Publications

2019
2018
2017
  • Echo state networks with multiple read-out modules. Laan, A., Vicente, R. (2017) ; bioRxiv 017558.
  • Analyzing Information Distribution in Complex Systems. Sootla, S., Theis, D.O., Vicente, R. (2017) ; Entropy, 19(12), 636.
  • Bivariate Partial Information Decomposition: the optimization perspective. Makkeh, A., Theis, D.O., Vicente, R. (2017) ; Entropy, 19(10), 530. 
  • Multiagent cooperation and competition with deep reinforcement learning. Tampuu, A., Matiisen T., Kodelja, D., Kuzovkin, I., Korjus, K., Aru, J., Aru, J., Vicente, R. (2017); PLoS One, 12(4), e0172395. 
  • VREX: an open-source toolbox for creating 3D virtual reality experiments. Vasser, M., Kängsepp, M., Magomedkerimov, M., Kilvits, K., Stafinjak, V., Kivisik, T., Vicente, R., & Aru, J. (2017) ; BMC Psychology, 5(1), 4. [paper]
  • Attention is withdrawn from the area of the visual field where the own hand is currently moving. Laak, K.J., Vasser, M., Uibopuu, O.J., & Aru, J (2017); Neurosci Conscious 2017; 3 (1): niw025. [paper]
  • In and out of consciousness: how does conscious processing (d) evolve over time? Aru, J., & Bachmann, T. (2017) ; Frontiers in Psychology, 8, 128 [paper]
2016
2015
2014
  • Sancristóbal, B., Vicente, R., & Garcia-Ojalvo, J. (2014). Role of frequency mismatch in neuronal communication through coherence. Journal of Computational Neuroscience, 1-16.
  • Wibral, M., Vicente, R., & Lizier, J.T. (Eds.) (2014). Directed Information Measures in Neuroscience. Springer. [url]
  • Wibral, M., Vicente, R., & Lindner, M. (2014) Transfer entropy in neuroscience. Directed Information Measures in Neuroscience, 3-36. Springer.
  • Vicente, R., & Wibral, M. (2014) Efficient estimation of information transfer. Directed Information Measures in Neuroscience, 37-58. Springer.
  • Wollstadt, P., Martinez-Zarzuela, M., Vicente, R., Diaz-Pernas, F.J., & Wibral, M. (2014). Efficient transfer entropy analysis of non-stationary neural time series. PLoS ONE, 9(7), e102833.
  • Castellano, M., Plöchl, M., Vicente, R., & Pipa, G. (2014) Neuronal oscillations form fronto-parietal networks during contour integration of dynamic visual stimuli, Frontiers in Integrative Neuroscience, 8, 64.
  • Zemmar, A., Weinmann, O., Kellner, Y., Yu, X., Vicente, R., Gullo, M., Kasper, H., Lussi, K., Ristic, Z., Luft, A., Rioult-Pedotti, M., Zuo, Y., Zagrebelsky, M., & Schwab, M.E. (2014) Neutralization of Nogo-A enhances synaptic plasticity in the rat motor cortex and improves motor learning in-vivo, Journal of Neuroscience, 34(26), 8685-8698.
