Listed on
(Coverage)
JCR2014-2021
SJR2008-2020;2022
CiteScore2011-2021
SCIE2014-2023
SCOPUS2017-2024
MEDLINE2016-2023
DOAJ2017-2023
EMBASE2016-2022
OA Info.
| OA |
oa mark
based on the information
- 2017;2018;2019;2020;2021;2022;2023;
|
| Keywords |
neural computing, neural networks, artificial intelligence, neural engineering, computational neuroscience |
| Review Process |
Blind peer review |
Journal info.
pages |
|
| Licences |
CC BY |
| Copyrights |
Yes |
| DOAJ Coverage |
Added on Date : 2007-09-03T15:21:47Z |
| Subject(s) |
Medicine: Medicine (General): Computer applications to medicine. Medical informatics | Medicine: Internal medicine: Neurosciences. Biological psychiatry. Neuropsychiatry |
Active
Inactive
Country
ENGLAND
Aime & Scopes
Computational Intelligence and Neuroscience is a forum for the interdisciplinary field of neural computing, neural engineering and artificial intelligence, where neuroscientists, cognitive scientists, engineers, psychologists, physicists, computer scientists, and artificial intelligence investigators among others can publish their work in one periodical that bridges the gap between neuroscience, artificial intelligence and engineering.
The journal provides research and review papers at an interdisciplinary level, with the field of intelligent systems for computational neuroscience as its focus. This field includes areas like artificial intelligence, models and computational theories of human cognition, perception and motivation; brain models, artificial neural nets and neural computing. All items relevant to building theoretical and practical systems are within its scope, including contributions in the area of applicable neural networks theory, supervised and unsupervised learning methods, algorithms, architectures, performance measures, applied statistics, software simulations, hardware implementations, benchmarks, system engineering and integration and innovative applications.
The journal spans the disciplines of computer science, mathematics, physics, psychology, cognitive science, medicine and neurobiology amongst others. Work on computational intelligence and neuroscience refers to work on theoretical and computational aspects of the development and functioning of the nervous system, which can be at the level of networks of neurons or at the cellular or the sub-cellular level.
Topics of the journal include but are not limited to computational, theoretical, experimental, clinical and applied aspects of the following:
/// Neural modeling and neural-computation
/// Neural signal processing
/// Brain-computer interfacing
/// Neuron-electronics
/// Neurofeedback, neural rehabilitation
/// Neuroinformatics
/// Brain waves, neuroimaging (fMRI, EEG, MEG, PET, NIR)
/// Neural circuits: artificial and biological
/// Neural control and neural system analysis
/// Learning theory (supervised/unsupervised/reinforcement learning)
/// Knowledge based neural networks, probabilistic, spatial, and temporal knowledge representation and reasoning
/// Learning Classifiers
/// Fusion of neural network- fuzzy systems- evolutionary algorithms
/// Biologically inspired Intelligent agents (architectures, environments, adaptation/ learning and knowledge management)
/// Bayesian networks and probabilistic reasoning
/// Swarm intelligence, Ant colony optimization, Multi-agent systems
/// Computational aspects of perceptual systems; Perception of different (visual, auditory and tactile) modalities; Perception and selective attention
/// Long-term, Short-term, and Working memory
/// Multi-level (neural, psychological, computational) analysis of cognitive phenomena
/// Integrated theories of natural and artificial cognitive systems
/// Information-theoretic, control-theoretic, and decision-theoretic approaches to neuroscience
/// Multi-disciplinary computational approaches to the study of creativity, learning, knowledge and inference, emotion and motivation, awareness and consciousness, perception and action, decision making and action, etc.
/// Cognitive systems from artificial life, dynamical systems, complex systems perspectives
/// Neurobiologically inspired evolutionary systems
