2011 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB)最新文献

Assessing retino-geniculo-cortical connectivities in Alzheimer's Disease with a neural mass model 用神经团块模型评估阿尔茨海默病的视网膜-膝小丘-皮质连通性

2011 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB) Pub Date : 2011-04-11 DOI: 10.1109/CCMB.2011.5952125

B. Bhattacharya, D. Coyle, L. Maguire

引用次数: 6

The application of a real-time rapid-prototyping environment for the behavioral rehabilitation of a lost brain function in rats 实时快速原型环境在大鼠失脑功能行为康复中的应用

2011 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB) Pub Date : 2011-04-11 DOI: 10.1109/CCMB.2011.5952121

R. Prueckl, Engelbert Grünbacher, R. Ortner, A. Taub, R. Hogri, A. Magal, Eyal Segalis, M. Zreik, N. Nossenson, Ivan Herreros-Alonso, Andrea Giovannucci, R. O. Almog, S. Bamford, Mira Marcus-Kalish, Y. Shacham, P. Verschure, H. Messer, M. Mintz, J. Scharinger, A. Silmon, C. Guger

{"title":"The application of a real-time rapid-prototyping environment for the behavioral rehabilitation of a lost brain function in rats","authors":"R. Prueckl, Engelbert Grünbacher, R. Ortner, A. Taub, R. Hogri, A. Magal, Eyal Segalis, M. Zreik, N. Nossenson, Ivan Herreros-Alonso, Andrea Giovannucci, R. O. Almog, S. Bamford, Mira Marcus-Kalish, Y. Shacham, P. Verschure, H. Messer, M. Mintz, J. Scharinger, A. Silmon, C. Guger","doi":"10.1109/CCMB.2011.5952121","DOIUrl":"https://doi.org/10.1109/CCMB.2011.5952121","url":null,"abstract":"In this paper we propose a Rapid Prototyping Environment (RPE) for real-time biosignal analysis including ECG, EEG, ECoG and EMG of humans and animals requiring a very precise time resolution. Based on the previous RPE which was mainly designed for developing Brain Computer Interfaces (BCI), the present solution offers tools for data preprocessing, analysis and visualization even in the case of high sampling rates and furthermore tools for precise cognitive stimulation. One application of the system, the analysis of multi-unit activity measured from the brain of a rat is presented to prove the efficiency of the proposed environment. The experimental setup was used to design and implement a biomimetic, biohybrid model for demonstrating the recovery of a learning function lost with age. Throughout the paper we discuss the components of the setup, the software structure and the online visualization. At the end we present results of a real-time experiment in which the model of the brain learned to react to the acquired signals.","PeriodicalId":315883,"journal":{"name":"2011 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114516783","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

Confabulation based sentence completion for machine reading 基于虚构的机器阅读句子补全

2011 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB) Pub Date : 2011-04-11 DOI: 10.1109/CCMB.2011.5952109

Qinru Qiu, Qing Wu, Daniel J. Burns, Michael J. Moore, R. Pino, Morgan Bishop, R. Linderman

{"title":"Confabulation based sentence completion for machine reading","authors":"Qinru Qiu, Qing Wu, Daniel J. Burns, Michael J. Moore, R. Pino, Morgan Bishop, R. Linderman","doi":"10.1109/CCMB.2011.5952109","DOIUrl":"https://doi.org/10.1109/CCMB.2011.5952109","url":null,"abstract":"Sentence completion and prediction refers to the capability of filling missing words in any incomplete sentences. It is one of the keys to reading comprehension, thus making sentence completion an indispensible component of machine reading. Cogent confabulation is a bio-inspired computational model that mimics the human information processing. The building of confabulation knowledge base uses an unsupervised machine learning algorithm that extracts the relations between objects at the symbolic level. In this work, we propose performance improved training and recall algorithms that apply the cogent confabulation model to solve the sentence completion problem. Our training algorithm adopts a two-level hash table, which significantly improves the training speed, so that a large knowledge base can be built at relatively low computation cost. The proposed recall function fills missing words based on the sentence context. Experimental results show that our software can complete trained sentences with 100% accuracy. It also gives semantically correct answers to more than two thirds of the testing sentences that have not been trained before.","PeriodicalId":315883,"journal":{"name":"2011 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124689834","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: 18

Performance analysis of left/right hand movement classification from EEG signal by intelligent algorithms 基于智能算法的脑电信号左/右手运动分类性能分析

2011 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB) Pub Date : 2011-04-11 DOI: 10.1109/CCMB.2011.5952111

