PublicationsUsingThisToolkit

List of publications including results which were produced using this toolkit

The publication introducing JIDT is:

J. T. Lizier, "JIDT: An information-theoretic toolkit for studying the dynamics of complex systems" Frontiers in Robotics and AI 1:11, 2014; doi:10.3389/frobt.2014.00011 (pre-print including supplementary info: arXiv:1408.3270)

Publications by other authors

A full and up to date list of papers citing, but not necessarily using, JIDT are available via this search on Google scholar. The citation count as of Oct 2021 is 271

A manual list of publications by other authors using JIDT to produce results includes the following. (I'm no longer able to keep this up, so this is bit out of date). Please let me know if you have published a paper using JIDT and I'll add it here.

• S. Roy, "Quantifying interactions among car drivers using information theory", Chao, 30, 113125 2020
• W. zu Castell & H. Schrenk, "Computing the adaptive cycle", Scientific Reports, 10, 18175, 2020
• P.M Burns, A. Castel, B. Javier, M. Cao, M. Paquet, G. Fecteau, A. Desrochers, M. Frasch, "Recording and manipulation of vagus nerve electrical activity in chronically instrumented unanesthetized near term fetal sheep", doi:10.6084/m9.figshare.7228307.v2 (preprint), 2020
• S. Keshmiri, "Stress Changes the Resting-State Cortical Flow of Information from Distributed to Frontally Directed Patterns ", Biology, 9(8), 236, 2020.
• G. Ramos-Fernandez, S.E. Smith Aguilar, D.C. Krakauer and J.C. Flack, "Collective Computation in Animal Fission-Fusion Dynamics", Froniers in Robotics and AI, 7:90, 2020.
• S. Roy, M.J. Shirazi, B. Jantzen, and N. Abaid, "Effect of visual and auditory sensing cues on collective behavior in Vicsek models" Physical Review E, 100(6): 062415, 2019.
• S. Roy, K. Howes, R. Müller, S. Butail, and N. Abaid, "Extracting Interactions between Flying Bat Pairs Using Model-Free Methods", Entropy, 21(1):42, 2019.
• C.H. Lubba, Z. Ouyang, N.S. Jones, T.M. Bruns, S.R. Schultz, "Bladder pressure encoding by near-independent fibre subpopulations - implications for decoding", bioRxiv, doi:10.1101/826297, 2019
• S. Kumar, K. Yoo, M.D. Rosenberg, D. Scheinost, R.T. Constable, S. Zhang, C.‐S.R. Li, M.M. Chun "An information network flow approach for measuring functional connectivity and predicting behavior". Brain and Behavior, e01346, 2019.
• S.P. Fitzgibbon, A.S. Janania, T.S. Grummett, K.J. Pope, "Detecting connectivity in EEG: A comparative study of data-driven effective connectivity measures", Computers in Biology and Medicine, in press, 2019.
• S. Keshmiri, H. Sumioka, M. Okubo and H. Ishiguro, "An Information-Theoretic Approach to Quantitative Analysis of the Correspondence Between Skin Blood Flow and Functional Near-Infrared Spectroscopy Measurement in Prefrontal Cortex Activity", Frontiers in Neuroscience, 13, 79, 2019.
• A. C. Puche Sarmiento, Y. Bocanegra García, J. F. Ochoa Gómez, "Active information storage in Parkinson's disease: a resting state fMRI study over the sensorimotor cortex", Brain Imaging and Behavior, in press, 2019
• S. Roy, B. Jantzen. "Detecting causality using symmetry transformations" Chaos, 28(7): 075305, 2018.
• J. Lee et al., "Detecting System Anomalies in Multivariate Time Series with Information Transfer and Random Walk", Proc. 2018 IEEE/ACM 5th International Conference on Big Data Computing Applications and Technologies (BDCAT), 2018.
• K. Nam, N. Seong, "Financial news-based stock movement prediction using causality analysis of influence in the Korean stock market", Decision Support Systems, in press, 2018.
• P. Kanda, M. Burke, R. Gupta, "Time-varying causality between equity and currency returns in the United Kingdom: Evidence from over two centuries of data", Physica A, 506, pp. 1060-1080, 2018.
• I. Potapov, J. Latukka, J. Kim, P. Luukko, K. Aalto-Setälä & Esa Räsänen, "Information transfer in QT-RR dynamics: Application to QT-correction", Scientific Reports 8, 14992, 2018.
