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Consciousness and Complexity

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Abbreviations

Thalamocortical system:

The network of highly interconnected cortical areas and thalamic nuclei that comprises a large part of the mammalian brain. The cortex is the wrinkled surface of the brain, the thalamus is a small walnut‐sized structure at its center. An intact thalamocortical system is essential for normal conscious experience.

Theory of neuronal group selection (TNGS):

A large‐scale selectionist theory of brain development and function with roots in evolutionary theory and immunology. According to this theory, brain dynamics shape and are shaped by selection among highly variant neuronal populations guided by value or salience.

Neural correlate of consciousness:

Patterns of activity in brain regions or groups of neurons that have privileged status in the generation of conscious experience. Explanatory correlates are neural correlates that in addition account for key properties of consciousness.

Dynamic core:

A  distributed and continually shifting coalesence of patterns of activity among neuronal groups within the thalamocortical system. According to the TNGS, neural dynamics within the core are of high neural complexity by virtue of which they give rise to conscious discriminations.

Neural complexity:

A  measure of simultaneous functional segregation and functional integration based on information theory. A system will have high neural complexity if each of its components can take on many different states and if these states make a difference to the rest of the system.

Small-world networks:

Networks in which most nodes are not neighbors of one another, but most nodes can be reached from every other by a small number of hops or steps. Small-world networks combine high clustering with short path lengths. They can be readily identified in neuroanatomical data, and they are well suited to generating dynamics of high neural complexity.

Metastability:

Dynamics that are characterized by segregating and integrating influences in the temporal domain; metastable systems are neither totally stable nor totally unstable.

Bibliography

Primary Literature

  1. Haldane E, Ross G (1985) The philosophical work of Descartes. Cambridge University Press, Cambridge

    Google Scholar 

  2. Popper K, Eccles JF (1977) The self and its brain. Springer, New York

    Google Scholar 

  3. Penrose R (1994) Shadows of the mind: A search for the missing science of consciousness. Oxford University Press, Oxford

    Google Scholar 

  4. McGinn C (1991) The problem of consciousness. Blackwell, Oxford

    Google Scholar 

  5. James W (1904) Does consciousness exist? Philos J Psychol Sci Methods 1:477–491

    Google Scholar 

  6. Edelman GM (1989) The remembered present. Basic Books, New York

    Google Scholar 

  7. Crick F, Koch C (1990) Towards a neurobiological theory of consciousness. Semin Neurosci 2:263–275

    Google Scholar 

  8. Dalton TC, Baars BJ (2003) Consciousness regained: The scientific restoration of mind and brain. In: Dalton TC, Evans RB (eds) The lifecycle of psychological ideas: Understanding the prominence and the dynamics of intellectual change. Springer, Berlin, pp 203–247

    Google Scholar 

  9. Koch C (2004) The quest for consciousness: A neurobiological approach. Roberts, Greenwood Village

    Google Scholar 

  10. Metzinger T (2000) Neural correlates of consciousness: Empirical and conceptual questions. Press MIT, Cambridge

    Google Scholar 

  11. Llinás R, Ribary U, Contreras D, Pedroarena C (1998) The neuronal basis for consciousness. Philos Trans Soc R Lond Biol B Sci 353:1841–1849

    Google Scholar 

  12. Rees G, Kreiman G, Koch C (2002) Neural correlates of consciousness in humans. Nat Rev Neurosci 3(4):261–70

    Google Scholar 

  13. Crutchfield JP, Young K (1989) Inferring statistical complexity. Phys Rev Lett 63:105–108

    MathSciNet  ADS  Google Scholar 

  14. Zurek WH (1990) Complexity, entropy, and the physics of information. Addison-Wesley, Redwood City

    Google Scholar 

  15. Adami C (2002) What is complexity? Bioessays 24:1085–1094

    Google Scholar 

  16. Tye M (2007) Qualia. In: Zalta E (ed) The Stanford Encyclopedia of Philosophy (Summer 2008 Edition). http://plato.stanford.edu/archives/sum2008/entries/qualia/

  17. Seth AK, Baars BJ (2005) Neural Darwinism and consciousness. Conscious Cogn 14:140–168

    Google Scholar 

  18. Edelman GM (2003) Naturalizing consciousness: A theoretical framework. Proc Natl Acad Sci USA 100(9):5520–5524

    ADS  Google Scholar 

  19. Seth AK, Baars BJ, Edelman DB (2005) Criteria for consciousness in humans and other mammals. Conscious Cogn 14(1):119–139