S. Bhattacharyya, A. Khasnobish, A. Konar, D. Tibarewala, A. Nagar

{"title":"Performance analysis of left/right hand movement classification from EEG signal by intelligent algorithms","authors":"S. Bhattacharyya, A. Khasnobish, A. Konar, D. Tibarewala, A. Nagar","doi":"10.1109/CCMB.2011.5952111","DOIUrl":"https://doi.org/10.1109/CCMB.2011.5952111","url":null,"abstract":"Brain Computer interfaces (BCI) has immense potentials to improve human lifestyle including that of the disabled. BCI has possible applications in the next generation human-computer, human-robot and prosthetic/assistive devices for rehabilitation. The dataset used for this study has been obtained from the BCI competition-II 2003 databank provided by the University of Technology, Graz. After pre-processing of the signals from their electrodes (C3 & C4), the wavelet coefficients, Power Spectral Density of the alpha and the central beta band and the average power of the respective bands have been employed as features for classification. This paper presents a comparative study of different classification methods including linear discriminant analysis (LDA), Quadratic discriminant analysis (QDA), k-nearest neighbor (KNN) algorithm, linear support vector machine (SVM), radial basis function (RBF) SVM and naive Bayesian classifiers algorithms in differentiating the raw EEG data obtained, into their associative left/right hand movements. Performance of left/right hand classification is studied using both original features and reduced features. The feature reduction here has been performed using Principal component Analysis (PCA). It is as observed that RBF kernelised SVM classifier indicates the highest performance accuracy of 82.14% with both original and reduced feature set. However, experimental results further envisage that all the other classification techniques provide better classification accuracy for reduced data set in comparison to the original data. It is also noted that the KNN classifier improves the classification accuracy by 5% when reduced features are used instead of the original.","PeriodicalId":315883,"journal":{"name":"2011 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB)","volume":"47 27","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131722314","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: 70

Mirror neurons, language, and embodied cognition 镜像神经元、语言和具身认知

2011 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB) Pub Date : 2011-04-11 DOI: 10.1109/CCMB.2011.5952129

L. Perlovsky

引用次数: 21

2011 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB) Pub Date : 2011-04-11 DOI: 10.1109/CCMB.2011.5952112

B. Nasseroleslami, H. Lakany, B. Conway

{"title":"Event-related (de-)synchronisation in arm isometric exertions: A wavelet analysis","authors":"B. Nasseroleslami, H. Lakany, B. Conway","doi":"10.1109/CCMB.2011.5952112","DOIUrl":"https://doi.org/10.1109/CCMB.2011.5952112","url":null,"abstract":"Neural activity associated with human voluntary motor control has been investigated using various large scale recording and imaging techniques such as Magnetoencephalog-raphy (MEG), electroencephalographic (EEG), and Electrocor-ticography (ECoG). While the EEG activity patterns associated with movement and especially movement execution are relatively known, there are only few studies that address the characteristics of motor rhythms in isometric exertions, and especially in the planning stage. In this paper we report on the results of an experiment where we have recorded EEG from 8 subjects during preparation, planning, and execution of directional arm isometric exertions in horizontal plane, according to instruction-delay visual cues. Continuous Morlet Wavelet Scalograms of the EEG signals in Cz C3 C4 electrodes associated with the task, show (de-)synchronisation patterns in planning and execution of the exertions. Phasic synchronisation in 2–7 Hz frequency band and both phasic and tonic desynchronisation in α (μ), β, and γ frequency bands are observed. Minor differences between contralateral, central and ipsilateral rhythmic motor activities during force generation are indicated and discussed. The results can be used to study the involvement of different brain regions during voluntary isometric tasks. The results pave the way for further clinical studies and also for Brain-Computer Interfacing (BCI) and BCI-rehabilitation research.","PeriodicalId":315883,"journal":{"name":"2011 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB)","volume":"57 73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2011-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117109195","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

Modeling decisions by brains that think, feel, and vegetate 通过思考、感觉和生长的大脑来建模决策

2011 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB) Pub Date : 2011-04-11 DOI: 10.1109/CCMB.2011.5952118

D. Levine

引用次数: 0

Implementing a cognition cycle with words computation 用单词计算实现一个认知循环

2011 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB) Pub Date : 2011-04-11 DOI: 10.1109/CCMB.2011.5952124

Koosha Sadeghi Oskooyee, Mohammad Mansour Riahi Kashani, A. Harounabadi

引用次数: 5

Comparative study of band-power extraction techniques for Motor Imagery classification 运动意象分类中频带功率提取技术的比较研究

2011 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB) Pub Date : 2011-04-11 DOI: 10.1109/CCMB.2011.5952105

N. Brodu, F. Lotte, A. Lécuyer

引用次数: 95

Deciding in uncertainy: The creativity effects 不确定决策:创造力效应

2011 IEEE Symposium on Computational Intelligence, Cognitive Algorithms, Mind, and Brain (CCMB) Pub Date : 2011-04-11 DOI: 10.1109/CCMB.2011.5952117

John G. Taylor

引用次数: 0