REAL-TIME FMRI TRAINING-INDUCED CHANGES IN REGIONAL CONNECTIVITY MEDIATING VERBAL WORKING MEMORY BEHAVIORAL PERFORMANCE

被引:25
作者
Shen, J. [1 ]
Zhang, G. [1 ,2 ]
Yao, L. [1 ,3 ]
Zhao, X. [1 ]
机构
[1] Beijing Normal Univ, Coll Informat Sci & Technol, Beijing 100875, Peoples R China
[2] Tianjin Univ, Sch Comp Sci & Technol, Tianjin Key Lab Cognit Comp & Applicat, Tianjin 300072, Peoples R China
[3] Beijing Normal Univ, State Key Lab Cognit Neurosci & Learning, Beijing 100875, Peoples R China
基金
中国国家自然科学基金;
关键词
verbal working memory; real-time fMRI; neurofeedback; training; structural equation modeling; frontoparietal connection; DIRECT-CURRENT STIMULATION; PREFRONTAL CORTEX; CORTICAL ACTIVITY; BRAIN ACTIVATION; PATH-ANALYSIS; NETWORK; METAANALYSIS; COMPONENTS; PARIETAL; TASK;
D O I
10.1016/j.neuroscience.2014.12.071
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Working memory refers to the ability to temporarily store and manipulate information that is necessary for complex cognition activities. Previous studies have demonstrated that working memory capacity can be improved by behavioral training, and brain activities in the frontal and parietal cortices and the connections between these regions are also altered by training. Our recent neurofeedback training has proven that the regulation of the left dorsal lateral prefrontal cortex (DLPFC) activity using real-time functional magnetic resonance imaging (rtfMRI) can improve working memory performance. However, how working memory training promotes interaction between brain regions and whether this promotion correlates with performance improvement remain unclear. In this study, we employed structural equation modeling (SEM) to calculate the interactions between the regions within the working memory network during neurofeedback training. The results revealed that the direct effect of the frontoparietal connection in the left hemisphere was enhanced by the rtfMRI training. Specifically, the increase in the path from the left DLPFC to the left inferior parietal lobule (IPL) was positively correlated with improved performance in verbal working memory. These findings demonstrate the important role of the frontoparietal connection in working memory training and suggest that increases in frontoparietal connectivity might be a key factor associated with behavioral improvement. (C) 2015 IBRO. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码:144 / 152
页数:9
相关论文
共 46 条
  • [1] [Anonymous], 2011, BRAIN STIMULATION, V4, P84
  • [2] Working memory and language: an overview
    Baddeley, A
    [J]. JOURNAL OF COMMUNICATION DISORDERS, 2003, 36 (03) : 189 - 208
  • [3] The episodic buffer: a new component of working memory?
    Baddeley, A
    [J]. TRENDS IN COGNITIVE SCIENCES, 2000, 4 (11) : 417 - 423
  • [4] How good is good enough in path analysis of fMRI data?
    Bullmore, ET
    Horwitz, B
    Honey, G
    Brammer, M
    Williams, S
    Sharma, T
    [J]. NEUROIMAGE, 2000, 11 (04) : 289 - 301
  • [5] Aging and repetition priming for targets and distracters in a working memory task
    Caggiano, Daniel M.
    Jiang, Yang
    Parasuraman, Raja
    [J]. AGING NEUROPSYCHOLOGY AND COGNITION, 2006, 13 (3-4) : 552 - 573
  • [6] Regulation of anterior insular cortex activity using real-time fMRI
    Caria, Andrea
    Veit, Ralf
    Sitaram, Ranganatha
    Lotze, Martin
    Weiskopf, Nikolaus
    Grodd, Wolfgang
    Birbaumer, Niels
    [J]. NEUROIMAGE, 2007, 35 (03) : 1238 - 1246
  • [7] Volitional Control of Anterior Insula Activity Modulates the Response to Aversive Stimuli. A Real-Time Functional Magnetic Resonance Imaging Study
    Caria, Andrea
    Sitaram, Ranganatha
    Veit, Ralf
    Begliomini, Chiara
    Birbaumer, Niels
    [J]. BIOLOGICAL PSYCHIATRY, 2010, 68 (05) : 425 - 432
  • [8] Carter CS, 1999, REV NEUROSCIENCE, V10, P49
  • [9] Cazalis Fabienne, 2011, Front Neurol, V1, P158, DOI 10.3389/fneur.2010.00158
  • [10] Vector autoregression, structural equation modeling, and their synthesis in neuroimaging data analysis
    Chen, Gang
    Glen, Daniel R.
    Saad, Ziad S.
    Hamilton, J. Paul
    Thomason, Moriah E.
    Gotlib, Ian H.
    Cox, Robert W.
    [J]. COMPUTERS IN BIOLOGY AND MEDICINE, 2011, 41 (12) : 1142 - 1155