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Formal Tools for the Analysis of Brain-Like Structures and Dynamics

  • Chapter
Creating Brain-Like Intelligence

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5436))

Abstract

Brains and artificial brainlike structures are paradigms of complex systems, and as such, they require a wide range of mathematical tools for their analysis. One can analyze their static structure as a network abstracted from neuroanatomical results of the arrangement of neurons and the synaptic connections between them. Such structures could underly, for instance, feature binding when neuronal groups coding for specific properties of objects are linked to neurons that represent the spatial location of the object in question. – One can then investigate what types of dynamics such abstracted networks can support, and what dynamical phenomena can readily occur. An example is synchronization. In fact, flexible and rapid synchronization between specific groups of neurons has been suggested as a dynamical mechanism for feature binding in brains [54]. In order to identify non-trivial dynamical patterns with complex structures, one needs corresponding complexity measures, as developed in [51,52,5]. Ultimately, however, any such dynamical features derive their meaning from their role in processing information. Neurons filter and select information, encode it by transforming it into an internal representation, and possibly also decode it, for instance by deriving specific motor commands as a reaction to certain sensory information.

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Author information

Authors and Affiliations

  1. Max Planck Institute for Mathematics in the Sciences, Inselstr. 22, 04103, Leipzig, Germany

    Jürgen Jost

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  1. Jürgen Jost
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Editors and Affiliations

  1. Honda Research Institute Europe GmbH, 63073 Offenbach/Main, Germany

    Bernhard Sendhoff

  2. Honda Research Institute Europe GmbH, Carl-Legien-Strasse 30, 63073, Offenbach/Main, Germany

    Edgar Körner

  3. Dept. of Psychological and Brain Sciences, Indiana University, IN 47405, Bloomington, USA

    Olaf Sporns

  4. Faculty of Technology, Neuroinformatics Group, Bielefeld University, Universitätsstr. 25, 33615, Bielefeld, Germany

    Helge Ritter

  5. Okinawa Institute of Science and Technology, Neural Computation Unit,, 12-22 Suzaki, Uruma, 904-2234, Okinawa, Japan

    Kenji Doya

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Jost, J. (2009). Formal Tools for the Analysis of Brain-Like Structures and Dynamics. In: Sendhoff, B., Körner, E., Sporns, O., Ritter, H., Doya, K. (eds) Creating Brain-Like Intelligence. Lecture Notes in Computer Science(), vol 5436. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00616-6_4

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  • DOI: https://doi.org/10.1007/978-3-642-00616-6_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-00615-9

  • Online ISBN: 978-3-642-00616-6

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