Literature DB >> 14615300

Interindividual differences in functional interactions among prefrontal, parietal and parahippocampal regions during working memory.

Michael F Glabus1, Barry Horwitz, John L Holt, Philip D Kohn, Brooke K Gerton, Joseph H Callicott, Andreas Meyer-Lindenberg, Karen Faith Berman.   

Abstract

To clarify the neural systems deployed by individual subjects during working memory (WM), we collected functional neuroimaging data from healthy subjects, and constructed a model of 2-back WM using structural equation modeling (SEM). A group model was constructed, and models for each subject were validated against it. The group model consisted principally of regions in the prefrontal and parietal cortex, with considerable interindividual variance in the single-subject models. To explore this variance, subjects were split into two groups based on performance. Performance level and self-reported strategy scores were used in a correlation analysis against path weights between nodes of individual models. High performers utilized a left hemisphere sub-network involving inferior parietal lobule and Broca's area, whereas lower performers utilized a right hemisphere sub-network with interactions between inferior parietal lobule and dorsolateral prefrontal cortex. Further, we observed an interaction between the parahippocampal formation and the inferior parietal lobule that was related to the different strategies used by the individuals to perform the task. Strategy and performance level appear to be intricately related in this task, with neural systems supporting verbal processing producing better performance than those associated with spatial processing. These results demonstrate that individual behavioral characteristics are reflected in specific neurofunctional patterns at the system level and that these can be captured by analytical techniques such as SEM.

Mesh:

Year:  2003        PMID: 14615300     DOI: 10.1093/cercor/bhg082

Source DB:  PubMed          Journal:  Cereb Cortex        ISSN: 1047-3211            Impact factor:   5.357


  29 in total

1.  Intrinsic resting-state activity predicts working memory brain activation and behavioral performance.

Authors:  Qihong Zou; Thomas J Ross; Hong Gu; Xiujuan Geng; Xi-Nian Zuo; L Elliot Hong; Jia-Hong Gao; Elliot A Stein; Yu-Feng Zang; Yihong Yang
Journal:  Hum Brain Mapp       Date:  2012-06-19       Impact factor: 5.038

2.  Modeling Dynamic Functional Neuroimaging Data Using Structural Equation Modeling.

Authors:  Larry R Price; Angela R Laird; Peter T Fox; Roger J Ingham
Journal:  Struct Equ Modeling       Date:  2009       Impact factor: 6.125

3.  Neuropsychological predictors of BOLD response during a spatial working memory task in adolescents: what can performance tell us about fMRI response patterns?

Authors:  Bonnie J Nagel; Valerie C Barlett; Alecia D Schweinsburg; Susan F Tapert
Journal:  J Clin Exp Neuropsychol       Date:  2005-10       Impact factor: 2.475

4.  Investigating the neural basis for functional and effective connectivity. Application to fMRI.

Authors:  Barry Horwitz; Brent Warner; Julie Fitzer; M-A Tagamets; Fatima T Husain; Theresa W Long
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2005-05-29       Impact factor: 6.237

5.  Early risk, attention, and brain activation in adolescents born preterm.

Authors:  Dennis P Carmody; Margaret Bendersky; Stanley M Dunn; J Kevin DeMarco; Thomas Hegyi; Mark Hiatt; Michael Lewis
Journal:  Child Dev       Date:  2006 Mar-Apr

6.  Brain connectivity related to working memory performance.

Authors:  Michelle Hampson; Naomi R Driesen; Pawel Skudlarski; John C Gore; R Todd Constable
Journal:  J Neurosci       Date:  2006-12-20       Impact factor: 6.167

7.  Unified structural equation modeling approach for the analysis of multisubject, multivariate functional MRI data.

Authors:  Jieun Kim; Wei Zhu; Linda Chang; Peter M Bentler; Thomas Ernst
Journal:  Hum Brain Mapp       Date:  2007-02       Impact factor: 5.038

8.  Modeling motor connectivity using TMS/PET and structural equation modeling.

Authors:  Angela R Laird; Jacob M Robbins; Karl Li; Larry R Price; Matthew D Cykowski; Shalini Narayana; Robert W Laird; Crystal Franklin; Peter T Fox
Journal:  Neuroimage       Date:  2008-02-15       Impact factor: 6.556

9.  Reorganization of functional brain networks mediates the improvement of cognitive performance following real-time neurofeedback training of working memory.

Authors:  Gaoyan Zhang; Li Yao; Jiahui Shen; Yihong Yang; Xiaojie Zhao
Journal:  Hum Brain Mapp       Date:  2014-12-26       Impact factor: 5.038

10.  Performance level modulates adult age differences in brain activation during spatial working memory.

Authors:  Irene E Nagel; Claudia Preuschhof; Shu-Chen Li; Lars Nyberg; Lars Bäckman; Ulman Lindenberger; Hauke R Heekeren
Journal:  Proc Natl Acad Sci U S A       Date:  2009-12-14       Impact factor: 11.205

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.