    Google Scholar 

  20. Edelman DB, Baars BJ, Seth AK (2005) Identifying the hallmarks of consciousness in non‐mammalian species. Conscious Cogn 14(1):169–187

    Google Scholar 

  21. Laureys S (2005) The neural correlate of (un)awareness: Lessons from the vegetative state. Trends Cogn Sci 9:556–559

    Google Scholar 

  22. Tononi G, Edelman GM (1998) Consciousness and complexity. Science 282:1846–1851

    Google Scholar 

  23. Seth AK, Izhikevich E, Reeke GN, Edelman GM (2006) Theories and measures of consciousness: An extended framework. Proc Natl Acad Sci USA 103(28):10799–10804

    ADS  Google Scholar 

  24. Tononi G (2004) An information integration theory of consciousness. Neuroscience BMC 5(1):42

    Google Scholar 

  25. Gazzaniga MS (2005) Forty-five years of split-brain research and still going strong. Nat Rev Neurosci 6:653–659

    Google Scholar 

  26. Pashler H (1994) Dual-task interference in simple tasks: data and theory. Psychol Bull 116:220–244

    Google Scholar 

  27. Zeki S (1990) A century of cerebral achromatopsia. Brain 113(6):1721–1777

    Google Scholar 

  28. Edelman GM, Tononi G (2000) A universe of consciousness: How matter becomes imagination. Basic Books, New York

    Google Scholar 

  29. Tononi G, McIntosh AR, Russell DP, Edelman GM (1998) Functional clustering: identifying strongly interactive brain regions in neuroimaging data. Neuroimage 7:133–149

    Google Scholar 

  30. Tononi G, Sporns O, Edelman GM (1992) Reentry and the problem of integrating multiple cortical areas: Simulation of dynamic integration in the visual system. Cerebral Cortex 2(4):31–35

    Google Scholar 

  31. Seth AK, McKinstry JL, Edelman GM, Krichmar JL (2004) Visual binding through reentrant connectivity and dynamic synchronization in a brain-based device. Cerebral Cortex 14:1185–99

    Google Scholar 

  32. Edelman GM (1987) Neural Darwinism. Basic Books, New York

    Google Scholar 

  33. Edelman GM (1993) Selection and reentrant signaling in higher brain function. Neuron 10:115–125

    Google Scholar 

  34. Friston KJ, Tononi G, Reeke GN, Sporns O, Edelman GM (1994) Value‐dependent selection in the brain: Simulation in a synthetic neural model. Neuroscience 59:229–243

    Google Scholar 

  35. Tononi G, Sporns O, Edelman GM (1999) Measures of degeneracy and redundancy in biological networks. Proc Natl Acad Sci USA 96:3257–3262

    ADS  Google Scholar 

  36. Edelman GM, Gally J (2001) Degeneracy and complexity in biological systems. Proc Natl Acad Sci USA 98(24):13763–13768

    ADS  Google Scholar 

  37. Kim J (1998) Mind in a Physical World: An Essay on the Mind-Body Problem and Mental Causation. Press MIT/Bradford Books, Cambridge

    Google Scholar 

  38. Wegner D (2003) The illusion of conscious will. Press MIT, Cambridge

    Google Scholar 

  39. Thompson E, Varela F (2001) Radical embodiment: Neural dynamics and consciousness. Trends Cogn Sci 5:418–425

    Google Scholar 

  40. Tononi G, Sporns O, Edelman GM (1994) A measure for brain complexity: Relating functional segregation and integration in the nervous system. Proc Natl Acad Sci USA 91:5033–5037

    ADS  Google Scholar 

  41. Vanduffel W, Payne BR, Lomber SG, Orban GA (1997) Functional impact of cerebral connections. Proc Natl Acad Sci USA 94:7617–7620

    ADS  Google Scholar 

  42. Papoulis A, Pillai SU (2002) Probability, random variables, and stochastic processes, 4th edn. McGraw-Hill, New York

    Google Scholar 

  43. Jones DS (1979) Elementary information theory. Clarendon Press, Oxford

    Google Scholar 

  44. McGill WJ (1954) Multivariate information transmission. Trans IEEE Inform Theory 4:93–111

    MathSciNet  Google Scholar 

  45. de Lucia M, Bottaccio M, Montuori M, Pietronero L (2004) A topological approach to neural complexity. Phys Rev E 71:016114