• T. Muzzu, S. Mitolo, G.P. Gava, S.R. Schultz, "Encoding of locomotion kinematics in the mouse cerebellum", PLoS ONE 13(9): e0203900, 2018.
• N. M. Timme and C. Lapish, "A Tutorial for Information Theory in Neuroscience", eNeuro, in press, 2018; doi:10.1523/ENEURO.0052-18.2018
• S. Romano, N. X. Vinh, K. Verspoor, J. Bailey, "The randomized information coefficient: assessing dependencies in noisy data", Machine Learning, 107(3), pp 509–549, 2018.
• D. Sohn, K. Aronis, H. Ashikaga, "Scale-Invariant Structures of Spiral Waves", arXiv:1806.10768, 2018.
• A. Lensen, B. Xue, M. Zhang, "Automatically Evolving Difficult Benchmark Feature Selection Datasets with Genetic Programming", Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2018), Kyoto, Japan, 2018.
• H. Ashikaga, A. Asgari-Targhi, "Locating Order-Disorder Phase Transition in a Cardiac System", Scientific Reports, 8:1967, 2018.
• O. M. Cliff, M. Prokopenko, R. Fitch, "Minimising the Kullback–Leibler Divergence for Model Selection in Distributed Nonlinear Systems", Entropy, 20(2), 51, 2018.
• A. Lensen, B. Xue, M. Zhang, "Generating Redundant Features with Unsupervised Multi-Tree Genetic Programming". In Proceedings of the 21st European Conference on Genetic Programming, 2018, Parma, Italy, April 2018.
• O. Berthold, "Evolving behaviour with empirical predictive information". In Proceedings of the Genetic and Evolutionary Computation Conference 2017, Berlin, Germany, July 15–19, 2017 (GECCO ’17).
• S. Lahiri, P. Nghe, S. J. Tans, M. L. Rosinberg, D. Lacoste "Information-theoretic analysis of the directional influence between cellular processes", PLoS ONE 12(11):e0187431, 2017.
• J. Park, H. Mori, Y. Okuyama, M. Asada, "Chaotic itinerancy within the coupled dynamics between a physical body and neural oscillator networks". PLoS ONE 12(8):e0182518, 2017.
• P. Warchol, "Buses of Cuernavaca - an agent-based model for universal random matrix behavior minimizing mutual information", arXiv:1709.10104, 2017.
• J. Garland, "Prediction in Projection: A new paradigm in delay-coordinate reconstruction", Ph.D. thesis, University of Colorado, 2016. arXiv:1805.07360.
• M. C. Andrews, J. Cursons, D. G. Hurley, M. Anaka, J. S. Cebon, A. Behren and E. J. Crampin, "Systems analysis identifies miR-29b regulation of invasiveness in melanoma", Molecular Cancer, 15:72, 2016.
• P. Wollstadt, K. K. Sellers, L. Rudelt, V. Priesemann, A. Hutt, F. Froehlich, M. Wibral, "The relation of local entropy and information transfer suggests an origin of isoflurane anesthesia effects in local information processing", arXiv:1608.08387, 2016
• D. G. Hurley, J. Cursons, Y. K. Wang, D. M. Budden, C. G. Print, and E. J. Crampin, "NAIL, a software toolset for inferring, analyzing and visualizing regulatory networks", Bioinformatics, in press, 2015.
• J. Rodewald, J. Colombi, K. Oyama, A. Johnson, "Using Information-theoretic Principles to Analyze and Evaluate Complex Adaptive Supply Network Architectures", Procedia Computer Science, 61, pp. 147-152, 2015.
• J. M. McCracken, "Exploratory Causal Analysis in Bivariate Time Series Data", Thesis, 2015.
• M. Harré, "Entropy and Transfer Entropy: The Dow Jones and the Build Up to the 1997 Asian Crisis", in H. Takayasu et al. (eds.), Proceedings of the International Conference on Social Modeling and Simulation, plus Econophysics Colloquium 2014, Springer Proceedings in Complexity, pp. 15-25, 2015.
• S. Dasgupta, F. Woergoetter, P. Manoonpong, "Information dynamics based self-adaptive reservoir for delay temporal memory tasks", Evolving Systems, 4(4), pp 235-249, 2013.
• J. Boedecker, A. Lazar, O. Obst, A. Zeman, "Effects of STDP and Intrinsic Plasticity on Information Dynamics in a Self-Organising Recurrent Neural Network", Sixth International Workshop on Guided Self-Organization, 2013. (abstract)

