Dr. Lionel Barnett

Research Fellow

Affiliations

Contact details

Software

Book

Bossomaier, T., Barnett, L., Harré, M. and Lizier, J. T. (2016):

An Introduction to Transfer Entropy: Information Flow in Complex Systems, Springer International Publishing, ISBN: 978-3-319-43222-9 (eBook), 978-3-319-43221-2 (Hardcover)

Publications

Novelli, L., Barnett, L., Seth, A. K. and Razi, A (2023):

Minimum-phase property of the hemodynamic response function, and implications for Granger Causality in fMRI [preprint], arΧiv:2312.01833 [q-bio.NC] (2023).

Barnett, L. and Seth, A. K. (2023):

Dynamical independence: Discovering emergent macroscopic processes in complex dynamical systems [preprint], [abstract], Phy. Rev. E 108, 014304 (2023).

✭ A Matlab® implementation of state-space Dynamical Independence calculation and optimisation as described in this article is available on GitHub.

Mediano, P. A. M., Rosas, F. E., Luppi, A. I., Noreika, V., Seth, A. K., Carhart-Harris, R. L., Barnett, L., and Bor, D. (2023):

Spectrally and temporally resolved estimation of neural signal diversity, [abstract], eLife reviewed preprint 12:RP88683 (2023).

✭ A Matlab® implementation of the methods detailed in this article is available on GitHub.

Gutknecht, A. J. and Barnett, L. (2023):

Sampling distribution for single-regression Granger causality estimators [abstract], [preprint], Biometrika asad009 (2023).

✭ A Matlab® implementation of the methods detailed in this article is available on GitHub.

Brown, J. M., Bossomaier, T., and Barnett, L. (2022):

Information flow in first-order Potts model phase transition [abstract], Nature Sci. Rep. 12 (2022).

Brown, J. M., Bossomaier, T., and Barnett, L. (2021):

Information transfer in finite flocks with topological interactions [abstract], J. Comput. Sci. 53 (2021).

Brown, J., Bossomaier, T., and Barnett, L. (2020):

Information flow in finite flocks [abstract], Nat. Sci. Rep. 10 (2020).

Barnett, L., Muthukumaraswamy, S. D., Carhart-Harris, R. L. and Seth, A. K. (2019):

Decreased directed functional connectivity in the psychedelic state [abstract], [preprint], NeuroImage 209 (2019).

Barnett, L., and Seth, A. K. (2019):

Inferring the temporal structure of directed functional connectivity in neural systems: some extensions to Granger causality [abstract], [preprint], Proceedings of the 2019 IEEE International Conference on Systems, Man and Cybernetics (SMC) Bari, Italy, October 6-9, 2019. (Best paper nomination, 9th Workshop on Brain-Machine Interface.)

Barnett, L., Barrett, A. B. and Seth, A. K. (2018):

Misunderstandings regarding the application of Granger causality in neuroscience [abstract], [preprint], PNAS Letter (2018 [submitted Aug 2017]).

Barnett, L., Barrett, A. B. and Seth, A. K. (2018):

Solved problems for Granger causality in neuroscience: A response to Stokes and Purdon [abstract], [preprint], NeuroImage 178 (2018).

Barnett, L., Brown, J. and Bossomaier, T. (2018):

Anomalous behaviour of mutual information in finite flocks [abstract], [preprint], Europhys. Lett. 120(3) (2018).

Brown, J. M., Bossomaier, T. and Barnett, L. (2017):

Review of data structures for computationally efficient nearest-neighbour entropy estimators for large systems with periodic boundary conditions [abstract], [preprint], J. Comp. Sci. 23 (2017).

Schartner, M. M., Pigorini, A., Gibbs, S. A., Arnulfo, G., Sarasso, S., Barnett, L., Nobili, L., Massimini, M., Seth, A. K. and Barrett, A. B. (2016):

Global and local complexity of intracranial EEG decreases during NREM sleep. [abstract], Neuroscience of Consciousness 3(1) (2016).

Barnett, L. and Seth, A. K. (2016):

Detectability of Granger causality for subsampled continuous-time neurophysiological processes. [abstract], [preprint], J. Neurosci. Methods 275 (2016).

Prokopenko, M., Barnett, L., Harré, M., Lizier, J. T., Obst, O. and Wang, X. R. (2015):

Fisher Transfer Entropy: Quantifying the gain in transient sensitivity. [link], [preprint], Phil. Trans. R. Soc. A (2015).

Barnett, L. and Seth, A. K. (2015):

Granger causality for state-space models. [abstract], [preprint], Phys. Rev. E 91(4) Rapid Communication (2015).

✭ A Matlab® implementation of the methods detailed in this paper is available on GitHub

Seth, A. K., Barrett, A. B. and Barnett, L. (2015):

Granger causality analysis in neuroscience and neuroimaging. [abstract], J. Neurosci. 35(8) (2015).

Barnett, L. and Seth, A. K. (2014):

The MVGC Multivariate Granger Causality Toolbox: A new approach to Granger-causal inference [abstract], [preprint]. J. Neurosci. Methods 223 (2014).

Barnett, L., Lizier, J. T., Harré, M., Seth, A. K. and Bossomaier, T. (2013):

Information flow in a kinetic Ising model peaks in the disordered phase [abstract], [preprint], [supp. mat.]. Phys. Rev. Lett. 111(17) (2013).

✭ See also a non-technical commentary, and presentation slides from CIDNET14

Barrett, A. B. and Barnett, L. (2013):

Granger causality is designed to measure effect, not mechanism [link]. Front. Neuroinform. 7(6) (2013).