    Google Scholar 

  46. Tononi G, Edelman GM, Sporns O (1998) Complexity and coherency: Integrating information in the brain. Trends Cogn Sci 2:474–484

    Google Scholar 

  47. Bressler SL (1995) Large-scale cortical networks and cognition. Brain Res Brain Res Rev 20:288–304

    Google Scholar 

  48. Friston K (2002) Beyond phrenology: what can neuroimaging tell us about distributed circuitry? Annu Rev Neurosci 25:221–250

    Google Scholar 

  49. Sporns O, Tononi G, Edelman GM (2000) Theoretical neuroanatomy: Relating anatomical and functional connectivity in graphs and cortical connection matrices. Cerebral Cortex 10:127–141

    Google Scholar 

  50. Sporns O, Tononi G (2002) Classes of network connectivity and dynamics. Complexity 7(1):28–38

    MathSciNet  Google Scholar 

  51. Seth AK, Edelman GM (2004) Theoretical neuroanatomy: Analyzing the structure, dynamics and function of neuronal networks. In: Ben Naim E, Fraunfelder H, Toroczkai Z (eds) Complex networks. Lecture Notes in Physics. Springer, Berlin, pp 487–518

    Google Scholar 

  52. Sporns O, Chialvo D, Kaiser M, Hilgetag C (2004) Organization, development and function of complex brain networks. Trends Cogn Sci 8:418–425

    Google Scholar 

  53. Buckley CL, Bullock S (2007) Spatial embedding and complexity: The small-world is not enough. In: Almeida e Costa F (ed) Proceedings of the Ninth European Conference on Artificial Life. Springer, Berlin, pp 986–995

    Google Scholar 

  54. Mitchell M (1997) An introduction to genetic algorithms. Press MIT, Cambridge

    Google Scholar 

  55. Watts DJ, Strogatz SH (1998) Collective dynamics of ‘small world’ networks. Nature 393:440–442

    ADS  Google Scholar 

  56. Sporns O (2004) Complex neural dynamics. In: Jirsa VK, Kelso JAS (eds) Coordination dynamics: Issues and trends. Springer, Berlin, pp 197–215

    Google Scholar 

  57. Sporns O, Kötter R (2004) Motifs in brain networks. PLoBiol S 2:e369–e369

    Google Scholar 

  58. Sporns O (2006) Small-world connectivity, motif composition, and complexity of fractal neuronal connections. Biosystems 85:55–64

    Google Scholar 

  59. Seth AK, Edelman GM (2004) Environment and behavior influence the complexity of evolved neural networks. Adapt Behav 12:5–21

    Google Scholar 

  60. Sporns O, Lungarella M (2006) Evolving coordinated behavior by maximizing information structure. In: Rocha L, Yaeger L, Bedau MS, Floreano D, Goldstone RL, Vespignani A (eds) Proceedings of the 10th European Conference on Artificial Life. Press MIT, Cambridge, pp 323–330

    Google Scholar 

  61. Lungarella M, Sporns O (2006) Mapping information flow in sensorimotor networks. PLoComput S Biol 2:e144–e144

    ADS  Google Scholar 

  62. Tononi G, Sporns O, Edelman GM (1996) A complexity measure for selective matching of signals by the brain. Proc Natl Acad Sci USA 93:3422–3427

    ADS  Google Scholar 

  63. Tononi G, Sporns O (2003) Measuring information integration. Neuroscience BMC 4(1):31

    Google Scholar 

  64. Schreiber T (2000) Measuring information transfer. Phys Rev Lett 85(2):461–4

    ADS  Google Scholar 

  65. Werner G (2007) Perspectives on the neuroscience of cognition and consciousness. Biosystems 87:82–95

    ADS  Google Scholar 

  66. Seth AK (2005) Causal connectivity of evolved neural networks during behavior. Netw Comput Neural Syst 16:35–54

    Google Scholar 

  67. Granger CWJ (1969) Investigating causal relations by econometric models and cross‐spectral methods. Econometrica 37:424–438