JIDT packaged inside other software:

• IDTxl by Wollstadt, Lizier, Vicente, Finn, Martinez Zarzeula, Lindner, Martinez Mediano, Novelli, Wibral -- a comprehensive toolkit for efficient inference of networks from multivariate time series data using information theory.
• HCTSA (Highly Comparative Time-Series Analysis) by Ben Fulcher
• NAIL (Network Analysis and Inference Library) by Daniel G. Hurley, Joseph Cursons, Yi Kan Wang, David M. Budden, Cristin G. Print, and Edmund J. Crampin
• FaultMap by Simon Streicher

JIDT used as a teaching tool in University courses:

• CSYS5030 Self-Organisation and Criticality at The University of Sydney by Joseph Lizier (of course!)
• CS523 Complex Adaptive Systems at University of New Mexico by Melanie Moses and Wayne Just

Publications by contributors to JIDT:

Publications from the JIDT contributors using results produced by JIDT include (this is far from a complete list!):

• P. A. M. Mediano, M. Shanahan, "Balanced Information Storage and Transfer in Modular Spiking Neural Networks", arXiv:1708.04392, 2017.
• X. R. Wang, J. T. Lizier, T. Nowotny, A. Z. Berna, M. Prokopenko, S. C. Trowell, "Feature Selection for Chemical Sensor Arrays Using Mutual Information", PLoS ONE 9(3): e89840.
• C. Gomez, J.T. Lizier, M. Schaum, P. Wollstadt, C. Gruetzner, P. Uhlhaas, C. Freitag, S. Schlitt, S. Boelte, R. Hornero and M. Wibral, "Reduced predictable information in brain signals in autism spectrum disorder", Frontiers in Neuroinformatics, vol. 8, no. 9, 2014.
• M. Wibral, J. T. Lizier, S. Voegler, V. Priesemann and R. Galuske, "Local active information storage as a tool to understand distributed neural information processing", in Frontiers in Neuroinformatics, vol. 8, no. 1, 2014.
• J. T. Lizier, M. Prokopenko and A.Y. Zomaya, "A framework for the local information dynamics of distributed computation in complex systems", in Guided Self-Organization: Inception, edited by M. Prokopenko, pp. 115-158, Springer, Berlin/Heidelberg, 2014. -- See example code at demos/octave/CellularAutomata/GsoChapterDemo2013.m
• M. Wibral, N. Pampu, V. Priesemann, F. Siebenhuehner, H. Seiwert, M. Lindner, J.T. Lizier and R. Vicente, "Measuring information-transfer delays", PLOS ONE, vol. 8, no. 2, e55809, 2013. -- See example code at demos/octave/DetectingInteractionLags
• J.T. Lizier and J.R. Mahoney, "Moving frames of reference, relativity and invariance in transfer entropy and information dynamics", Entropy, vol. 15, no. 1, pp. 177-197, 2013. -- See example code at demos/octave/CellularAutomata/movingFrame.m