2015 International Workshop on Pattern Recognition in NeuroImaging最新文献

筛选
英文 中文
Fusing Simultaneous EEG and fMRI Using Functional and Anatomical Information 利用功能和解剖信息融合EEG和fMRI
2015 International Workshop on Pattern Recognition in NeuroImaging Pub Date : 2015-06-10 DOI: 10.1109/PRNI.2015.22
Sofie Therese Hansen, I. Winkler, L. K. Hansen, K. Müller, Sven Dähne
{"title":"Fusing Simultaneous EEG and fMRI Using Functional and Anatomical Information","authors":"Sofie Therese Hansen, I. Winkler, L. K. Hansen, K. Müller, Sven Dähne","doi":"10.1109/PRNI.2015.22","DOIUrl":"https://doi.org/10.1109/PRNI.2015.22","url":null,"abstract":"Simultaneously measuring electro physical and hemodynamic signals has become more accessible in the last years and the need for modeling techniques that can fuse the modalities is growing. In this work we augment a specific fusion method, the multimodal Source Power Co-modulation (mSPoC), to not only use functional but also anatomical information. The goal is to extract correlated source components from electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). Anatomical information enters our proposed extension to mSPoC via the forward model, which relates the activity on cortex level to the EEG sensors. The augmented mSPoC is shown to outperform the original version in realistic simulations where the signal to noise ratio is low or where training epochs are scarce.","PeriodicalId":380902,"journal":{"name":"2015 International Workshop on Pattern Recognition in NeuroImaging","volume":"683 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133322707","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
Population Inference for Node Level Differences in Multi-subject Functional Connectivity 多主体功能连接中节点水平差异的人口推断
2015 International Workshop on Pattern Recognition in NeuroImaging Pub Date : 2015-06-10 DOI: 10.1109/PRNI.2015.34
Manjari Narayan, Genevera I. Allen
{"title":"Population Inference for Node Level Differences in Multi-subject Functional Connectivity","authors":"Manjari Narayan, Genevera I. Allen","doi":"10.1109/PRNI.2015.34","DOIUrl":"https://doi.org/10.1109/PRNI.2015.34","url":null,"abstract":"Using Gaussian graphical models as the basis for functional connectivity, we propose new models and test statistics to detect whether subject covariates predict differences in network metrics in a population of subjects. Our approach emphasizes the need to account for errors in estimating subject level networks when conducting inference at the population level. Using simulations, we show that failure to do so reduces statistical power in detecting covariate effects for realistic graph structures. We illustrate the benefits of our procedure for clinical neuroimaging using a resting-state fMRI study of neurofibromatosis-I.","PeriodicalId":380902,"journal":{"name":"2015 International Workshop on Pattern Recognition in NeuroImaging","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116455180","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
Kernel Convolution Model for Decoding Sounds from Time-Varying Neural Responses 基于时变神经响应的声音解码核卷积模型
2015 International Workshop on Pattern Recognition in NeuroImaging Pub Date : 2015-06-10 DOI: 10.1109/PRNI.2015.10
A. Faisal, Anni Nora, J. Seol, H. Renvall, R. Salmelin
{"title":"Kernel Convolution Model for Decoding Sounds from Time-Varying Neural Responses","authors":"A. Faisal, Anni Nora, J. Seol, H. Renvall, R. Salmelin","doi":"10.1109/PRNI.2015.10","DOIUrl":"https://doi.org/10.1109/PRNI.2015.10","url":null,"abstract":"In this study we present a kernel based convolution model to characterize neural responses to natural sounds by decoding their time-varying acoustic features. The model allows to decode natural sounds from high-dimensional neural recordings, such as magneto encephalography (MEG), that track timing and location of human cortical signalling no invasively across multiple channels. We used the MEG responses recorded from subjects listening to acoustically different environmental sounds. By decoding the stimulus frequencies from the responses, our model was able to accurately distinguish between two different sounds that it had never encountered before with 70% accuracy. Convolution models typically decode frequencies that appear at a certain time point in the sound signal by using neural responses from that time point until a certain fixed duration of the response. Using our model, we evaluated several fixed durations (time-lags) of the neural responses and observed auditory MEG responses to be most sensitive to spectral content of the sounds at time-lags of 250 ms to 500 ms. The proposed model should be useful for determining what aspects of natural sounds are represented by high-dimensional neural responses and may reveal novel properties of neural signals.","PeriodicalId":380902,"journal":{"name":"2015 International Workshop on Pattern Recognition in NeuroImaging","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129609583","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
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信