    Google Scholar 

  68. Seth AK (2007) Granger causality. Scholarpedia, p 15501

    Google Scholar 

  69. Hamilton JD (1994) Time series analysis. Princeton University Press, Princeton

    Google Scholar 

  70. Geweke J (1982) Measurement of linear dependence and feedback between multiple time series. J Amer Stat Assoc 77:304–13

    MathSciNet  Google Scholar 

  71. Seth AK (2008) Causal networks in simulated neural systems. Cogn Neurodyn 2:49–64

    Google Scholar 

  72. Seth AK, Edelman GM (2007) Distinguishing causal interactions in neural populations. Neural Comput 19:910–933

    MathSciNet  Google Scholar 

  73. Ding M, Chen Y, Bressler S (2006) Granger causality: Basic theory and application to neuroscience. In: Schelter S, Winterhalder M, Timmer J (eds) Handbook of Time Series Analysis. Wiley, Wienheim, pp 438–460

    Google Scholar 

  74. Zellner A (1971) An introduction to Bayesian inference in econometrics. Wiley, New York

    Google Scholar 

  75. Ancona N, Marinazzo D, Stramaglia S (2004) Radial basis function approaches to nonlinear granger causality of time series. Phys Rev E 70:056221

    ADS  Google Scholar 

  76. Chen Y, Rangarajan G, Feng J, Ding M (2004) Analyzing multiple nonlinear time series with extended Granger causality. Phys Lett A 324:26–35

    MathSciNet  ADS  Google Scholar 

  77. Gao S, Seth AK, Kendrick K, Feng J. Partial granger causality: Eliminating exogenous input. J Neurosci Methods 172(1)79–93

    Google Scholar 

  78. Bogen JE (1995) On the neurophysiology of consciousness: I An overview. Conscious Cogn 4:52–62

    ADS  Google Scholar 

  79. Kolb B, Whishaw IQ (1996) Fundamentals of human neuropsychology, 4th edn. Freeman WH, New York

    Google Scholar 

  80. Baars BJ (1988) A cognitive theory of consciousness. Cambridge University Press, New York

    Google Scholar 

  81. Baars BJ (2002) The conscious access hypothesis: Origins and recent evidence. Trends Cogn Sci 6:47–52

    Google Scholar 

  82. Lau HC, Passingham RE (2006) Relative blindsight in normal observers and the neural correlate of visual consciousness. Proc Natl Acad Sci USA 103:18763–18768

    ADS  Google Scholar 

  83. Dehaene S, Naccache L, Cohen L, Bihan DL, Mangin JF, Poline JB, Rivière D (2001) Cerebral mechanisms of word masking and unconscious repetition priming. Nat Neurosci 4:752–758

    Google Scholar 

  84. Floyer‐Lea A, Matthews PM (2004) Changing brain networks for visuomotor control with increased movement automaticity. Neurophysiol J 92:2405–2412

    Google Scholar 

  85. Blake R, Logothetis N (2002) Visual competition. Nat Rev Neurosci 3:13–21

    Google Scholar 

  86. Tononi G, Srinivasan R, Russell DP, Edelman GM (1998) Investigating neural correlates of conscious perception by frequency‐tagged neuromagnetic responses. Proc Natl Acad Sci USA 95:3198–3203

    ADS  Google Scholar 

  87. Srinivasan R, Russell DP, Edelman GM, Tononi G (1999) Increased synchronization of magnetic responses during conscious perception. J Neurosci 19:5435–5448

    Google Scholar 

  88. Silberstein RB, Schier MA, Pipingas A, Ciorciari J, Wood SR, Simpson DG (1990) Steady‐state visually evoked potential topography associated with a visual vigilance task. Brain Topogr 3:337–347

    Google Scholar 

  89. Cosmelli D, David O, Lachaux J-P, Martinerie J, Garnero L, Renault B, Varela F (2004) Waves of consciousness: Ongoing cortical patterns during binocular rivalry. Neuroimage 23:128–140

    Google Scholar 

  90. Nunez P, Srinivasan R (2006) A theoretical basis for standing and traveling brain waves measured with human EEG with implications for an integrated consciousness. Clin Neurophysiol 117:2424–2435

    Google Scholar 

  91. Chen Y, Seth AK, Gally JS, Edelman GM (2003) The power of human brain magnetoencephalographic signals can be modulated up or down by changes in an attentive visual task. Proc Natl Acad Sci USA 100:3501–3506

