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The human brain from above: an increase in complexity from environmental stimuli to abstractions

Abstract

Contrary to common belief, the brain appears to increase the complexity from the perceived object to the idea of it. Topological models predict indeed that: (a) increases in anatomical/functional dimensions and symmetries occur in the transition from the environment to the higher activities of the brain, and (b) informational entropy in the primary sensory areas is lower than in the higher associative ones. To demonstrate this novel hypothesis, we introduce a straightforward approach to measuring island information levels in fMRI neuroimages, via Rényi entropy derived from tessellated fMRI images. This approach facilitates objective detection of entropy and corresponding information levels in zones of fMRI images generally not taken into account. We found that the Rényi entropy is higher in associative cortices than in the visual primary ones. This suggests that the brain lies in dimensions higher than the environment and that it does not concentrate, but rather dilutes messages coming from external inputs.

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References

  • Bromiley, PA, Thacker, NA, Bouhova-Thacker, E (2010) Shannon entropy, Renyi entropy, and information. Tina 2004-004, Statistic and Inf Series, Imaging Science and Biomedical Engineering, The University of Manchester, UK

  • Duyckaerts G, Godefroy G (2000) Voronoï tessellation to study the numerical density and the spatial distribution of neurons. J Chem Neuroanat 20(1):83–92

    CAS  Article  PubMed  Google Scholar 

  • Edelsbrunner H (2006) Geometry and topology for mesh generation. Cambridge University Press, Cambridge

    Google Scholar 

  • Frank NP, Hart SM (2010) A dynamical system using the Voronoï tessellation. Am Math Mon 117(2):92–112

    Google Scholar 

  • Freeman WJ (2007) Definitions of state variables and state space for brain-computer interface: part 1. Multiple hierarchical levels of brain function. Cogn Neurodyn 1(1):3–14. doi:10.1007/s11571-006-9001-x

    Article  PubMed  Google Scholar 

  • Mandelkow H, de Zwart JA, Duyn JH (2016) Linear discriminant analysis achieves high classification accuracy for the BOLD fMRI response to naturalistic movie stimuli. Front Hum Neurosci 10:128. doi:10.3389/fnhum.2016.00128

    Article  PubMed  PubMed Central  Google Scholar 

  • Nieuwenhuys R, Voogd J, van Huijzen C (2008) The human central nervous system. Springer, Heidelberg

    Book  Google Scholar 

  • Peters JF (2016) Computational proximity. In: Intelligent Systems Reference Library (ed) Excursions in the topology of digital images. Springer, Berlin. doi:10.1007/978-3-319-30262-1

    Google Scholar 

  • Peters JF, İnan E (2016) Strongly near Voronoï nucleus clusters. 1–7. arXiv:1602(03734)

  • Peters JF, Tozzi A, Ramanna S (2016) Brain tissue tessellation shows absence of canonical microcircuits. Neurosci Letters 626:99–105

    CAS  Article  Google Scholar 

  • Peters JF, Ramanna S, Tozzi A, Inan E (2017) BOLD-independent computational entropy assesses functional donut-like structures in brain fMRI image. Frontiers Hum Neurosci. doi:10.3389/fnhum.2017.00038

    Google Scholar 

  • Pexman PM, Siakaluk PD, Yap MJ (2013) Introduction to the research topic meaning in mind: semantic richness effects in language processing. Hum Neurosci, Front. doi:10.3389/fnhum.2013.00723

    Google Scholar 

  • Rényi A (1961) On measures of entropy and information. In: Proceedings of the fourth Berkeley symposium on mathematical statistics and probability, vol. I, University of California Press, Berkeley, pp 547–457 (MR0132570)

  • Rényi A (1966) On the amount of information in a random variable concerning an event. J Math Sci 1:30–33 (MR0210263)

    Google Scholar 

  • Rényi A (1982) Tagebuch über die Informationstheorie. VEB Deutcher der Wissenschaften, Berlin (MR0707097)

    Google Scholar 

  • Taylor P, Hobbs JN, Burroni J, Siegelmann HT (2015) The global landscape of cognition: hierarchical aggregation as an organizational principle of human cortical networks and functions. Sci Rep 5:18112. doi:10.1038/srep18112

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  • Tozzi A (2015) Information processing in the CNS: a supramolecular chemistry? Cogn Neurodyn 9(5):463–477

    Article  PubMed  PubMed Central  Google Scholar 

  • Tozzi A, Peters JF (2016a) Towards a fourth spatial dimension of brain activity. Cogn Neurodyn 10(3):189–199. doi:10.1007/s11571-016-9379-z

    Article  PubMed  PubMed Central  Google Scholar 

  • Tozzi A, Peters JF (2016b) A topological approach unveils system invariances and broken symmetries in the brain. J Neurosci Res 94(5):351–365. doi:10.1002/jnr.23720

    CAS  Article  PubMed  Google Scholar 

  • Werner S, Noppeney U (2009) Superadditive responses in superior temporal sulcus predict audiovisual benefits in object categorization. Cereb Cortex 20(8):1829–1842

    Article  PubMed  Google Scholar 

  • Xing M, Ajilore O, Wolfson OE, Abbott C, MacNamara A et al (2016) Brain informatics and health. Ser Lect Notes Comput Sci 9919:149. doi:10.1007/978-3-319-47103-7_15

    Article  Google Scholar 

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Correspondence to Arturo Tozzi.

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Peters, J.F., Tozzi, A., Ramanna, S. et al. The human brain from above: an increase in complexity from environmental stimuli to abstractions. Cogn Neurodyn 11, 391–394 (2017). https://doi.org/10.1007/s11571-017-9428-2

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  • DOI: https://doi.org/10.1007/s11571-017-9428-2

Keywords

  • Entropy
  • Topology
  • fMRI
  • Tessellation