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.

計算智能和神經(jīng)科學是一個跨學科領域的論壇神經(jīng)計算、神經(jīng)工程與人工智能、神經(jīng)學家,認知科學家、工程師、心理學家、物理學家、計算機科學家,和人工智能研究人員等可以發(fā)布他們的工作在一個神經(jīng)科學期刊,橋梁之間的差距,人工智能和工程。該雜志以計算神經(jīng)科學的智能系統(tǒng)為重點，提供跨學科水平的研究和評論論文。該領域包括人工智能、人類認知、感知和動機的模型和計算理論等領域；腦模型，人工神經(jīng)網(wǎng)絡和神經(jīng)計算。所有與構建理論和實際系統(tǒng)相關的項目都在其范圍內(nèi)，包括在適用的神經(jīng)網(wǎng)絡理論、監(jiān)督和非監(jiān)督學習方法、算法、體系結構、性能度量、應用統(tǒng)計學、軟件仿真、硬件實現(xiàn)、基準測試、系統(tǒng)工程以及集成和創(chuàng)新應用領域的貢獻。該雜志涵蓋了計算機科學、數(shù)學、物理、心理學、認知科學、醫(yī)學和神經(jīng)生物學等學科。計算智能和神經(jīng)科學方面的工作是指神經(jīng)系統(tǒng)發(fā)展和功能的理論和計算方面的工作，可以是神經(jīng)元網(wǎng)絡層面的工作，也可以是細胞或亞細胞層面的工作。該雜志的主題包括但不限于計算，理論，實驗，臨床和應用方面的以下方面：神經(jīng)建模和神經(jīng)計算神經(jīng)信號處理腦-機接口Neuron-electronicsNeuroneedback、神經(jīng)康復Neuroinformatics腦電波，神經(jīng)成像(fMRI, EEG, MEG, PET, NIR)神經(jīng)回路：人工神經(jīng)回路和生物神經(jīng)回路神經(jīng)控制與神經(jīng)系統(tǒng)分析學習理論(監(jiān)督/非監(jiān)督/強化學習)基于知識的神經(jīng)網(wǎng)絡，概率，空間和時間的知識表示和推理學習分類器神經(jīng)網(wǎng)絡融合。模糊系統(tǒng)。進化算法受生物啟發(fā)的智能體(架構、環(huán)境、適應/學習和知識管理)貝葉斯網(wǎng)絡和概率推理群體智能，蟻群優(yōu)化，多智能體系統(tǒng)知覺系統(tǒng)的計算方面;感知不同的(視覺、聽覺和觸覺)模式;知覺和選擇性注意長期記憶、短期記憶和工作記憶認知現(xiàn)象的多層次(神經(jīng)、心理、計算)分析自然和人工認知系統(tǒng)的綜合理論神經(jīng)科學的信息理論、控制理論和決策理論方法研究創(chuàng)造力、學習、知識和推理、情感和動機、意識和意識、感知和行動、決策和行動等的多學科計算方法。認知系統(tǒng)從人工生命，動力系統(tǒng)，復雜系統(tǒng)的角度神經(jīng)生物學啟發(fā)的進化系統(tǒng)專題文章將納入原創(chuàng)研究論文或評論文章。文章被期望是高質(zhì)量的貢獻，代表新的和重要的研究，發(fā)展或應用的實際用途和價值。決定將基于文章的原創(chuàng)性、技術可靠性、清晰的闡述、科學貢獻和多學科影響。