    ADS  Google Scholar 

  92. Srinivasan R (2004) Internal and external neural synchronization during conscious perception. Int Bifurcat J Chaos 14:825–842

    Google Scholar 

  93. Mashour GA (2004) Consciousness unbound: Toward a paradigm of general anesthesia. Anesthesiology 100:428–433

    Google Scholar 

  94. John ER, Prichep LS, Kox W, Valdés‐Sosa P, Bosch‐Bayard J, Aubert E, Tom M, di Michele F, Gugino LD (2001) Invariant reversible QEEG effects of anesthetics. Conscious Cogn 10:165–183

    Google Scholar 

  95. Massimini M, Ferrarelli F, Huber R, Esser SK, Singh H, Tononi G (2005) Breakdown of cortical effective connectivity during sleep. Science 309:2228–2232

    ADS  Google Scholar 

  96. Stam CJ, Jones BF, Nolte G, Breakspear M, Scheltens P (2007) Small-world networks and functional connectivity in Alzheimer’s disease. Cereb Cortex 17:92–99

    Google Scholar 

  97. Stephan KE, Hilgetag CC, Burns GA, O’Neill MA, Young MP, Kötter R (2000) Computational analysis of functional connectivity between areas of primate cerebral cortex. Philos Trans Soc R Lond Biol B Sci 355:111–126

    Google Scholar 

  98. Turing A (1950) Computing machinery and intelligence. Mind 59:433–460

    MathSciNet  Google Scholar 

  99. Ashby WR (1952) Design for a brain: The origin of adaptive behaviour. Chapman Hall, London

    Google Scholar 

  100. Katchalsky A, Rowland V, Hubermann B (1974) Neurosci Res Prog Bull 12

    Google Scholar 

  101. Haken H (2002) Brain dynamics. Springer, New York

    Google Scholar 

  102. Freeman WJ (1975) Mass action in the nervous system. Academic Press, New York

    Google Scholar 

  103. Freeman WJ (2005) A field‐theoretic approach to understanding scale-free neocortical dynamics. Biol Cybern 92(6):350–359

    MathSciNet  Google Scholar 

  104. Kelso JAS (1995) Dynamic patterns: The self‐organisation of brain and behavior. Press MIT, Cambridge

    Google Scholar 

  105. Werner G (2007) Metastability, criticality and phase transitions in brain and its models. Biosystems 90:496–508

    ADS  Google Scholar 

  106. Izhikevich EM (2006) Dynamical systems in neuroscience: The geometry and excitability of bursting. Press MIT, Cambridge

    Google Scholar 

  107. Bressler S, Kelso J (2001) Cortical coordination dynamics and cognition. Trends Cogn Sci 5:26–36

    Google Scholar 

  108. Friston KJ (1997) Transients, metastability, and neuronal dynamics. Neuroimage 5:164–171

    Google Scholar 

  109. Fingelkurts A (2004) Making complexity simpler: Multivariability and metastability in the brain. Int Neurosci J 114:843–862

    Google Scholar 

  110. Baars BJ (2005) Global workspace theory of consciousness: Toward a cognitive neuroscience of human experience. Prog Brain Res 150:45–53

    ADS  Google Scholar 

  111. Dehaene S, Sergent C, Changeux J-P (2003) A neuronal network model linking subjective reports and objective physiological data during conscious perception. Proc Natl Acad Sci USA 100:8520–8525

    ADS  Google Scholar 

  112. Wallace R (2005) Consciousness: A mathematical treatment of the neuronal global workspace model. Springer, New York

    Google Scholar 

  113. Dehaene S, Kerszberg M, Changeux J-P (1998) A neuronal model of a global workspace in effortful cognitive tasks. Proc Natl Acad Sci USA 95:14529–14534

    ADS  Google Scholar 

  114. Dehaene S, Changeux J-P (2005) Ongoing spontaneous activity controls access to consciousness: a neuronal model for inattentional blindness. PLoBiol S 3:e141–e141

    Google Scholar 

  115. Bollobás B (1985) Random graphs. Academic Press, London

    Google Scholar 

  116. von der Malsburg C (1995) Binding in models of perception and brain function. Curr Opin Neurobiol 5:520–526

    Google Scholar 

  117. Singer W, Gray CM (1995) Visual feature integration and the temporal correlation hypothesis. Annu Rev Neurosci 18:555–586