Bossomaier, T., Barnett, L. and Harré, M. (2013):

Information and phase transitions in socio-economic systems. [abstract], [pdf], Complex Adaptive Systems Modeling 1(9) (2013).

Seth, A. K., Chorley, P. and Barnett, L. (2013):

Granger causality analysis of fMRI BOLD signals is invariant to hemodynamic convolution but not downsampling [abstract] [preprint]. Neuroimage 65 (2013).

Barnett, L. and Bossomaier, T. (2012):

Transfer entropy as a log-likelihood ratio [abstract] [preprint]. Phys. Rev. Lett. 109(13) (2012).

Bossomaier, T., Barnett, L.,Thiruvarudchelvan, V. and Jelinek, H. (2012):

Energy saving accounts for the suppression of sensory detail [pdf]. COGNITIVE 2012, The Fourth International Conference on Advanced Cognitive Technologies and Applications, July 22-27 2012, Nice, France.

Seth, A. K., Barrett, A. B. and Barnett, L. (2011):

Causal density and integrated information as measures of conscious level [abstract] [pdf]. Phil. Trans. R. Soc. A 369(1952) (2011).

Barnett, L. and Seth, A. K. (2011):

Behaviour of Granger causality under filtering: Theoretical invariance and practical application [abstract], [preprint]. J. Neurosci. Methods 201(2) (2011).

Barnett, L., Buckley, C. L. and Bullock, S. (2011):

Neural complexity: A graph theoretic interpretation [abstract] [pdf]. Phys. Rev. E 83(4) (2011).

Barrett, A. B., Barnett, L. and Seth, A. K. (2010):

Multivariate Granger causality and generalized variance [abstract] [preprint]. Phys. Rev. E 81(4) (2010).

Bullock, S., Barnett, L. and Di Paolo, E. A. (2010):

Spatial embedding and the structure of complex networks [abstract] [pdf]. Complexity, Special Issue on Spatial Organisation 16(2) (2010).

Buckley, C. L., Bullock, S., and Barnett, L. (2010):

Spatially Embedded Dynamics and Complexity. [abstract] [pdf]. Complexity, Special Issue on Spatial Organisation 16(2) (2010).

Barnett, L., Barrett, A. B. and Seth, A. K. (2009):

Granger causality and transfer entropy are equivalent for Gaussian variables [abstract] [preprint]. Phys. Rev. Lett. 103(23) (2009).

Barnett, L., Buckley, C. L. and Bullock, S. (2009):

Neural Complexity and Structural Connectivity [abstract] [pdf]. Phys. Rev. E 79(5) (2009).

Barnett, L. (2008):

Ruggedness and evolvability --- an evolution's-eye view (abstract) [presentation] In S. Bullock, J. Noble, R. Watson, and M. A. Bedau (Eds.), Artificial Life XI: Proceedings of the Eleventh International Conference on the Simulation and Synthesis of Living Systems (p. 748). MIT Press, Cambridge, MA.

Hu, X-B., Di Paolo E. A. and Barnett, L. (2008):

Ripple-spreading model and genetic algorithm for random complex networks: Preliminary study [pdf]. In The World Congress on Computer Intelligence (WCCI2008), Hong Kong, China, 01-06 June 2008.

Barnett, L., Di Paolo, E. and Bullock, S. (2007):

Spatially embedded random networks [abstract] [preprint]. Phys. Rev. E 76(5) (2007).

Barnett, L. (2003):

Evolutionary search on fitness landscapes with neutral networks [pdf] [postscript]. DPhil. thesis, Informatics Dept. (formerly COGS), University of Sussex.

Barnett, L. (2003):

Recombination and bistability in finite populations [pdf]. In Crutchfield, J. P. and Schuster, P. (Eds.), Evolutionary Dynamics: Exploring the Interplay of Selection, Accident, Neutrality, and Function (p. 291). Oxford University Press, New York

Barnett, L. (2002):

Explorations in evolutionary visualisation [pdf]. In Bilotta, E. et. al. (Eds.), Beyond Fitness: Visualising Evolution, ALife VIII: Workshop Proceedings, The 8th International Conference on the Simulation and Synthesis of Living Systems (p. 113). MIT Press.

Barnett, L. (2001):

Netcrawling - optimal evolutionary search with neutral networks [pdf]. In Proceedings of the 2001 Congress on Evolutionary Computation CEC2001 (pp. 30-37). IEEE Press.

Barnett, L. (2000):

The effects of recombination on a haploid quasispecies evolving on a single-peak fitness landscape [pdf]. Unpublished.

Barnett, L. (1998):

Collapsing the state space - applying Markov analysis to evolutionary systems [postscript]. In Nehaniv, C. L. and Wagner, G. P. (Eds.), The Right Stuff: Appropriate Mathematics for Evolutionary and Developmental Biology, Workshop Extended Abstracts for the Sixth International Conference on Artificial Life. MIT Press.

Barnett, L. (1998):

Ruggedness and neutrality - the NKp family of fitness landscapes [pdf] [postscript]. In Adami, C., Belew, R. K., Kitano, H. and Taylor, C. (Eds.), Alife VI, Proceedings of the Sixth International Conference on Artificial Life (pp. 18-27). MIT Press.

Barnett, L. (1997):

Tangled webs: Evolutionary dynamics on fitness landscapes with neutrality [postscript]. Masters dissertation, Informatics Dept. (formerly COGS), University of Sussex.