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静息态脑功能成像是脑功能磁共振成像方法的一种 。正常人脑在静息态下依然存在有规律的功能活动网络 ，且病理状态下的脑功能活动网络与正常人脑存在差异及重塑
，被检者处于静息状态下应用血氧水平依赖脑功能成像获得脑活动功能图的成像技术
。无须进行复杂的任务设计，可操作性好 ，可避免基于任务的研究由于任务设计的不同及被检者执行情况的差异性导致的实验结果的不可比性。

以下就 静息态功能磁共振成像 
，及其 脑网络分析方法 ： 基于种子点方法（ Seed-based ）、图论（ Graph theory ） 、独立成分分析（ ICA ） 以及 不同的脑静息态网络 列举相关文献，以供该领域的学者参考 。

静息态功能磁共振成像 (rs-fMRI )

1.?Resting statefunctional magnetic resonance imaging:an emerging clinical tool.

doi:10.4103/0028-3886.111107

2.?Clinical applicationsof resting state functional connectivity.

doi:10.3389/fnsys.2010.00019

3.?Resting state activityin patients with disorders of consciousness.

doi:10.1016/j.yfrne.2010.11.002

4.?Resting state fMRI: apersonal history.

doi:10.1016/j.neuroimage.2012.01.090

5.?Brain work and brain imaging.

doi:10.1146/annurev.neuro.29.051605.112819

这里主要介绍几种处理静息态fMRI数据 ，检查脑区之间功能连接的存在和程度的方法
， 包括：基于种子点方法
、图论、独立成分分析
。

基于种子点的分析（Seed-based analysis）： 种子点可以是先验定义的区域，或者可以从任务态fMRI实验中获得的激活图中选择 ，从而确定特定的感兴趣区域。

1. Functional connectivity in the motor cortex of resting human brain usingecho-planar MRI.

doi: 10.1002/mrm.1910340409

2. Exploring the brain network: a review on resting-state fMRI functionalconnectivity.

doi: 10.1016/j.euroneuro.2010.03.008

3. Review of methods for functional brain connectivity detection using fMRI.

doi: 10.1016/j.compmedimag.2008.10.011

4. DPARSF: a MATLAB toolbox for “pipeline
” data analysis of resting-statefMRI.

doi: 10.3389/fnsys.2010.00013

5. Abnormal spontaneous brain activity in minimal hepatic encephalopathy:resting-state fMRI study.

doi: 10.5152/dir.2015.15208

6. A multisite resting state fMRI study on the amplitude of low frequencyfluctuations in schizophrenia.

doi: 10.3389/fnins.2013.00137

7. Regional homogeneity approach to fMRI data analysis.

doi:10.1016/j.neuroimage.2003.12.030

8. Competition between functional brain networks mediates behavioralvariability.

doi: 10.1016/j.neuroimage.2007.08.008

9. REST: a toolkit for resting-state functional magnetic resonance imagingdata processing.

doi: 10.1371/journal.pone.0025031

图论（ Graph theory ）： 人脑形成一个集成的复杂网络
，将所有脑区和子网络连接到一个复杂的系统中 。使用图论分析方法可以检查大脑网络的整体结构，图论提供了一个理论框架 ，其中可以检查复杂网络的拓扑，并且可以揭示有关功能脑网络局部和全局的信息
。

1. Social network analysis: a methodological introduction.

doi: 10.1111/j.1467-839X.2007.00241.x

2. A computational study of whole-brain connectivity in resting state andtask fMRI.

doi: 10.12659/MSM.891142

3. Brain connectivity in autism.

doi:10.3389/fnhum.2014.00349

4. Development of large-scale functional brain networks in children.

doi: 10.1371/journal.pbio.1000157

5. Complex brain networks: graph theoretical analysis of structural andfunctional systems.

doi: 10.1038/nrn2618

6. Efficiency and cost of economical brain functional networks.

doi: 10.1371/journal.pcbi.0030017

7. Efficient behavior of smallworld networks.

doi: 10.17877/DE290R-11359

8. Graph-based network analysis of resting-state functional MRI.

doi: 10.3389/fnsys.2010.00016

9. The ubiquity of small-world networks.

doi: 10.1089/brain.2011.0038

独立成分分析（ Independent component analysis
， ICA ）： 静息态fMRI的ICA是一种盲源分离方法，主要是从静息态中分离出相互独立的源。这个方法可以应用于全脑功能连接 ，将fMRI分离出大尺度脑网络 。

