Cognitive and Computational Neuroscience - Principles, Algorithms and Applications最新文献

Introductory Chapter: Cognitive and Computational Neuroscience - Principles, Algorithms, and Applications 导论章:认知和计算神经科学-原理，算法和应用

Cognitive and Computational Neuroscience - Principles, Algorithms and Applications Pub Date : 2018-05-30 DOI: 10.5772/INTECHOPEN.72824

S. A. Hosseini

引用次数: 0

Spiking Central Pattern Generators through Reverse Engineering of Locomotion Patterns 通过运动模式逆向工程的峰值中心模式发生器

Cognitive and Computational Neuroscience - Principles, Algorithms and Applications Pub Date : 2018-05-30 DOI: 10.5772/INTECHOPEN.72348

Andrés Espinal, M. Sotelo-Figueroa, H. J. Estrada-García, M. Ornelas-Rodríguez, H. Rostro-González

引用次数: 1

Convergence of Action, Reaction, and Perception via Neural Oscillations in Dynamic Interaction with External Surroundings 在与外界环境的动态互动中，通过神经振荡的行动、反应和知觉的收敛

Cognitive and Computational Neuroscience - Principles, Algorithms and Applications Pub Date : 2018-05-30 DOI: 10.5772/INTECHOPEN.76397

D. Gupta, S. Teixeira

引用次数: 2

Computational Models of Consciousness-Emotion Interactions in Social Robotics: Conceptual Framework 社交机器人中意识-情感互动的计算模型:概念框架

Cognitive and Computational Neuroscience - Principles, Algorithms and Applications Pub Date : 2017-12-21 DOI: 10.5772/INTECHOPEN.72369

R. Szczepanowski, Małgorzata Gakis, K. Arent, Janusz Sobecki

{"title":"Computational Models of Consciousness-Emotion Interactions in Social Robotics: Conceptual Framework","authors":"R. Szczepanowski, Małgorzata Gakis, K. Arent, Janusz Sobecki","doi":"10.5772/INTECHOPEN.72369","DOIUrl":"https://doi.org/10.5772/INTECHOPEN.72369","url":null,"abstract":"There is a little information on how to design a social robot that effectively executes consciousness-emotion (C-E) interaction in a socially acceptable manner. In fact, development of such socially sophisticated interactions depends on models of human high- level cognition implemented in the robot’s design. Therefore, a fundamental research problem of social robotics in terms of effective C-E interaction processing is to define a computational architecture of the robotic system in which the cognitive-emotional inte-gration occurs and determine cognitive mechanisms underlying consciousness along with its subjective aspect in detecting emotions. Our conceptual framework rests upon assumptions of a computational approach to consciousness, which points out that con- sciousness and its subjective aspect are specific functions of the human brain that can be implemented into an artificial social robot’s construction. Such research framework of developing C-E addresses a field of machine consciousness that indicates important computational correlates of consciousness in such an artificial system and the possibility to objectively describe such mechanisms with quantitative parameters based on signal-detection and threshold theories.","PeriodicalId":333803,"journal":{"name":"Cognitive and Computational Neuroscience - Principles, Algorithms and Applications","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116094637","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Characterizing Motor System to Improve Training Protocols Used in Brain-Machine Interfaces Based on Motor Imagery 表征运动系统以改进基于运动图像的脑机接口训练协议

Cognitive and Computational Neuroscience - Principles, Algorithms and Applications Pub Date : 2017-12-20 DOI: 10.5772/INTECHOPEN.72667

L. Alonso-Valerdi, A. González-Garrido

{"title":"Characterizing Motor System to Improve Training Protocols Used in Brain-Machine Interfaces Based on Motor Imagery","authors":"L. Alonso-Valerdi, A. González-Garrido","doi":"10.5772/INTECHOPEN.72667","DOIUrl":"https://doi.org/10.5772/INTECHOPEN.72667","url":null,"abstract":"Motor imagery (MI)-based brain-machine interface (BMI) is a technology under devel- opment that actively modifies users’ perception and cognition through mental tasks, so as to decode their intentions from their neural oscillations, and thereby bringing some kind of activation. So far, MI as control task in BMIs has been seen as a skill that must be acquired, but neither user conditions nor controlled learning conditions have been taken into account. As motor system is a complex mechanism trained along lifetime, and MI-based BMI attempts to decode motor intentions from neural oscil - lations in order to put a device into action, motor mechanisms should be considered when prototyping BMI systems. It is hypothesized that the best way to acquire MI skills is following the same rules humans obey to move around the world. On this basis, new training paradigms consisting of ecological environments, identification of control tasks according to the ecological environment, transparent mapping, and multisensory feedback are proposed in this chapter. These new MI training paradigms take advantages of previous knowledge of users and facilitate the generation of mental image due to the automatic development of sensory predictions and motor behav- ior patterns in the brain. Furthermore, the effectuation of MI as an actual movement would make users feel that their mental images are being executed, and the resulting sensory feedback may allow forward model readjusting the imaginary movement in course.","PeriodicalId":333803,"journal":{"name":"Cognitive and Computational Neuroscience - Principles, Algorithms and Applications","volume":"134 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122414652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2