

Dr Adam BarrettEPSRC Research Fellow 
Address: 
Office: Chichester I, 158 (first floor)
adam.barrettatsussexdotacdotuk 
My research makes use of mathematical methods to attempt to understand what is distinct about the particular neural structures, dynamics and functions that give rise to conscious experience. More specifically, inspired by Integrated Information Theory, a major focus of my work is on the development of potential measures of conscious level that quantify the extent to which neural dynamics simultaneously generate and integrate information. In other words, I work on modelling and developing our mathematical understanding of neural complexity, as well as deriving statistical techniques for applying abstract measures based on this concept to neuroimaging data. A key component of this involves developing methodology for quantifying the strength of directed interactions (functional connectivity) between neural dynamical variables, and this leads to applications broadly across neuroscience. Datasets I have analysed include EEG recordings from subjects undergoing general anaesthesia, and intracranial depth electrode recordings from awake and asleep epileptic patients. Other current interests include:
Prior to the Sackler Centre for Consciousness Science, I was a postdoc at the Institute for Adaptive and Neural Computation at the University of Edinburgh. There I worked mainly on synaptic plasticity and the neural basis of learning and memory. I obtained my PhD in theoretical physics from the University of Oxford, and the topic of my thesis was string/Mtheory. For a full CV, click here. 
Publications
Vandenbroucke, A.R.E., Sligte, I.G., Barrett, A.B., Seth, A.K., Fahrenfort, J.J., & Lamme, V.A.F. (in press). Accurate metacognition for visual sensory memory representations. Psych. Science. [link]
Barrett, A.B. (2014). An integration of integrated information theory with fundamental physics. Front. Psychol. 5(63). [view]
Barrett, A.B., Dienes, Z., & Seth, A.K. (2013). Measures of metacognition on signaldetection theoretic models. Psych. Meth. 18(4): 535552. [preprint]
Garfinkel, S.N., Barrett, A.B., Minati, L., Dolan, R.J., Seth, A.K. & Critchley, H.D. (2013). What the heart forgets: Cardiac timing influences memory for words and is modulated by metacognition and interoceptive sensitivity. Psychophysiology 50(6): 505512. [preprint]
Barrett, A.B., & Barnett, L. (2013). Granger causality is designed to measure effect, not mechanism. Frontiers in Neuroinformatics 7(6). [view]
van Rossum, M.C.W., Shippi, M., & Barrett, A.B. (2012). Softbound synaptic plasticity outperforms hardbound plasticity for a variety of learning paradigms. PLoS Comput. Biol. 8(12): e1002836. [view]
FeldwischDrentrup, H., Barrett, A.B., Smith, M.T., & van Rossum, M.C.W. (2012). Fluctuations in the open time of synaptic channels: an application to noise analysis based on charge. J. Neurosci. Meth. 210(1): 1521. [pdf]
Barrett, A.B., Murphy, M., Bruno, M.A., Noirhomme, Q., Boly, M., Laureys, S., & Seth, A.K. (2012). Granger causality analysis of steadystate electroencephalographic signals during propofolinduced anaesthesia. PLoS ONE, 7(1): e29072. [pdf]
Seth, A.K., Barrett, A.B., & Barnett, L. (2011). Causal density and information integration as measures of conscious level. Phil. Trans. Roy. Soc. A, 369:37483767. [pdf]
Froese, T., Gould, C., & Barrett, A.B. (2011). ReViewing from Within: A commentary on the use of first and secondperson methods in the science of consciousness. Constructivist Foundations, 6(2): 254269. [pdf]
Barrett, A.B., & Seth, A.K. (2011). Practical measures of integrated information for timeseries data. PLoS Comput. Biol., 7(1): e1001052. [pdf]
Seth, A.K., & Barrett, A.B. (2010). Neural theories need to account for, not discount, introspection and behaviour. Cog. Neurosci., 1(3):227228. [pdf]
Barrett, A.B., Barnett, L., & Seth, A.K. (2010). Multivariate Granger causality and generalized variance. Phys. Rev. E, 81: 041907. [pdf]
Cortes, J.M., Greve, A., Barrett, A.B., & van Rossum, M.C.W. (2010). Dynamics and robustness of familiarity memory. Neural Comput., 22(2):448466. [preprint]
Barnett, L., Barrett, A.B., & Seth, A.K. (2009). Granger causality and transfer entropy are equivalent for Gaussian variables. Phys. Rev. Lett., 103: 238701. [pdf]
beim Graben, P., Barrett, A.B., & Atmanspacher, H. (2009). Stability criteria for the contextual emergence of macrostates in neural networks. Network: Computation in Neural Systems, 20(3): 177195. [preprint]
Barrett, A.B., Billings, G.O., Morris, R.G.M., & van Rossum, M.C.W. (2009). State based model of longterm potentiation and synaptic tagging and capture. PLoS Comput. Biol., 5(1): e1000259. [view]
Barrett, A.B., & van Rossum, M.C.W. (2008). Optimal learning rules for discrete synapses. PLoS Comput. Biol., 4(11), e1000230. [view]
Physics
"Mtheory on Manifolds with G2 Holonomy", A.B. Barrett, DPhil thesis, University of Oxford, UK (2006). [eprint]
"Fourdimensional Effective Mtheory on a Singular G2 Manifold", (A.B. Barrett primary author; A. Lukas senior author; L.B Anderson and M. Yamaguchi coauthors), Phys. Rev. D, 74, 086008 (2006). [eprint]
"MTheory on the Orbifold C2/ZN", (A.B. Barrett primary author; A. Lukas senior author; L.B Anderson coauthor), Phys. Rev. D, 73, 106011 (2006). [eprint]
"Classification and Moduli Kaehler Potentials of G2 Manifolds", (A.B. Barrett primary author; A. Lukas senior author), Phys. Rev. D, 71, 046004 (2005). [eprint]