Special Issue Cognitive Neurodynamics - Extended Deadline 01/01/2023

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Peter beim Graben

nieprzeczytany,
13 gru 2022, 05:03:0313.12.2022
do Eduardo Mizraji, Andrés Pomi, Juan Valle Lisboa, Serafim Rodrigues, Christian Huyck

Dear colleagues and friends,

you may remember our invitation to submit to our envisaged Special Issue of the Springer/Nature journal "Cognitive Neurodynamics"

    https://www.springer.com/journal/11571/

that aims at collecting state-of-the-art research or review articles on "Computational Cognitive Neurodynamics".

We have been asked to extend the deadline over the upcoming holidays. Therefore, we decided to give you another extension by additional four weeks.

New submission deadline: February, 1st, 2023

Kind regards,

Peter

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Description

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 architectures
•    neuromorphic electronics and algorithms
•    quantum computing and quantum cognition
•    neural networks and neural fields
•    cognitive dynamical systems
•    Bayesian neurocognitive models
•    machine learning and cognitive robotics
•    neurocomputational vision
•    computational neurolinguistics

Important Dates
- Submission deadline: November 30, 2022
- Final manuscript due: March 10, 2023
- Tentative publication date: July, 2023

Guest Editors
Dr. Peter beim Graben, Bernstein Center for Computational Neuroscience Berlin, Humboldt-Universität zu Berlin, Berlin, Germany.
Prof. Dr. Chris Huyck, Department of Computer Science, School of Science & Technology, Middlesex University London, London, UK.
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, Group of Cognitive Systems Modeling, Biophysics and Systems Biology Section, Facultad de Ciencias, Universidad de la República, Uruguay.
Prof. Dr. Serafim Rodrigues, Mathematical, Computational and Experimental Neuroscience, Basque Center for Applied Mathematics BCAM, Bilbao, Basque Country, Spain.
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.

-- 

Dr. Peter beim Graben
Bernstein Center for Computational Neuroscience Berlin
https://www.researchgate.net/profile/Peter_Beim_Graben2

-- Actually, physics is too hard for physicists --
D. Hilbert

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