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功能共振分析方法系統圖

發布時間:2025-10-10 01:36:33

1. 文獻合集 | 靜息態功能連接和腦網路分析方法

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靜息態腦功能成像是腦功能磁共振成像方法的一種。正常人腦在靜息態下依然存在有規律的功能活動網路,且病理狀態下的腦功能活動網路與正常人腦存在差異及重塑,被檢者處於靜息狀態下應用血氧水平依賴腦功能成像獲得腦活動功能圖的成像技術。無須進行復雜的任務設計,可操作性好,可避免基於任務的研究由於任務設計的不同及被檢者執行情況的差異性導致的實驗結果的不可比性。

以下就 靜息態功能磁共振成像 ,及其 腦網路分析方法 : 基於種子點方法( Seed-based )、圖論( Graph theory )、獨立成分分析( ICA ) 以及 不同的腦靜息態網路 列舉相關文獻,以供該領域的學者參考。

靜息態功能磁共振成像 (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

這里主要介紹幾種處理靜息態fMRI數據,檢查腦區之間功能連接的存在和程度的方法, 包括:基於種子點方法、圖論、獨立成分分析。

基於種子點的分析(Seed-based analysis): 種子點可以是先驗定義的區域,或者可以從任務態fMRI實驗中獲得的激活圖中選擇,從而確定特定的感興趣區域。

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

圖論( Graph theory ): 人腦形成一個集成的復雜網路,將所有腦區和子網路連接到一個復雜的系統中。使用圖論分析方法可以檢查大腦網路的整體結構,圖論提供了一個理論框架,其中可以檢查復雜網路的拓撲,並且可以揭示有關功能腦網路局部和全局的信息。

1. Social network analysis: a methodological introction.

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

獨立成分分析( Independent component analysis , ICA ): 靜息態fMRI的ICA是一種盲源分離方法,主要是從靜息態中分離出相互獨立的源。這個方法可以應用於全腦功能連接,將fMRI分離出大尺度腦網路。

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 andal 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

以下是關於不同的 腦靜息態網路 ,如突顯網路、聽覺網路、基底神經節網路、視覺網路、視覺空間網路、默認模式網路、語言網路、執行網路&執行控制網路、楔前葉網路、感覺運動網路等相關文獻合集。

突顯網路

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

聽覺網路

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

基底神經節網路

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-Inced 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

視覺網路

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

視覺空間網路

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

默認模式網路

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

語言網路

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

執行網路 & 執行控制網路

1. ConceptualProcessing ring 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

楔前葉網路

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

感覺運動網路

1. A small number of abnormal brain connections predictsalt 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;

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