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Replicating a Learning Brain’s Cortex in a Humanoid Bot: Pyramidal Neurons Govern Geometry of Hexagonal Close Packing of the Cortical Column Assemblies-II

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Rhythmic Advantages in Big Data and Machine Learning

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Abstract

As a human brain learns, the hexagonal close packing of cortical column deforms, we have replicated the process using artificial cortical columns made of capillary glass tubes and placing artificial cortex on a humanoid bot built by us. Initially, we theoretically constructed the neurons using dielectric material to emulate the biological cortex. Using those neurons, we constructed nineteen cortical columns, each made of twenty-six distinct neuron compositions, and explored the electric and magnetic field distributions around them. We re-oriented neurons theoretically and experimentally on a 1:100 larger scale to tune the electric and magnetic fields in the assembly of cortical columns and replicated change in the symmetry of the assembly of cortical columns as it happens during decision-making in the biological brain’s cortex. We placed an additional sheet of cortical columns made with organic nanowire on the head of the humanoid bot. Monochromatic laser lights of 12 different colors were sent through the thermoplastic embedded capillary tube-based cortical column assemblies. The capillary tube was filled with helical carbon nanotubes with different solvents. Software-free, purely analog bot sensed from environment visual, sound data and we monitored live using laser light how cortical columns emit modified optical and magnetic vortices through the bot’s cortex layer.

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Acknowledgements

Authors acknowledge the Asian office of Aerospace R&D (AOARD) a part of United States Air Force (USAF) for the grant no FA2386-16-1-0003 (2016–2019) on electromagnetic resonance-based communication and intelligence of biomaterials.

Author information

Authors and Affiliations

  1. International Center for Materials and Nanoarchitectronics (MANA), Research Center for Advanced Measurement and Characterization (RCAMC), NIMS, 1-2-1 Sengen, Tsukuba, Ibaraki, 3050047, Japan

    Pushpendra Singh, Pathik Sahoo, Daisuke Fujita & Anirban Bandyopadhyay

  2. Amity School of Applied Sciences, Amity University Rajasthan, Jaipur Delhi Highway, Kant Kalwar, Jaipur, N11C, Rajasthan, India

    Pushpendra Singh & Kanad Ray

  3. Materials Science and Technology Division, CSIR-National Institute for Interdisciplinary Science and Technology (CSIR-NIIST), Thiruvanathapuram, 695019, Kerala, India

    B. Aswathy

  4. Chemical Science and Technology Division, CSIR-North East Institute of Science and Technology, NEIST, Jorhat, 785006, Assam, India

    Subrata Ghosh

  5. Academy of Scientific and Innovative Research (AcSIR), CSIR-NEIST Campus, Jorhat, 785006, Assam, India

    Subrata Ghosh

Authors
  1. Pushpendra Singh
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  2. Pathik Sahoo
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  3. B. Aswathy
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  4. Kanad Ray
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  5. Subrata Ghosh
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  6. Daisuke Fujita
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  7. Anirban Bandyopadhyay
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Contributions

A.B. (Anirban Bandyopadhyay) conceived and designed research; Pu.Si. (Pushpendra Singh) and A.B. performed theoretical and experimental study; Pu.Si. drafted manuscript; A.B. and Pu.Si. edited and revised manuscript, K.R. AsB and P.Sa. S.G. reviewed the work.

Editor information

Editors and Affiliations

  1. National Institute for Materials Science, Tsukuba, Japan

    Anirban Bandyopadhyay

  2. Department of Physics, AMITY University Rajasthan, Jaipur, India

    Kanad Ray

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Singh, P. et al. (2022). Replicating a Learning Brain’s Cortex in a Humanoid Bot: Pyramidal Neurons Govern Geometry of Hexagonal Close Packing of the Cortical Column Assemblies-II. In: Bandyopadhyay, A., Ray, K. (eds) Rhythmic Advantages in Big Data and Machine Learning . Studies in Rhythm Engineering. Springer, Singapore. https://doi.org/10.1007/978-981-16-5723-8_6

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