe in human memory

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

Practical Measures of Integrated Information for Time-Series Data

Barrett, A. B., & Seth, A. K. (2011) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1001052 · Cited by 225 · see citing works

Assessing the strength of directed influences among neural signals using renormalized partial directed coherence

Schelter, B., Timmer, J., & Eichler, M. (2009) · Journal of Neuroscience Methods · doi:10.1016/j.jneumeth.2009.01.006 · Cited by 214 · see citing works

Inferior frontal gyrus activity triggers anterior insula response to emotional facial expressions.

Jabbi, M., & Keysers, C. (2008) · Emotion · doi:10.1037/a0014194 · Cited by 190 · 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

Characterizing and Modulating Brain Circuitry through Transcranial Magnetic Stimulation Combined with Electroencephalography

Farzan, F., Vernet, M., Shafi, M. M. D., Rotenberg, A., Daskalakis, Z. J., & Pascual-Leone, A. (2016) · Frontiers in Neural Circuits · doi:10.3389/fncir.2016.00073 · Cited by 173 · see citing works

Fully Connected Cascade Artificial Neural Network Architecture for Attention Deficit Hyperactivity Disorder Classification From Functional Magnetic Resonance Imaging Data

Deshpande, G., Wang, P., Rangaprakash, D., & Wilamowski, B. (2015) · IEEE Transactions on Cybernetics · doi:10.1109/tcyb.2014.2379621 · Cited by 161 · see citing works

General relationship of global topology, local dynamics, and directionality in large-scale brain networks

Moon, J.-Y., Lee, U., Blain-Moraes, S., & Mashour, G. A. (2015) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1004225 · Cited by 136 · see citing works

Investigation of relationships between fMRI brain networks in the spectral domain using ICA and granger causality reveals distinct differences between schizophrenia patients and healthy controls

Demirci, O., Stevens, M. C., Andreasen, N. C., Michael, A., Liu, J., White, T., Pearlson, G. D., Clark, V. P., & Calhoun, V. D. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.02.014 · Cited by 126 · see citing works

A graphical vector autoregressive modelling approach to the analysis of electronic diary data

Wild, B., Eichler, M., Friederich, H.-C., Hartmann, M., Zipfel, S., & Herzog, W. (2010) · BMC Medical Research Methodology · doi:10.1186/1471-2288-10-28 · Cited by 123 · see citing works

Joint action aesthetics

Vicary, S., Sperling, M., von Zimmermann, J., Richardson, D. C., & Orgs, G. (2017) · PLOS ONE · doi:10.1371/journal.pone.0180101 · Cited by 102 · see citing works

Serotonergic psychedelics temporarily modify information transfer in humans.

Alonso, J. F., Romero, S., Mañanas, M. À., & Riba, J. (2015) · International Journal of Neuropsychopharmacology · doi:10.1093/ijnp/pyv039 · Cited by 101 · see citing works

Optogenetically induced seizure and the longitudinal hippocampal network dynamics

Osawa, S.-I., Iwasaki, M., Hosaka, R., Matsuzaka, Y., Tomita, H., Ishizuka, T., Sugano, E., Okumura, E., Yawo, H., Nakasato, N., et al. (2013) · PLoS ONE · doi:10.1371/journal.pone.0060928 · Cited by 96 · see citing works

Long-term relationship between climate change and nomadic migration in historical China

Pei, Q., & Zhang, D. D. (2014) · Ecology and Society · doi:10.5751/es-06528-190268 · Cited by 95 · see citing works

Untangling Brain-Wide Dynamics in Consciousness by Cross-Embedding

Tajima, S., Yanagawa, T., Fujii, N., & Toyoizumi, T. (2015) · PLOS Computational Biology · doi:10.1371/journal.pcbi.1004537 · Cited by 76 · see citing works

Assessing Granger Causality in Electrophysiological Data: Removing the Adverse Effects of Common Signals via Bipolar Derivations

Trongnetrpunya, A., Nandi, B., Kang, D., Kocsis, B., Schroeder, C. E., & Ding, M. (2016) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2015.00189 · Cited by 75 · see citing works

How to detect the Granger-causal flow direction in the presence of additive noise?

Vinck, M., Huurdeman, L., Bosman, C. A., Fries, P., Battaglia, F. P., Pennartz, C. M. A., & Tiesinga, P. H. (2015) · NeuroImage · doi:10.1016/j.neuroimage.2014.12.017 · Cited by 77 · see citing works

Advances in Electrophysiological Research

Kamarajan, C. (2015) · Alcohol Research: Current Reviews · doi:10.35946/arcr.v37.1.05 · Cited by 72 · see citing works

Hyper-influence of the orbitofrontal cortex over the ventral striatum in obsessive-compulsive disorder

Abe, Y., Sakai, Y., Nishida, S., Nakamae, T., Yamada, K., Fukui, K., & Narumoto, J. (2015) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2015.08.017 · Cited by 56 · see citing works

Temporal dynamics of physical activity and affect in depressed and nondepressed individuals

Stavrakakis, N., Booij, S. H., Roest, A. M., de Jonge, P., Oldehinkel, A. J., & Bos, E. H. (2015) · Health Psychology · doi:10.1037/hea0000303 · Cited by 47 · see citing works

Estimating Directed Connectivity from Cortical Recordings and Reconstructed Sources

Papadopoulou, M., Friston, K., & Marinazzo, D. (2019) · Brain Topography · doi:10.1007/s10548-015-0450-6 · Cited by 40 · see citing works

Sparse System Identification of Leptin Dynamics in Women With Obesity

Amin, M. R., Pednekar, D. D., Azgomi, H. F., van Wietmarschen, H., Aschbacher, K., & Faghih, R. T. (2022) · Frontiers in Endocrinology · doi:10.3389/fendo.2022.769951 · Cited by 14 · see citing works

Inferring a Cognitive Architecture from Multitask Neuroimaging Data: A Data‐Driven Test of the Common Model of Cognition Using Granger Causality

Hake, H. S., Sibert, C., & Stocco, A. (2022) · Topics in Cognitive Science · doi:10.1111/tops.12623 · Cited by 8 · see citing works

Causal Deep Learning

Berrevoets, J., Kacprzyk, K., Qian, Z., & van der Schaar, M. (2023) · arXiv · doi:10.48550/arxiv.2303.02186 · Cited by 8 · see citing works