1. Exploring the brain network: a review on resting-state fMRI functionalconnectivity.

doi: 10.1016/j.euroneuro.2010.03.008

2. Advances and pitfalls in the analysis and interpretation of restingstatefMRI data.

doi: 10.3389/fnsys.2010.00008

3. An information-maximization approach to blind separation and blinddeconvolution.

doi: 10.1162/neco.1995.7.6.1129

4. Analysis of fMRI data by blind separation into independent spatialcomponents.

doi: 10.1002/(SICI)1097-0193(1998)6:3<160::AID-HBM5>3.0.CO;2-1

5. Intrinsic brain activity in altered states of consciousness: howconscious is the default mode of brain function?

doi: 10.1196/annals.1417.015

6. Group comparison of resting-state FMRI data using multi-subject ICA anddual regression.

doi: 10.1016/S1053-8119(09)71511-3

7. A review of group ICA for fMRI data and ICA for joint inference ofimaging, genetic, and ERP data.

doi: 10.1016/j.neuroimage.2008.10.057

8. A unified framework for group independent component analysis formulti-subject fMRI data.

doi: 10.1016/j.neuroimage.2008.05.008

9. Independent component analysis of fMRI group studies by self-organizingclustering.

doi: 10.1016/j.neuroimage.2004.10.042

10. Comparison of three methods for generating group statistical inferencesfrom independent component analysis of functional magnetic resonance imagingdata.

doi: 10.1002/jmri.20009

以下是关于不同的 脑静息态网络 
，如突显网络 、听觉网络
、基底神经节网络、视觉网络 、视觉空间网络
、默认模式网络、语言网络 、执行网络&执行控制网络
、楔前叶网络、感觉运动网络等相关文献合集
。

突显网络

1. Cognitive Control and the Salience Network: An Investigation of ErrorProcessing and Effective Connectivity.

doi: 10.1523/JNEUROSCI.4692-12.2013

2. Salience processing and insular cortical function and dysfunction.

doi: 10.1038/nrn3857

3. Saliency, switching, attention and control: a network model of insulafunction.

doi: 10.1007/s00429-010-0262-0

听觉网络

1. Asymmetric Interhemispheric Transfer in the Auditory Network: Evidencefrom TMS, Resting-State fMRI, and Diffusion Imaging.

doi: 10.1523/JNEUROSCI.2333-15.2015

2. Default Mode, Dorsal Attention and Auditory Resting State NetworksExhibit Differential Functional Connectivity in Tinnitus and Hearing Loss.

doi: 10.1371/journal.pone.0076488

基底神经节网络

1. Aberrant functional connectivity within the basal ganglia of patientswith Parkinson’s disease.

doi: 10.1016/j.nicl.2015.04.003

2. Functional connectivity in the basal ganglia network differentiates PDpatients from controls.

doi: 10.1212/wnl.0000000000000592

3. Identifying the Basal Ganglia Network Model Markers forMedication-Induced Impulsivity in Parkinson's Disease Patients.

doi: 10.1371/journal.pone.0127542

4. The basal ganglia: A neural network with more than motor function.

doi: 10.1016/S1071-9091(02)00003-7

视觉网络

1. Consistent resting-state networks across healthysubjects.

doi: 10.1073/pnas.0601417103

2. Investigations into resting-stateconnectivity using independent component analysis.

doi: 10. 1098/rstb.2005.1634

3. Spontaneous Activity Associated with PrimaryVisual Cortex: A Resting-State fMRI Study.

doi: 10.1093/cercor/bhm105

视觉空间网络

1.?Default-mode network activity distinguishes Alzheimer’sdisease from healthy aging: Evidence from functional MRI.

