西安交通大学生物医学信息工程教育部重点实验室,西安,710049
网络首发:2014-02-10,
纸质出版:2014
移动端阅览
尤二涛, 徐进, 张永兴. 再认记忆的事件相关电位多域特征值研究[J]. 西安交通大学学报, 2014,48(2):137-142.
Multi-Domain Feature of Event-Related Potential in Recognition Memory[J]. 2014, 48(2): 137-142.
尤二涛, 徐进, 张永兴. 再认记忆的事件相关电位多域特征值研究[J]. 西安交通大学学报, 2014,48(2):137-142. DOI: 10.7652/xjtuxb201402023.
Multi-Domain Feature of Event-Related Potential in Recognition Memory[J]. 2014, 48(2): 137-142. DOI: 10.7652/xjtuxb201402023.
为了更好地了解再认记忆状态下的事件相关电位(ERP)在时域、频域和空间域的性质
与传统的ERP信号特征提取方法往往都局限于时域特征不同
该研究采用非负张量分解(NTF)技术
提取再认记忆实验中与“Old”和“New”刺激相关的ERP的多域特征值。多域特征值是从多个导联ERP信号的时频转换中提取的
因此可以同时反映ERP在时域、频域和空间域上的性质。研究结果发现
多域特征值可以明显地反映出不同刺激类型下ERP信号的差异
与额区新旧效应相关的FN400在“New”刺激下的多域特征值显著大于“Old”刺激下的
与顶区新旧效应相关的P600在“Old”刺激下的多域特征值显著大于“New”刺激下的
说明多域特征值能很好地用于区分和识别再认记忆中的新旧刺激
这不仅为再认记忆的研究提供了一个新方法
而且为基于ERP的认知功能研究提供了新的思路和途径。
To explore the properties of event-related potential(ERP)related with recognition memory in the time
frequency and spatial domains
nonnegative tensor factorization(NTF)was applied to extract multi-domain feature from ERP signals related with “New” stimulus and “Old” stimulus respectively during recognition memory task
which is different from the traditional method to extract the feature of time domain
and the multi-domain feature was extracted from time-frequency transformation of multiple channel ERP signals so that it can reflect the properties of ERP in the time
frequency and spatial domains simultaneously. It is discovered that the multi-domain feature is able to discriminate ERP for different stimulus. The multi-domain feature of FN400 related with frontal old/new effect to “New” stimulus gets greater than the feature to “Old” stimulus. The multi-domain feature of P600 associated with parietal old/new effect to “Old” stimulus gets larger than the feature to “New” stimulus. Therefore
the multi-domain feature extracted by NTF reveals properties of ERP in the time
frequency and spatial domains
and provides a novel method to recognition memory research and cognitive function research based on ERP signal.
RICHLER J J, CHEUNG O S, GAUTHIER I. Holistic processing predicts face recognition[J]. Psychological Science, 2011, 22(4): 464-471.
HOLGER W. The role of age and ethnic group in face recognition memory: ERP evidence from a combined own-age and own-race bias study[J]. Biological Psychology, 2012, 89(1): 134-147.
MICHAEL D R, CURRAN T. Event-related potentials and recognition memory[J]. Trends in Cognitive Sciences, 2007, 6(11): 251-256.
HINTZMAN D L, CURRAN T. Retrieval dynamics of recognition and frequency judgments: evidence for separate processes of familiarity and recall[J]. Mem Lang, 1994, 33(1): 1-18.
樊晓燕, 郭春彦. 从认知神经科学的角度看熟悉性和回想[J]. 心理科学进展, 2005, 13(2): 314-319.
FAN Xiaoyan, GUO Chunyan. Cognitive neuroscience research on recollection and familiarity[J]. Advances in Psychological Science, 2005, 13(2): 314-319.
李岩松, 周仁来. 再认记忆双加工的理论模型及研究方法[J]. 北京师范大学学报, 2008, 44(3): 243-246.
LI Yansong, ZHOU Renlai. The theoretical model of recognition memory dual-processing and methods[J]. Journal of Beijing Normal University, 2008, 44(3): 243-246.
CURRAN T. Brain potentials of recollection and familiarity[J]. Mem Cogn, 2000, 28(6): 923-938.
王湘, 程灶火, 姚树桥, 等. 汉词再认的ERP新旧效应[J]. 航天医学与医学工程, 2005, 2(18): 154-156.
WANG Xiang, CHENG Zaohuo, YAO Shuqiao, et al. ERP correlates of recognition memory for Chinese words[J]. Space Medicine Medical Engineering, 2005, 2(18): 154-156.
CICHOCKI A, ZDUNEK R, PHAN A H, et al. Nonnegative matrix and tensor factorizations: applications to exploratory multi-way data analysis and blind source separation[M]. Chichester, UK: John Wiley Sons, Ltd., 2009: 214-236.
CONG F, PHAN A H, LYYTINEN H, et al. Classifying healthy children and children with attention deficit through features derived from sparse and nonnegative tensor factorization using event-related potential[C]∥Latent Variable Analysis and Signal Separation. Berlin, Germany: Springer-Verlag, 2010: 620-628.
CONG F, PHAN A H, ASTIKAINEN P, et al. Multi-domain feature of event-related potential extracted by nonnegative tensor factorization: 5 vs. 14 electrodes EEG data[M]∥Lecture Notes in Computer Science: Vol 7191. Berlin, Germany: Springer-Verlag, 2012: 502-510.
KIM Y D, CHOI S. Nonnegative tucker decomposition[C]∥IEEE Conference on Computer Vision and Pattern Recognition. Piscataway, USA: IEEE, 2007: 1-8.
周丙寅. 张量分解及其在动态纹理中的应用[D]. 石家庄: 河北师范大学, 2012.
MORUP M, HANSEN L K. Automatic relevance determination for multi-way models[J]. Journal of Chemometrics, 2009, 23(2): 352-363.
TIMMERMAN M E, KIERS H A. Three-mode principal components analysis: choosing the numbers of components and sensitivity to local optima[J]. British Journal of Mathematical and Statistical Psychology, 2000, 53(1): 1-16.
TALLON-BAUDRY C, BERTRAND O, DELPUECH C, et al. Stimulus specificity of phase-locked and non-phase-locked 40 Hz visual responses in human[J]. J Neurosci, 1996, 16(13): 4240-4249.
0
浏览量
4
下载量
0
CSCD
关联资源
相关文章
相关作者
相关机构
京公网安备11010802024621