    Google Scholar 

  118. Fries P, Reynolds JH, Rorie AE, Desimone R (2001) Modulation of oscillatory neuronal synchronization by selective visual attention. Science 291:1560–1563

    ADS  Google Scholar 

  119. Steinmetz PN, Roy A, Fitzgerald PJ, Hsiao SS, Johnson KO, Niebur E (2000) Attention modulates synchronized neuronal firing in primate somatosensory cortex. Nature 404:187–190

    ADS  Google Scholar 

  120. Engel AK, Fries P, König P, Brecht M, Singer W (1999) Temporal binding, binocular rivalry, and consciousness. Conscious Cogn 8:128–151

    Google Scholar 

  121. Melloni L, Molina C, Pena M, Torres D, Singer W, Rodriguez E (2007) Synchronization of neural activity across cortical areas correlates with conscious perception. Neurosci J 27:2858–2865

    Google Scholar 

  122. Palva S, Linkenkaer‐Hansen K, Näätänen R, Palva J (2005) Early neural correlates of conscious somatosensory perception. Neurosci J 25:5248–5258

    Google Scholar 

  123. Meador KJ, Ray PG, Echauz JR, Loring DW, Vachtsevanos GJ (2002) Gamma coherence and conscious perception. Neurology 59:847–854

    Google Scholar 

  124. Shadlen MN, Movshon JA (1999) Synchrony unbound: a critical evaluation of the temporal binding hypothesis. Neuron 24:67–77 111

    Google Scholar 

  125. Crick F, Koch C (2003) A framework for consciousness. Nat Neurosci 6:119–126

    Google Scholar 

  126. Hebb DO (1949) The organization of behavior. Wiley, New York

    Google Scholar 

  127. Lamme VAF (2006) Towards a true neural stance on consciousness. Trends Cogn Sci 10:494–501

    Google Scholar 

  128. Chalmers DJ (1996) The conscious mind: In search of a fundamental theory. Oxford University Press, Oxford

    Google Scholar 

  129. Bennett MR, Hacker PMS (2003) Philosophical foundations of neuroscience. Blackwell, Oxford

    Google Scholar 

  130. Thompson E (2004) Life and mind: A tribute to Francisco Varela. Phenomenol Cogn Sci 3:381–98

    Google Scholar 

  131. Izhikevich E, Gally JS, Edelman GM (2004) Spike‐timing dynamics of neuronal groups. Cerebral Cortex 14:933–944

    Google Scholar 

  132. Seth AK, Dienes Z, Cleeremans A, Overgaard M, Pessoa L (2008) Measuring consciousness: relating behavioural and neurophysiological approaches. Trends Cogn Sci 12:314–21

    Google Scholar 

Books and Reviews

  1. Baars DJ, Banks WP, Newman JB (2003) Essential sources in the scientific study of consciousness. Press MIT, Cambridge

    Google Scholar 

  2. Dorogovtsev SN, Mendes JFF (2003) Evolution of Networks: from biological networks to the Internet and WWW. Oxford University Press, Oxford

    Google Scholar 

  3. Edelman GM (2004) Wider than the sky: The phenomenal gift of consciousness. Yale University Press, New Haven

    Google Scholar 

  4. Edelman GM, Tononi G (2000) A universe of consciousness: How matter becomes imagination. Basic Books, New York

    Google Scholar 

  5. Koch C (2004) The Quest for Consciousness: A Neurobiological Approach. Roberts, Greenwood Village

    Google Scholar 

  6. Metzinger T (2000) Neural correlates of consciousness. Press MIT, Cambridge

    Google Scholar 

  7. Tononi G (2004) An information integration theory of consciousness. Neuroscience BMC 5(1):42

    Google Scholar 

  8. Seth AK, Izhikevich E, Reeke GN, Edelman GM (2006) Theories and measures of consciousness: An extended framework. Proc Natl Acad Sci USA 103(28):10799–10804

    ADS  Google Scholar 

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  1. Department of Informatics, University of Sussex, Brighton, UK

    Anil K. Seth

  2. The Neurosciences Institute, San Diego, USA

    Gerald M. Edelman

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Seth, A.K., Edelman, G.M. (2009). Consciousness and Complexity . In: Meyers, R. (eds) Encyclopedia of Complexity and Systems Science. Springer, New York, NY. https://doi.org/10.1007/978-0-387-30440-3_94

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