2013 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB)最新文献_第2页

A cognitive robotic model of mental rotation 心智旋转的认知机器人模型

2013 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB) Pub Date : 2013-04-16 DOI: 10.1109/CCMB.2013.6609163

Kristsana Seepanomwan, Daniele Caligiore, G. Baldassarre, A. Cangelosi

引用次数: 2

Why “dark thoughts” aren't really dark: A novel algorithm for metaphor identification 为什么“黑暗的想法”并不真的黑暗:一种新的隐喻识别算法

2013 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB) Pub Date : 2013-04-16 DOI: 10.1109/CCMB.2013.6609166

Dany H. Assaf, Yair Neuman, Yohai Cohen, S. Argamon, N. Howard, Mark Last, O. Frieder, Moshe Koppel

引用次数: 28

A model of stimulus induced epileptic spike-wave discharges 刺激诱发的癫痫尖波放电模型

2013 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB) Pub Date : 2013-04-16 DOI: 10.1109/CCMB.2013.6609165

P. Taylor, G. Baier, S. Cash, J. Dauwels, J. Slotine, Yujiang Wang

{"title":"A model of stimulus induced epileptic spike-wave discharges","authors":"P. Taylor, G. Baier, S. Cash, J. Dauwels, J. Slotine, Yujiang Wang","doi":"10.1109/CCMB.2013.6609165","DOIUrl":"https://doi.org/10.1109/CCMB.2013.6609165","url":null,"abstract":"Recent clinical and experimental evidence suggests that the spike-wave discharges (SWD) of absence seizures result from local activity within a hyperexcitable cortical region with rapid generalization through thalamocortical networks. The cortical focus is said to react more strongly to stimulation than other areas. We seek to develop a model which is in agreement with these recent experimental findings and suggest a possible explanation. In this study we extend an existing neural field model of thalamocortical interaction to account for multiple cortical regions which are connected according connectivity inferred from a clinically diagnosed epileptic patient. We stimulate at different model electrodes and investigate the resulting seizure duration. We observe that stimulation of only a small subset (11%) of model electrodes can lead to the rapid generalisation of SWD via both corticocortical and thalamocortical pathways. We find that the resulting model dynamics (seizure duration) varies significantly dependent upon the nodes stimulated and the amplitude of the stimulus. Our model indicates that heterogeneities in corticocortical connectivity could serve as a possible reason for the cortical focus and provides a platform for in silico hypothesis generation in complement to in vivo hypothesis validation.","PeriodicalId":395025,"journal":{"name":"2013 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB)","volume":"515 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116214282","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: 30

A hierarchical classification system for sleep stage scoring via forehead EEG signals 基于脑电图信号的睡眠阶段分级评分系统

2013 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB) Pub Date : 2013-04-16 DOI: 10.1109/CCMB.2013.6609157

Chih-Sheng Huang, Chun-Ling Lin, L. Ko, Shen-Yi Liu, Tung-Ping Su, Chin-Teng Lin

引用次数: 40

Connectivity pattern modeling of motor imagery EEG 运动意象脑电连接模式建模

2013 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB) Pub Date : 2013-04-16 DOI: 10.1109/CCMB.2013.6609171

Xinyang Li, S. Ong, Yaozhang Pan, K. Ang

引用次数: 7

Model-based reinforcement learning for humanoids: A study on forming rewards with the iCub platform 基于模型的类人强化学习:基于iCub平台的奖励形成研究

2013 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB) Pub Date : 2013-04-16 DOI: 10.1109/CCMB.2013.6609170

A. Fachantidis, A. D. Nuovo, A. Cangelosi, I. Vlahavas

{"title":"Model-based reinforcement learning for humanoids: A study on forming rewards with the iCub platform","authors":"A. Fachantidis, A. D. Nuovo, A. Cangelosi, I. Vlahavas","doi":"10.1109/CCMB.2013.6609170","DOIUrl":"https://doi.org/10.1109/CCMB.2013.6609170","url":null,"abstract":"Technological advancements in robotics and cognitive science are contributing to the development of the field of cognitive robotics. Modern robotic platforms are able to exhibit the ability to learn and reason about complex tasks and to follow behavioural goals in complex environments. Nevertheless, many challenges still exist. One of these great challenges is to equip these robots with cognitive systems that allow them to deal with less constrained situations, beyond constrained scenarios as in industrial robotics. In this work we explore the application of the Reinforcement Learning (RL) paradigm to study the autonomous development of robot controllers without a priori supervised learning. Such a model-based RL architecture is discussed for the cognitive implications of applying RL in humanoid robots. To this end we show a developmental framework for RL in robotics and its implementation and testing for the iCub robotic platform in two novel experimental scenarios. In particular we focus on iCub simulation experiments with comparisons between internal perception-based reward signals and external ones, in order to compare learning performance of the robot guided by its own perception of action's outcomes with the one when the robot has its actions externally evaluated.","PeriodicalId":395025,"journal":{"name":"2013 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117150701","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: 7

