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Experimental Investigation of High-Resolution Spatio-Temporal Patterns

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Cognitive Phase Transitions in the Cerebral Cortex - Enhancing the Neuron Doctrine by Modeling Neural Fields

Part of the book series: Studies in Systems, Decision and Control ((SSDC,volume 39))

Abstract

In the past decades, a wide range of experiments have been conducted using invasive and non-invasive techniques to analyze neural correlates of cognitive behaviors. Here we introduce examples of high-resolution intracranial electrocorticogram (ECoG) experiments with rabbits and human participants, as well as noninvasive scalp electroencephalogram (EEG) experiments. Results of these experiments will be used to illustrate the neurodynamic principles of cognition discussed in this work.

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References

  1. Barrie JM, Freeman WJ, Lenhart M (1996) Modulation by discriminative training of spatial patterns of gamma EEG amplitude and phase in neocortex of rabbits. J Neurophysiol 76:520–539

    Google Scholar 

  2. Freeman WJ, Holmes MD, West GA, Vanhatalo S (2006) Fine spatiotemporal structure of phase in human intracranial EEG. Clin Neurophysiol 117:1228–1243

    Article  Google Scholar 

  3. Menon V, Freeman WJ, Cutillo BA, Desmond JE, Ward MF, Bressler SL, Laxer KD, Barbaro N, Gevins AS (1996) Spatio-temporal correlations in human gamma band electrocorticograms. Electroencephalogr Clin Neurophysiol 98(2):89–102

    Article  Google Scholar 

  4. Freeman WJ (1995) The Hebbian paradigm reintegrated: local reverberations as internal representations. Behav Brain Sci 18(4):631–631

    Article  Google Scholar 

  5. Freeman WJ, (2000/2006) Neurodynamics. An Exploration of Mesoscopic Brain Dynamics. Springer, London. Electronic version, http://sulcus.berkeley.edu/

    Google Scholar 

  6. Freeman WJ, Burke BC, Holmes MD (2003) Aperiodic phase re-setting in scalp EEG of beta-gamma oscillations by state transitions at alpha-theta rates. Hum Brain Mapp 19(4):248–272

    Article  Google Scholar 

  7. Liley DT, Alexander DM, Wright JJ, Aldous MD (1999) Alpha rhythm emerges from large-scale networks of realistically coupled multicompartmental model cortical neurons. Netw: Comput Neural Syst 10(1):79–92

    Article  MATH  Google Scholar 

  8. Nunez PL, Cutillo BA (eds) (1995) Neocortical dynamics and human EEG rhythms. Oxford University Press, New York

    Google Scholar 

  9. Wright JJ, Liley DTJ (1996) Dynamics of the brain at global and microscopic scales. Neural Netw EEG, Behav Brain Sci 19(1996):285–320

    Article  Google Scholar 

  10. Tallon-Baudry C, Bertrand O, Delpuech C, Pernier J (1996) Stimulus-specificity of phase-locked and non phase-locked 40-Hz visual responses in human. J Neurosci 16:4240–4249

    Google Scholar 

  11. Tallon-Baudry C, Bertrand O, Peronnet F, Pernier J (1998) Induced gamma-band activity during the delay of a visual short-term memory task in humans. J Neurosci 18:4244–4254

    Google Scholar 

  12. Muller MM, Bosch J, Elbert T, Kreiter A, Valdes Sosa M, Valdes Sosa P, Rockstroh B (1996) Visually induced gamma band responses in human EEG—a link to animal studies. Exp Brain Res 112:96–112

    Article  Google Scholar 

  13. Rodriguez E, George N, Lachaux J-P, Martinerie J, Renault B, Varela F (1999) Perception’s shadow: long-distance synchronization of human brain activity. Nature 397:430–433

    Article  Google Scholar 

  14. Miltner WHR, Braun C, Matthias A, Witte H, Taub E (1999) Coherence of gamma-band EEG activity as a basis for associative learning. Nature 397(6718):434–436

    Article  Google Scholar 

  15. Milner B (1966) Amnesia following operation on the temporal lobes. In: Whitty CWM, Zangwill OM (eds) Amnesia. Butterworths, London, pp 109–133

    Google Scholar 

  16. Freeman WJ (1975/2004) Mass action in the nervous system. Academic Press, New York. Electronic version 2004—http://sulcus.berkeley.edu/MANSWWW/MANSWWW.html

    Google Scholar 

  17. von der Malsburg C (1983) How are nervous structures organized? In: Basar E, Flohr H, Haken H, Mandell AJ (eds) Synergetics of the Brain. Springer, Berlin, pp 238–249

