中文簡(jiǎn)介

計(jì)算智能和神經(jīng)科學(xué)是一個(gè)跨學(xué)科領(lǐng)域的論壇神經(jīng)計(jì)算、神經(jīng)工程與人工智能、神經(jīng)學(xué)家,認(rèn)知科學(xué)家、工程師、心理學(xué)家、物理學(xué)家、計(jì)算機(jī)科學(xué)家,和人工智能研究人員等可以發(fā)布他們的工作在一個(gè)神經(jīng)科學(xué)期刊,橋梁之間的差距,人工智能和工程。該雜志以計(jì)算神經(jīng)科學(xué)的智能系統(tǒng)為重點(diǎn)，提供跨學(xué)科水平的研究和評(píng)論論文。該領(lǐng)域包括人工智能、人類認(rèn)知、感知和動(dòng)機(jī)的模型和計(jì)算理論等領(lǐng)域；腦模型，人工神經(jīng)網(wǎng)絡(luò)和神經(jīng)計(jì)算。所有與構(gòu)建理論和實(shí)際系統(tǒng)相關(guān)的項(xiàng)目都在其范圍內(nèi)，包括在適用的神經(jīng)網(wǎng)絡(luò)理論、監(jiān)督和非監(jiān)督學(xué)習(xí)方法、算法、體系結(jié)構(gòu)、性能度量、應(yīng)用統(tǒng)計(jì)學(xué)、軟件仿真、硬件實(shí)現(xiàn)、基準(zhǔn)測(cè)試、系統(tǒng)工程以及集成和創(chuàng)新應(yīng)用領(lǐng)域的貢獻(xiàn)。該雜志涵蓋了計(jì)算機(jī)科學(xué)、數(shù)學(xué)、物理、心理學(xué)、認(rèn)知科學(xué)、醫(yī)學(xué)和神經(jīng)生物學(xué)等學(xué)科。計(jì)算智能和神經(jīng)科學(xué)方面的工作是指神經(jīng)系統(tǒng)發(fā)展和功能的理論和計(jì)算方面的工作，可以是神經(jīng)元網(wǎng)絡(luò)層面的工作，也可以是細(xì)胞或亞細(xì)胞層面的工作。該雜志的主題包括但不限于計(jì)算，理論，實(shí)驗(yàn)，臨床和應(yīng)用方面的以下方面：神經(jīng)建模和神經(jīng)計(jì)算神經(jīng)信號(hào)處理腦-機(jī)接口Neuron-electronicsNeuroneedback、神經(jīng)康復(fù)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(xué)習(xí)理論(監(jiān)督/非監(jiān)督/強(qiáng)化學(xué)習(xí))基于知識(shí)的神經(jīng)網(wǎng)絡(luò)，概率，空間和時(shí)間的知識(shí)表示和推理學(xué)習(xí)分類器神經(jīng)網(wǎng)絡(luò)融合。模糊系統(tǒng)。進(jìn)化算法受生物啟發(fā)的智能體(架構(gòu)、環(huán)境、適應(yīng)/學(xué)習(xí)和知識(shí)管理)貝葉斯網(wǎng)絡(luò)和概率推理群體智能，蟻群優(yōu)化，多智能體系統(tǒng)知覺(jué)系統(tǒng)的計(jì)算方面;感知不同的(視覺(jué)、聽(tīng)覺(jué)和觸覺(jué))模式;知覺(jué)和選擇性注意長(zhǎng)期記憶、短期記憶和工作記憶認(rèn)知現(xiàn)象的多層次(神經(jīng)、心理、計(jì)算)分析自然和人工認(rèn)知系統(tǒng)的綜合理論神經(jīng)科學(xué)的信息理論、控制理論和決策理論方法研究創(chuàng)造力、學(xué)習(xí)、知識(shí)和推理、情感和動(dòng)機(jī)、意識(shí)和意識(shí)、感知和行動(dòng)、決策和行動(dòng)等的多學(xué)科計(jì)算方法。認(rèn)知系統(tǒng)從人工生命，動(dòng)力系統(tǒng)，復(fù)雜系統(tǒng)的角度神經(jīng)生物學(xué)啟發(fā)的進(jìn)化系統(tǒng)專題文章將納入原創(chuàng)研究論文或評(píng)論文章。文章被期望是高質(zhì)量的貢獻(xiàn)，代表新的和重要的研究，發(fā)展或應(yīng)用的實(shí)際用途和價(jià)值。決定將基于文章的原創(chuàng)性、技術(shù)可靠性、清晰的闡述、科學(xué)貢獻(xiàn)和多學(xué)科影響。

　　英文簡(jiǎn)介

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.

　　近年期刊自引率趨勢(shì)圖

　　JCR分區(qū)

JCR分區(qū)等級(jí)	JCR所屬學(xué)科	分區(qū)	影響因子
Q2	MATHEMATICAL & COMPUTATIONAL BIOLOGY	Q2	3.12
	NEUROSCIENCES	Q3

　　近年期刊影響因子趨勢(shì)圖

　　CiteScore數(shù)值

CiteScore	SJR	SNIP	學(xué)科類別	分區(qū)	排名	百分位
3.90	0.863	1.559	大類：Mathematics 小類：General Mathematics	Q1	33 / 391	91%
			大類：Mathematics 小類：General Computer Science	Q2	63 / 231	72%
			大類：Mathematics 小類：General Neuroscience	Q3	66 / 112	41%

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