An energy efficient real-time seizure detection method in rats with spontaneous temporal lobe epilepsy 自发性颞叶癫痫大鼠能量高效实时检测方法

2013 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB) Pub Date : 2013-04-16 DOI: 10.1109/CCMB.2013.6609162

Yu-Lin Wang, Sheng-Fu Liang, Fu-Zen Shaw, Y. Huang, Yin-Lin Chen

{"title":"An energy efficient real-time seizure detection method in rats with spontaneous temporal lobe epilepsy","authors":"Yu-Lin Wang, Sheng-Fu Liang, Fu-Zen Shaw, Y. Huang, Yin-Lin Chen","doi":"10.1109/CCMB.2013.6609162","DOIUrl":"https://doi.org/10.1109/CCMB.2013.6609162","url":null,"abstract":"The presence of an on-line seizure detection system could drive an antiepileptic stimulator in real time to suppress seizure generation and to enhance the patients' safety and quality of life. In this paper, the continuous long-term EEGs of three Wistar rats with spontaneous temporal lobe seizure were analyzed. We proposed the development of an energy efficient real-time seizure detection method that employs a hierarchical architecture. The first stage was used to fast detect the seizure-like EEG segment, and a classifier was utilized in the second stage for final confirmation. Only when a suspected seizure segment is found, the second stage is activated. With 2-staged architecture, it saved about 99.4% computation energy in the experiment. Therefore, it is useful to improve the longevity of the closed-loop seizure control system. Three classifiers, linear discriminant analysis (LDA), quadratic discriminant analysis (QDA) and support vector machine (SVM), were applied for comparison. From the experimental results, three classifiers yielded the comparable performances. However, considering of the trade-off between detection performances and power consumption, LDA which yielded the 100% detection rate, 0.22 FP/hr, and 1.69 s detection latency is suggested for a portable closed-loop seizure controller.","PeriodicalId":395025,"journal":{"name":"2013 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128811246","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: 3

A quantitative comparison of the most sophisticated EOG-based eye movement recognition techniques 最复杂的基于眼电信号的眼动识别技术的定量比较

2013 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB) Pub Date : 2013-04-16 DOI: 10.1109/CCMB.2013.6609164

M. Duvinage, J. Cubeta, T. Castermans, M. Petieau, T. Hoellinger, G. Cheron, T. Dutoit

{"title":"A quantitative comparison of the most sophisticated EOG-based eye movement recognition techniques","authors":"M. Duvinage, J. Cubeta, T. Castermans, M. Petieau, T. Hoellinger, G. Cheron, T. Dutoit","doi":"10.1109/CCMB.2013.6609164","DOIUrl":"https://doi.org/10.1109/CCMB.2013.6609164","url":null,"abstract":"Although ElectroOculoGraphic (EOG) signals have been intensively used for human-machine interfaces, none of the available eye movement recognition techniques have been objectively compared to each other. In this paper, we propose to compare two widely known techniques (the standard R. Barea (RB) and A. Bulling (AB)'s works) and a Spiking Neural Network based approach. We also suggest several potential improvements that were all assessed according to the Fl-score. Additionally, we investigate 3 different target configurations on the screen: 3×3, 3×5 and 5×5. This aims at detecting which configuration can reach the best bitrate. Finally, double blink and wink detectors are Fl-score evaluated to estimate their relevancy as a mouse click. In this 6-healthy-subject experiment, we observed that both RB and AB methods provide fairly similar results. According to the bitrate analysis while considering complexity, the 3×3 is the most suitable interface. Among the different potential enhancements, the clustering approach instead of a fixed grid leads to a much quicker learning procedure. Regarding the eye mouse click detectors, their performance should be high enough to be used in a reliable interface.","PeriodicalId":395025,"journal":{"name":"2013 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114364766","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: 5

Spiking-timing based pattern recognition with real-world visual stimuli 基于脉冲时序的模式识别与真实世界的视觉刺激

2013 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB) Pub Date : 2013-04-16 DOI: 10.1109/CCMB.2013.6609161

Jun Hu, Huajin Tang, K. Tan

引用次数: 2

EEG-based motion sickness classification system with genetic feature selection 基于脑电图的运动病遗传特征选择分类系统

2013 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB) Pub Date : 2013-04-16 DOI: 10.1109/CCMB.2013.6609180

L. Ko, Hua-Chin Lee, Shu-Fang Tsai, Tsung-Chin Shih, Ya-Ting Chuang, Hui-Ling Huang, Shinn-Ying Ho, Chin-Teng Lin

引用次数: 14