Metaanalytic Connectivity Modeling: Delineating the Functional Connectivity of the Human Amygdala

被引:268
作者
Robinson, Jennifer L. [1 ,2 ,3 ,4 ]
Laird, Angela R. [4 ]
Glahn, David C. [4 ,5 ,6 ]
Lovallo, William R. [7 ]
Fox, Peter T. [4 ]
机构
[1] Scott & White Mem Hosp & Clin, Coll Med, Texas A&M Hlth Sci Ctr, Inst Neurosci, Temple, TX 76508 USA
[2] Texas A&M Hlth Sci Ctr, Coll Med, Dept Neurosurg, Temple, TX USA
[3] Texas A&M Hlth Sci Ctr, Coll Med, Dept Psychiat & Behav Sci, Temple, TX USA
[4] Univ Texas Hlth Sci Ctr San Antonio, Res Imaging Ctr, San Antonio, TX 78229 USA
[5] Yale Univ, Dept Psychiat, Hartford, CT USA
[6] Yale Univ, Inst Living, Hartford, CT USA
[7] Vet Affairs Med Ctr, Behav Sci Labs, Oklahoma City, OK 73104 USA
关键词
meta-analysis; brainmap; fMRI; PET; CoCoMac; TRANSCRANIAL MAGNETIC STIMULATION; ANTERIOR CINGULATE CORTEX; HUMAN BRAIN; CEREBRAL-CORTEX; RHESUS-MONKEY; NEGATIVE EMOTION; NEURAL SYSTEMS; COGNITION; DATABASE; SINGLE;
D O I
10.1002/hbm.20854
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Functional neuroimaging has evolved into an indispensable tool for noninvasively investigating brain function. A recent development of such methodology is the creation of connectivity models for brain regions and related networks, efforts that have been inhibited by notable limitations. We present a new method for ascertaining functional connectivity of specific brain structures using metaanalytic connectivity modeling (MACM), along with validation of our method using a nonhuman primate database. Drawing from decades of neuroimaging research and spanning multiple behavioral domains, the method overcomes many weaknesses of conventional connectivity analyses and provides a simple, automated alternative to developing accurate and robust models of anatomically-defined human functional connectivity. Applying MACM to the amygdala, a small structure of the brain with a complex network of connections, we found high coherence with anatomical studies in nonhuman primates as well as human-based theoretical models of emotive-cognitive integration, providing evidence for this novel method's utility. Hum Brain Mapp 31:173-184, 2010. (C) 2009 Wiley-Liss, Inc.
引用
收藏
页码:173 / 184
页数:12
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