doi: 10.1073/pnas.0308627101

2. Functional connectivity in the resting brain: A network analysis of thedefault mode hypothesis.

doi: 10.1073/pnas.0135058100

3. Investigations into Resting-State Connectivity Using IndependentComponent Analysis.

doi: 10.1098/rsbt.2005.1634

4.Searching for a baseline: functional imaging andthe resting human brain.

doi: 10.1038/35094500

默认模式网络

1. Development of the Default Mode and CentralExecutive Networks across early adolescence: A longitudinal study.

doi: 10.1016/j.dcn.2014.08.002

2. Searching for a baseline: functional imaging and the resting human brain.

?doi: 10.1038/35094500

语言网络

1. Evidenceof Mirror Neurons in Human Inferior Frontal Gyrus.

doi: 10.1523/JNEUROSCI.2668-09.2009

2. How Localized are Language Brain Areas? A Review of Brodmann Areas Involvementin Oral Language.

doi: 10.1093/arclin/acv081

3. Mirror Neurons and the Lateralization of Human Language.

doi: 10.1523/JNEUROSCI.1452-06.2006

4. Speech-associated gestures, Broca’s area, and the human mirror system.

doi: 10.1016/j.bandl.2007.02.008

执行网络 & 执行控制网络

1. ConceptualProcessing during the Conscious Resting State: A Functional MRI Study.

doi: 10.1162/089892999563265

2. Dissociable Intrinsic Connectivity Networks for Salience Processing andExecutive Control.

doi: 10.1523/JNEUROSCI.5587-06.2007

3. Resting-state activity in the left executive control network isassociated with behavioral approach and is increased in substance dependence.

doi: 10.1016/j.drugalcdep.2014.02.320

4. Searching for Activations That Generalize Over Tasks.

doi: 10.1002/(SICI)1097-0193(1997)5:4<317::AID-HBM19>3.0.CO;2-A

5. The Human Brain Is Intrinsically Organized into Dynamic, AnticorrelatedFunctional Networks.

doi: 10.1073/pnas.0504136102

楔前叶网络

1. Posterior Cingulate Cortex Activation by EmotionalWords: fMRI Evidence From a Valence Decision Task.

doi: 10.1002/hbm.10075

2. Posterior Cingulate Cortex Mediates Outcome-Contingent Allocation ofBehavior.

doi: 10.1016/j.neuron.2008.09.012

3. Precuneus Is a Functional Core of the Default-Mode Network.

doi: 10.1523/JNEUROSCI.4227-13.2014

4. Remembering familiar people: the posterior cingulate cortex andautobiographical memory retrieval.

doi: 10.1016/S0306-4522(01)00108-7

5. The precuneus/posterior cingulate cortex plays a pivotal role in thedefault mode network: Evidence from a partial correlation network analysis.

doi: 10.1016/j.neuroimage.2008.05.059

6. The precuneus: a review of its functional anatomy and behaviouralcorrelates.

doi: 10.1093/brain/awl004

感觉运动网络

1. A small number of abnormal brain connections predictsadult autism spectrum disorder.

doi: 10.1038/ncomms11254

2. Functional Connectivity in the Motor Cortex of Resting Human Brain UsingEcho-Planar MRI.

doi: 10.1002/mrm.1910340409

3. Identifying patients with Alzheimer’s disease using resting-state fMRI andgraph theory.

doi: 10.1016/j.clinph.2015.02.060

4. Recovery of resting brain connectivity ensuing mild traumatic braininjury.

doi: 10.3389/fnhum.2015.00513

5. Resting state fMRI: A personal history.

doi: 10.1016/j.neuroimage.2012.01.090

6. Resting state functional MRI in Parkinson’s disease: the impact of deepbrain stimulation on ‘effective’ connectivity.

doi: 10.1093/brain/awu027

7. Resting-State fMRI Connectivity Impairment in Schizophrenia and BipolarDisorder.

doi: 10.1093/schbul/sbt092

8. Simultaneous Assessment of Flow and BOLD Signals in Resting-StateFunctional Connectivity Maps.

doi: 10.1002/(SICI)1099-1492(199706/08)10:4/5<165::AID-NBM454>3.0.CO;