Measuring and manipulating brain connectivity with resting state functional connectivity magnetic resonance imaging (fcMRI) and transcranial magnetic stimulation (TMS)

被引:329
作者
Fox, Michael D. [1 ,2 ]
Halko, Mark A. [2 ]
Eldaief, Mark C. [2 ,3 ]
Pascual-Leone, Alvaro [2 ,4 ]
机构
[1] Harvard Univ, Brigham & Womens Hosp, Sch Med, Massachusetts Gen Hosp, Boston, MA 02115 USA
[2] Beth Israel Deaconess Med Ctr, Berenson Allen Ctr Noninvas Brain Stimulat, Boston, MA 02215 USA
[3] Harvard Univ, Beth Israel Deaconess Med Ctr, Div Cognit Neurol, Dept Neurol,Med Sch, Boston, MA 02215 USA
[4] Univ Autonoma Barcelona, Inst Guttmann, Hosp Neurorehabil, Inst Univ Adscrit, E-08193 Barcelona, Spain
关键词
Spontaneous brain activity; Non-invasive brain stimulation; Neuro-navigation; Anticorrelation; fMRI; DEFAULT-MODE NETWORK; HUMAN MOTOR CORTEX; DORSOLATERAL PREFRONTAL CORTEX; LOW-FREQUENCY RTMS; MEDICATION-RESISTANT DEPRESSION; CORTICAL EFFECTIVE CONNECTIVITY; PAIRED ASSOCIATIVE STIMULATION; INDEPENDENT COMPONENT ANALYSIS; ANTERIOR CINGULATE CORTEX; BOLD SIGNAL FLUCTUATIONS;
D O I
10.1016/j.neuroimage.2012.03.035
中图分类号
Q189 [神经科学];
学科分类号
071006 [神经生物学];
摘要
Both resting state functional magnetic resonance imaging (fcMRI) and transcranial magnetic stimulation (TMS) are increasingly popular techniques that can be used to non-invasively measure brain connectivity in human subjects. TMS shows additional promise as a method to manipulate brain connectivity. In this review we discuss how these two complimentary tools can be combined to optimally study brain connectivity and manipulate distributed brain networks. Important clinical applications include using resting state fcMRI to guide target selection for TMS and using TMS to modulate pathological network interactions identified with resting state fcMRI. The combination of TMS and resting state fcMRI has the potential to accelerate the translation of both techniques into the clinical realm and promises a new approach to the diagnosis and treatment of neurological and psychiatric diseases that demonstrate network pathology. (C) 2012 Elsevier Inc. All rights reserved.
引用
收藏
页码:2232 / 2243
页数:12
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