Computational Intelligence and Neuroscience

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官方网站：http://www.hindawi.com/journals/cin/

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PMC链接：http://www.ncbi.nlm.nih.gov/nlmcatalog?term=1687-5265%5BISSN%5D

计算智能和神经科学是一个跨学科领域的论坛神经计算、神经工程与人工智能、神经学家,认知科学家、工程师、心理学家、物理学家、计算机科学家,和人工智能研究人员等可以发布他们的工作在一个神经科学期刊,桥梁之间的差距,人工智能和工程。该杂志以计算神经科学的智能系统为重点，提供跨学科水平的研究和评论论文。该领域包括人工智能、人类认知、感知和动机的模型和计算理论等领域；脑模型，人工神经网络和神经计算。所有与构建理论和实际系统相关的项目都在其范围内，包括在适用的神经网络理论、监督和非监督学习方法、算法、体系结构、性能度量、应用统计学、软件仿真、硬件实现、基准测试、系统工程以及集成和创新应用领域的贡献。该杂志涵盖了计算机科学、数学、物理、心理学、认知科学、医学和神经生物学等学科。计算智能和神经科学方面的工作是指神经系统发展和功能的理论和计算方面的工作，可以是神经元网络层面的工作，也可以是细胞或亚细胞层面的工作。该杂志的主题包括但不限于计算，理论，实验，临床和应用方面的以下方面：神经建模和神经计算神经信号处理脑-机接口Neuron-electronicsNeuroneedback、神经康复Neuroinformatics脑电波，神经成像(fMRI, EEG, MEG, PET, NIR)神经回路：人工神经回路和生物神经回路神经控制与神经系统分析学习理论(监督/非监督/强化学习)基于知识的神经网络，概率，空间和时间的知识表示和推理学习分类器神经网络融合。模糊系统。进化算法受生物启发的智能体(架构、环境、适应/学习和知识管理)贝叶斯网络和概率推理群体智能，蚁群优化，多智能体系统知觉系统的计算方面;感知不同的(视觉、听觉和触觉)模式;知觉和选择性注意长期记忆、短期记忆和工作记忆认知现象的多层次(神经、心理、计算)分析自然和人工认知系统的综合理论神经科学的信息理论、控制理论和决策理论方法研究创造力、学习、知识和推理、情感和动机、意识和意识、感知和行动、决策和行动等的多学科计算方法。认知系统从人工生命，动力系统，复杂系统的角度神经生物学启发的进化系统专题文章将纳入原创研究论文或评论文章。文章被期望是高质量的贡献，代表新的和重要的研究，发展或应用的实际用途和价值。决定将基于文章的原创性、技术可靠性、清晰的阐述、科学贡献和多学科影响。

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-computationNeural signal processingBrain-computer interfacingNeuron-electronicsNeurofeedback, neural rehabilitationNeuroinformaticsBrain waves, neuroimaging (fMRI, EEG, MEG, PET, NIR)Neural circuits: artificial and biologicalNeural control and neural system analysisLearning theory (supervised/unsupervised/reinforcement learning)Knowledge based neural networks, probabilistic, spatial, and temporal knowledge representation and reasoningLearning ClassifiersFusion of neural network- fuzzy systems- evolutionary algorithmsBiologically inspired Intelligent agents (architectures, environments, adaptation/ learning and knowledge management)Bayesian networks and probabilistic reasoningSwarm intelligence, Ant colony optimization, Multi-agent systemsComputational aspects of perceptual systems; Perception of different (visual, auditory and tactile) modalities; Perception and selective attentionLong-term, Short-term, and Working memoryMulti-level (neural, psychological, computational) analysis of cognitive phenomenaIntegrated theories of natural and artificial cognitive systemsInformation-theoretic, control-theoretic, and decision-theoretic approaches to neuroscienceMulti-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 perspectivesNeurobiologically inspired evolutionary systemsFeatured contributions will fall into original research papers or review articles. Articles are expected to be high quality contributions representing new and significant research, developments or applications of practical use and value. Decisions will be made based on originality, technical soundness, clarity of exposition, scientific contribution and multidisciplinary impact of the article.