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Increase of Universality in Human Brain during Mental Imagery from Visual Perception

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  • Joydeep Bhattacharya

Abstract

Background: Different complex systems behave in a similar way near their critical points of phase transitions which leads to an emergence of a universal scaling behaviour. Universality indirectly implies a long-range correlation between constituent subsystems. As the distributed correlated processing is a hallmark of higher complex cognition, I investigated a measure of universality in human brain during perception and mental imagery of complex real-life visual object like visual art. Methodology/Principal Findings: A new method was presented to estimate the strength of hidden universal structure in a multivariate data set. In this study, I investigated this method in the electrical activities (electroencephalogram signals) of human brain during complex cognition. Two broad groups - artists and non-artists - were studied during the encoding (perception) and retrieval (mental imagery) phases of actual paintings. Universal structure was found to be stronger in visual imagery than in visual perception, and this difference was stronger in artists than in non-artists. Further, this effect was found to be largest in the theta band oscillations and over the prefrontal regions bilaterally. Conclusions/Significance: Phase transition like dynamics was observed in the electrical activities of human brain during complex cognitive processing, and closeness to phase transition was higher in mental imagery than in real perception. Further, the effect of long-term training on the universal scaling was also demonstrated.

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  • Joydeep Bhattacharya, 2009. "Increase of Universality in Human Brain during Mental Imagery from Visual Perception," PLOS ONE, Public Library of Science, vol. 4(1), pages 1-11, January.
    • Handle: RePEc:plo:pone00:0004121
    DOI: 10.1371/journal.pone.0004121
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    References listed on IDEAS

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    1. Ivanov, P.Ch & Rosenblum, M.G & Peng, C.-K & Mietus, J.E & Havlin, S & Stanley, H.E & Goldberger, A.L, 1998. "Scaling and universality in heart rate variability distributions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 249(1), pages 587-593.
    2. Jayanth R. Banavar & John Damuth & Amos Maritan & Andrea Rinaldo, 2002. "Modelling universality and scaling," Nature, Nature, vol. 420(6916), pages 626-626, December.
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    1. Karkare, Siddharth & Saha, Goutam & Bhattacharya, Joydeep, 2009. "Investigating long-range correlation properties in EEG during complex cognitive tasks," Chaos, Solitons & Fractals, Elsevier, vol. 42(4), pages 2067-2073.
    2. Banerjee, Archi & Sanyal, Shankha & Patranabis, Anirban & Banerjee, Kaushik & Guhathakurta, Tarit & Sengupta, Ranjan & Ghosh, Dipak & Ghose, Partha, 2016. "Study on Brain Dynamics by Non Linear Analysis of Music Induced EEG Signals," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 444(C), pages 110-120.
    3. Marieke van Rooij & Guy Van Orden, 2011. "It's about Space, It's about Time, Neuroeconomics and the Brain Sublime," Journal of Economic Perspectives, American Economic Association, vol. 25(4), pages 31-56, Fall.

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