Special Issue of "Cognitive Neurodynamics" (Springer/Nature)

[Peter beim Graben]

Dear colleagues and friends,

we are currrently organizing a 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" and we have the pleasure to
cordially invite you as one of the leading experts in the field to
submit some of your recent results.

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