Brain like Computing, Communication and Machines

A special issue of Information (ISSN 2078-2489).

Deadline for manuscript submissions: closed (31 October 2012) | Viewed by 37488

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International Center for Materials and Nanoarchitectronics (MANA), Research Center for Advanced Measurement and Characterization (RCAMC), National Institute for Materials Science (NIMS), 1-2-1 Sengen, Main Bldg, Tsukuba 815, Japan
Interests: bioinformatics; information theory; modelling human brain; dielectric resonance of biomaterials; proteins; neuron; organic jelly-based neuromorphic device; artificial brain; molecular robots for drug delivery
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Special Issue Information

Dear Colleagues,

In the early 20th century, the discovery of computers triggered by fundamental formulations of information theory and switches started a revolution that defines the current human civilization. In the early 21st century we expect another revolution when brain science will be understood and a movement will begin to implement those technologies and we have no doubt that Brain age machines will take over. Therefore, we welcome brain age machines to take over, the people who will play key role in this transformation to the new age, we invite them to this special issue and wish to carry out brain storming sessions in the articles on the paths of development. We plan to include those topics which are directly involved with this research of brain mimicking functionally, neurobiologically and outline of those projects which have undertaken this astronomical challenge. We will outline a road map of this century, how brain-like computing will advance forward. We will not remain confined in the domain of brain like computing, rather, we will try to find how many different research fields will be influenced by such activities. For example, materials science, electronics, robotics.

Dr. Anirban Bandyopadhyay
Guest Editor

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Published Papers (3 papers)

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Research

155 KiB  
Article
Quaternionic Multilayer Perceptron with Local Analyticity
by Teijiro Isokawa, Haruhiko Nishimura and Nobuyuki Matsui
Information 2012, 3(4), 756-770; https://doi.org/10.3390/info3040756 - 28 Nov 2012
Cited by 34 | Viewed by 15249
Abstract
A multi-layered perceptron type neural network is presented and analyzed in this paper. All neuronal parameters such as input, output, action potential and connection weight are encoded by quaternions, which are a class of hypercomplex number system. Local analytic condition is imposed on [...] Read more.
A multi-layered perceptron type neural network is presented and analyzed in this paper. All neuronal parameters such as input, output, action potential and connection weight are encoded by quaternions, which are a class of hypercomplex number system. Local analytic condition is imposed on the activation function in updating neurons’ states in order to construct learning algorithm for this network. An error back-propagation algorithm is introduced for modifying the connection weights of the network. Full article
(This article belongs to the Special Issue Brain like Computing, Communication and Machines)
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1054 KiB  
Article
Fröhlich Condensate: Emergence of Synergetic Dissipative Structures in Information Processing Biological and Condensed Matter Systems
by Áurea R. Vasconcellos, Fabio Stucchi Vannucchi, Sérgio Mascarenhas and Roberto Luzzi
Information 2012, 3(4), 601-620; https://doi.org/10.3390/info3040601 - 24 Oct 2012
Cited by 11 | Viewed by 12407
Abstract
We consider the case of a peculiar complex behavior in open boson systems sufficiently away from equilibrium, having relevance in the functioning of information-processing biological and condensed matter systems. This is the so-called Fröhlich–Bose–Einstein condensation, a self-organizing-synergetic dissipative structure, a phenomenon apparently working [...] Read more.
We consider the case of a peculiar complex behavior in open boson systems sufficiently away from equilibrium, having relevance in the functioning of information-processing biological and condensed matter systems. This is the so-called Fröhlich–Bose–Einstein condensation, a self-organizing-synergetic dissipative structure, a phenomenon apparently working in biological processes and present in several cases of systems of boson-like quasi-particles in condensed inorganic matter. Emphasis is centered on the quantum-mechanical-statistical irreversible thermodynamics of these open systems, and the informational characteristics of the phenomena. Full article
(This article belongs to the Special Issue Brain like Computing, Communication and Machines)
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262 KiB  
Article
Holographic View of the Brain Memory Mechanism Based on Evanescent Superluminal Photons
by Takaaki Musha
Information 2012, 3(3), 344-350; https://doi.org/10.3390/info3030344 - 17 Aug 2012
Cited by 4 | Viewed by 8896
Abstract
D. Pollen and M. Trachtenberg proposed the holographic brain theory to help explain the existence of photographic memories in some people. They suggested that such individuals had more vivid memories because they somehow could access a very large region of their memory holograms. [...] Read more.
D. Pollen and M. Trachtenberg proposed the holographic brain theory to help explain the existence of photographic memories in some people. They suggested that such individuals had more vivid memories because they somehow could access a very large region of their memory holograms. Hameroff suggested in his paper that cylindrical neuronal microtubule cavities, or centrioles, function as waveguides for the evanescent photons for quantum signal processing. The supposition is that microtubular structures of the brain function as a coherent fiber bundle set used to store holographic images, as would a fiber-optic holographic system. In this paper, the author proposes that superluminal photons propagating inside the microtubules via evanescent waves could provide the access needed to record or retrieve a quantum coherent entangled holographic memory. Full article
(This article belongs to the Special Issue Brain like Computing, Communication and Machines)
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