    Chapter  Google Scholar 

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

    Article  Google Scholar 

  19. Ramon C, Freeman WJ, Holmes M, Ishimaru A, Haueisen J, Schimpf PH, Rezvanian E (2009) Similarities between simulated spatial spectra of scalp EEG MEG Structural MRI. Brain topogr 22(3):191–196

    Article  Google Scholar 

  20. Ramon C, Schimpf PH, Haueisen J (2006) Influence of head models on EEG simulations and inverse source localizations. Biomed Eng Online 5(1):10

    Article  Google Scholar 

  21. Haueisen J, Tuch DS, Ramon C, Schimpf PH, Wedeen VJ, George JS, Belliveau JW (2002) The influence of brain tissue anisotropy on human EEG and MEG. Neuroimage 15(1):159–166

    Article  Google Scholar 

  22. Ramon C, Gehin C, Schmitt PM (2006) Interface pressure monitoring for a secured instrumented childbirth. In: 28th Annual International Conference of the IEEE Engineering in Medicine and Biology Society EMBS’06, p 3186–3189

    Google Scholar 

  23. Geddes LA, Baker LE (1967) The specific resistance of biological materials. A compendium of data for the biomedical engineer and physiologist. Med Biol Eng 5(3):271–293

    Article  Google Scholar 

  24. Foster KR, Schwan HP (1989) Dielectric properties of tissues and biological materials: a critical review. CRC Crit Rev Biomed Eng 17:25–104

    Google Scholar 

  25. Gabriel S, Lau RW, Gabriel C (1996) The dielectric properties of biological tissues: II measurements in the frequency range 10 Hz to 20 GHz. Phys Med Biol 41(11):2251

    Article  Google Scholar 

  26. Schimpf PH (2007) Application of quasi-static magnetic reciprocity to finite element models of the meg lead-field. IEEE Trans Biomed Eng 54(11):2082–2088

    Article  Google Scholar 

  27. Freeman WJ (2001) How brains make up their minds. Columbia University Press, New York

    Google Scholar 

  28. Schroeder M (1991) Fractals, chaos power laws. WH Freeman Publishers, New York

    MATH  Google Scholar 

  29. Freeman WJ, Zhai J (2009) Simulated power spectral density (PSD) of background electrocorticogram (ECoG). Cogn Neurodyn 3(1):97–103

    Article  Google Scholar 

  30. Freeman WJ (2004) Origin, structure, and role of background EEG activity. Part 1 Analytic amplitude. Clin Neurophysiol 115:2077–2088

    Article  Google Scholar 

  31. Hartline HK, Ratliff F (1958) Spatial summation of inhibitory influences in the eye of Limulus and the mutual interaction of receptor units. J Gen Physiol 41:1049–1066

    Article  Google Scholar 

  32. Freyer F, Aquino K, Robinson PA, Ritter P, Breakspear M (2009) Bistability and non-Gaussian fluctuations in spontaneous cortical activity. J Neurosci 29(26):8512–8524

    Article  Google Scholar 

  33. Pikovsky A, Rosenblum M, Kurths J (2001) Synchronization a universal concept non-linear science. Cambridge University Press, Cambridge

    Book  MATH  Google Scholar 

  34. Freeman WJ, Burke BC (2003) A neurobiological theory of meaning in perception. Part 4. Multicortical patterns of amplitude modulation in gamma EEG. Int J Bifurc Chaos 13:2857–2866

    Google Scholar 

  35. Freeman WJ, Baird B (1987) Relation of olfactory EEG to behavior: spatial analysis. Behav Neurosci 101(3):393

    Article  Google Scholar 

  36. Freeman WJ, Barrie JM (2000) Analysis of spatial patterns of phase in neocortical gamma EEGs in rabbit. J Neurophysiol 84(3):1266–1278

    Google Scholar 

  37. Sammon JW (1969) A nonlinear mapping for data structure analysis. IEEE Trans Comput, C-18:401–409

    Google Scholar 

  38. Freeman WJ (2005) Origin, structure, and role of background EEG activity. Part 3. Neural frame classification. Clin Neurophysiol 116(5):1118–1129

    Article  Google Scholar 

  39. Pockett S, Bold GEJ, Freeman WJ (2009) EEG synchrony during a perceptual-cognitive task: widespread phase synchrony at all frequencies. Clin Neurophysiol 120:695–708

    Article  Google Scholar 

  40. Ruiz Y, Pockett S, Freeman WJ, Gonzales E, Guang Li (2010) A method to study global spatial patterns related to sensory perception in scalp EEG. J Neurosci Methods 191:110–118

