Collection

Computational Cognitive Neurodynamics

Submission status
Closed
According to a central dogma of traditional cognitive science, cognitive computation is essentially the stepwise, rule-driven manipulation of discrete symbolic data structures. This view, however, is at variance with the continuous characteristics of natural events, with respect to both states and time. Therefore, any attempt to implement cognitive computation in time-continuous dynamical systems with continuous states, such as neural networks, embodied robots, neuromorphic electronics, or swarm intelligence, requires a mapping of discrete symbolic states onto continuous activation patterns. Moreover, stepwise transitions between symbolic states, that are intentionally interpreted as rule-following, have to be embedded into a framework that covers continuous flow and temporal evolution of neural patterns. The modeling of intelligent behavior comprises a wide field of mathematical methods ranging from discrete mathematics as used in computer science and artificial intelligence, over linear algebra and algebraic representation theory, dynamical systems and neural networks, machine learning and data analysis, up to functional analysis as employed in quantum logic and quantum cognition. The main aim of this Special Issue on "Computational Cognitive Neurodynamics" is to introduce and discuss major problems for the description, analysis, modeling and interpretation of cognitive processes, to review the state-of-the-art of mathematical and computational approaches for intelligent behavior, and to explore emerging algorithms and possible hardware solutions for cognitive neurodynamical systems and artificial intelligence. The list of topic includes but not limited to: - vector logics and vector symbolic - architecturesneuromorphic electronics and algorithms - quantum computing and quantum cognitionneural - networks and neural fields - cognitive dynamical systems - Bayesian neurocognitive models - machine learning and cognitive robotics - neurocomputational vision - computational neurolinguistics

Editors

  • Dr. Peter beim Graben Dr. Peter beim Graben , 

    Dr. Peter beim Graben

    Bernstein Center for Computational Neuroscience Berlin, Humboldt-Universität zu Berlin, Berlin, Germany

  • Prof. Dr. Chris Huyck Prof. Dr. Chris Huyck , 

    Prof. Dr. Chris Huyck

    Department of Computer Science, School of Science & Technology, Middlesex University London, London, UK

  • Prof. Dr. Eduardo Mizraji Prof. Dr. Eduardo Mizraji , 

    Prof. Dr. Eduardo Mizraji

    Group of Cognitive Systems Modeling, Biophysics and Systems Biology Section, Facultad de Ciencias, Universidad de la República, Uruguay

  • Prof. Dr. Andrés Pomi Prof. Dr. Andrés Pomi , 

    Prof. Dr. Andrés Pomi

    Group of Cognitive Systems Modeling, Biophysics and Systems Biology Section, Facultad de Ciencias, Universidad de la República, Uruguay

  • Prof. Dr. Serafim Rodrigues Prof. Dr. Serafim Rodrigues  &

    Prof. Dr. Serafim Rodrigues

    Mathematical, Computational and Experimental Neuroscience, Basque Center for Applied Mathematics BCAM, Bilbao, Basque Country, Spain

  • Dr. Juan C. Valle-Lisboa Dr. Juan C. Valle-Lisboa

    Dr. Juan C. Valle-Lisboa

    Biophysics and Systems Biology Section, Facultad de Ciencias and Interdisciplinary Center of Cognition for Teaching and Learning CICEA, Universidad de la República, Uruguay

Articles (7 in this collection)

  3. Invariants for neural automata

    Authors (first, second and last of 4)

    • Jone Uria-Albizuri
    • Giovanni Sirio Carmantini
    • Serafim Rodrigues
    • Content type: Research Article
    • Open Access
    • Published: 31 May 2023