  • Aru, J. (2014). Distilling the neural correlates of conscious perception. Goethe University Frankfurt. (PhD-thesis). PDF
2013
  • Kuzovkin, I. (2013). Adaptive Interactive Learning: a Novel Approach to Training Brain-Computer Interface Systems. University of Tartu [pdf] (Master Thesis)
  • Wibral, M., Pampu, N., Priesemann, V., Siebenhühner F., Seiwert H., Lindner, M., Lizier, J.T., & Vicente, R. (2013). Measuring information-transfer delays. PLoS ONE, 8(2), e55809. [url]
  • Sancristóbal, B., Vicente, R., Sancho, J.M., & Garcia-Ojalvo, J. (2013). Emerging bimodal firing patterns implement different encoding strategies during gamma-band oscillations. Frontiers in Computational Neuroscience 7:18. [url]
  • Roux, F., Wibral, M., Singer, W., Aru, J., & Uhlhaas, P.J. (2013). The Phase of Thalamic Alpha Activity Modulates Cortical Gamma-Band Activity: Evidence from Resting-State MEG Recordings. Journal of Neuroscience, 33(45), 17827-35. [pdf]
  • Garces, P., Vicente, R., Wibral, M., Pineda Pardo, J.A., Lopez, M.E., Aurtenetxe, S., Marcos, A., de Andres, M.E., Yus, M., Sancho, M., Maestu, F., & Fernandez, A. (2013). Brain-wide slowing of spontaneous alpha rhythms in mild cognitive impairment. Frontiers in Aging Neuroscience, 5, 100. [url]
2012
  • Aru, J., Bachmann, T, Singer, W. & Melloni, L. (2012). Distilling the neural correlates of consciousness. Neuroscience & Biobehavioral Reviews, 36, 737-746. PDF
  • Aru, J., Korjus, K., Murd, C., & Bachmann, T. (2012). Spectral Signatures of the Effects of Caffeine and Occipitally Applied Transcranial Magnetic Stimulation in a Task-Free Experimental Setup. Journal of Caffeine Research, 2(1), 23-30. [url]
  • Aru, J., Axmacher, N., Do Lam, A.T.A., Fell, J., Elger, C.R., Singer, W., & Melloni, L. (2012). Local Category-Specific Gamma Band Responses in the Visual Cortex Do Not Reflect Conscious Perception. Journal of Neuroscience, 32(43), 14909-14914. [pdf]
  • D’Huys, O., Fischer, I., Danckaert, J., & Vicente, R. (2012). Spectral and correlation properties of rings of delay-coupled elements: Comparing linear and nonlinear systems. Physical Review E, 85(5), 056209. [url]
  • Vicente, R. & Mirasso, C.R. (2012). Cuando las neuronas sincronizan sus relojes. Mente y Cerebro, 53, 62-71. [pdf]
2011
  • Korjus, K. (2011). Causality Measures in Neuroscience: Wiener-Granger causality and transfer entropy applied to intracranial EEG data. University of Manchester [pdf] (Master Thesis)
  • Lindner, M., Vicente, R., Priesemann, V., & Wibral, M. (2011). TRENTOOL: A Matlab open source toolbox to analyse information flow in time series data with transfer entropy. BMC Neuroscience, 12(1), 119. [url]
  • Perez, T., Garcia, G.C., Eguiluz, V., Vicente, R., Pipa, G., & Mirasso C.R. (2011). Effect of the topology and delayed interactions in neuronal networks synchronization. PLoS ONE, 6(5), e19900. [url]
  • D’Huys, O., Fischer, I., Danckaert, J., & Vicente, R. (2011). Role of the delay for the symmetry in the dynamics of networks. Physical Review E, 83(4), 046223. [url]
  • Wibral, M., Rahm, B., Rieder, M., Lindner, M., Vicente, R., & Kaiser, J. (2011). Transfer entropy in magnetoencephalographic data: Quantifying information flow in cortical and cerebellar networks. Progress in Biophysics and Molecular Biology, 105(1), 80-97. [url]
  • Vicente, R., Wibral, M., Lindner, M., & Pipa, G. (2011). Transfer entropy –a model-free measure of effective connectivity for the neurosciences. Journal of Computational Neuroscience, 30(1), 45-67. [url]
  • Eriksson, D., Vicente, R., & Schmidt, K. (2011). A linear model of phase-dependent power correlations in neuronal oscillations. Frontiers in Computational Neuroscience 5:34. [url]
  • Scheller, B., Castellano, M., Vicente, R., & Pipa, G. (2011). Spike train auto-structure impacts post-synaptic firing and time-dependent plasticity. Frontiers in Computational Neuroscience 5:60. [url]