    Article  Google Scholar 

  41. Ohl FW, Scheich H, Freeman WJ (2001) Change in pattern of ongoing cortical activity with auditory category learning. Nature 412:733–736

    Article  Google Scholar 

  42. Kozma R, Freeman WJ (2002) Classification of EEG patterns using nonlinear neurodynamics and chaos. Neurocomputing 44–46:1107–1112

    Article  MATH  Google Scholar 

  43. Kay LM, Freeman WJ (1998) Bidirectional processing in the olfactory-limbic axis during olfactory behavior. Behav Neurosci 112:541–553

    Article  Google Scholar 

  44. Rice SO (1950) Mathematical analysis of random noise and appendixes., Technical Publications Monograph B-1589Bell Telephone Labs Inc, New York

    Google Scholar 

  45. Freeman WJ, Ahlfors SM, Menon V (2009) Combining EEG, MEG and fMRI signals to characterize mesoscopic patterns of brain activity related to cognition. Special issue (Lorig TS (ed)). Int J Psychophysiol 73(1):43–52

    Google Scholar 

  46. Freeman WJ, Quian Quiroga R (2013) Imaging brain function with EEG: advanced temporal and spatial analysis of electroencephalographic and electrocorticographic signals. Springer, New York

    Book  Google Scholar 

  47. Freeman WJ (2009) Deep analysis of perception through dynamic structures that emerge in cortical activity from self-regulated noise. Cogn Neurodyn 3(1):105–116

    Article  Google Scholar 

  48. Freeman WJ (2004) Origin, structure, and role of background EEG activity. Part 2 Analytic phase. Clin Neurophysiol 115:2089–2107

    Article  Google Scholar 

  49. Freeman WJ, Gaál G, Jorsten R (2003) A neurobiological theory of meaning in perception part III: multiple cortical areas synchronize without loss of local autonomy. Int J Bifurc Chaos 13(10):2845–2856

    Article  MATH  Google Scholar 

  50. Skarda CA, Freeman WJ (1987) How brains make chaos in order to make sense of the world. Behav Brain Sci 10:161–195

    Article  Google Scholar 

  51. Freeman WJ, Kozma R (2010) Freeman’s mass action. Scholarpedia 5(1):8040

    Article  Google Scholar 

  52. Freeman WJ, Vitiello G (2010) Vortices in brain waves. Int J Mod Phy B 24(17):3269–3295

    Article  MathSciNet  MATH  Google Scholar 

  53. Kozma R, Freeman WJ (2008) Intermittent spatio-temporal de-synchronization and sequenced synchrony in ECoG signals. Chaos 18:037131

    Article  Google Scholar 

  54. Freeman WJ, Rogers LJ (2002) Fine temporal resolution of analytic phase reveals episodic synchronization by state transitions in gamma EEG. J Neurophysiol 87:937–945

    Article  Google Scholar 

  55. Freeman WJ (2007) Proposed cortical “shutter” mechanism in cinematographic perception. In: Perlovsky L, Kozma R (eds) Neurodynamics of cognition and consciousness. Springer, Heidelberg, pp 11–38

    Chapter  Google Scholar 

  56. Braitenberg V, Schuz A (1998) Cortex: statistics and geometry of neuronal connectivity, 2nd edn. Springer, Berlin

    Book  Google Scholar 

  57. Capolupo A, Freeman WJ, Vitiello G (2013) Dissipation of ‘dark energy’ by cortex in knowledge retrieval. Phys Life Rev, Online. doi:10.1016/j.plrev.2013.01.001

    Google Scholar 

  58. Freeman WJ (2015) Perspectives: mechanism and significance of global coherence in scalp EEG. In: Buzsaki G, Freeman WJ, (eds)) Current opinion in neurobiology 31: brain rhythms and coordination, pp 199–207

    Google Scholar 

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Authors and Affiliations

  1. Department of Mathematical Sciences, University of Memphis, Memphis, TN, USA

    Robert Kozma

  2. Division of Neurobiology, University of California at Berkele, Berkeley, CA, USA

    Walter J. Freeman

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  1. Robert Kozma
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  2. Walter J. Freeman
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Correspondence to Robert Kozma .

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Kozma, R., Freeman, W.J. (2016). Experimental Investigation of High-Resolution Spatio-Temporal Patterns. In: Cognitive Phase Transitions in the Cerebral Cortex - Enhancing the Neuron Doctrine by Modeling Neural Fields. Studies in Systems, Decision and Control, vol 39. Springer, Cham. https://doi.org/10.1007/978-3-319-24406-8_2

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  • DOI: https://doi.org/10.1007/978-3-319-24406-8_2

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-24406-8

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