|
1）Stephan KE, Penny WD, Moran RJ, et al. Ten simple rules for dynamic causal modeling. Neuroimage. 2010; 49: 3099-109
|
|
|
|
2）Kahan J, Foltynie T. Understanding DCM: ten simple rules for the clinician. Neuroimage. 2013; 83: 542-9
|
|
|
|
|
|
3）Sato W, Toichi M, Uono S, et al. Impaired social brain network for processing dynamic facial expressions in autism spectrum disorders. BMC Neurosci. 2012; 13: 99
|
|
|
|
|
|
4）Rowe JB. Connectivity analysis is essential to understand neurological disorders. Front Syst Neurosci. 2010; 4. pii: 144
|
|
|
|
|
|
5）Seghier ML, Zeidman P, Neufeld NH, et al. Identifying abnormal connectivity in patients using dynamic causal modeling of FMRI responses. Front Syst Neurosci. 2010; 4. pii: 142
|
|
|
|
|
|
6）Fox MD, Snyder AZ, Vincent JL, et al. The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proc Natl Acad Sci U S A. 2005; 102: 9673-8
|
|
|
|
|
|
7）Whitfield-Gabrieli S, Ford JM. Default mode network activity and connectivity in psychopathology. Annu Rev Clin Psychol. 2012; 8: 49-76
|
|
|
|
|
|
8）van den Heuvel MP, Hulshoff Pol HE. Exploring the brain network: a review on resting-state fMRI functional connectivity. Eur Neuropsychopharmacol. 2010; 20: 519-34
|
|
|
|
|
|
9）Fornito A, Bullmore ET. Connectomics: A new paradigm for understanding brain disease. Eur Neuropsychopharmacol. 2014 Mar 5. [Epub ahead of print]
|
|
|
|
|
|
10）Fox MD, Greicius M. Clinical applications of resting state functional connectivity. Front Syst Neurosci. 2010; 4: 19
|
|
|
|
|
|
11）Mur M, Bandettini PA, Kriegeskorte N. Revealing representational content with pattern-information fMRI--an introductory guide. Soc Cogn Affect Neurosci. 2009; 4: 101-9
|
|
|
|
|
|
12）Du W, Calhoun VD, Li H, et al. High classification accuracy for schizophrenia with rest and task FMRI data. Front Hum Neurosci. 2012; 6: 145
|
|
|
|
|
|
13）Yoon JH, Nguyen DV, McVay LM, et al. Automated classification of fMRI during cognitive control identifies more severely disorganized subjects with schizophrenia. Schizophr Res. 2012; 135: 28-33
|
|
|
|
|
|
14）Zarogianni E, Moorhead TW, Lawrie SM. Towards the identification of imaging biomarkers in schizophrenia, using multivariate pattern classification at a single-subject level. Neuroimage Clin. 2013; 3: 279-89
|
|
|
|
|
|
15）Hahn T, Marquand AF, Ehlis AC, et al. Integrating neurobiological markers of depression. Arch Gen Psychiatry. 2011; 68: 361-8
|
|
|
|
|
|
16）Coutanche MN, Thompson-Schill SL, Schultz RT. Multi-voxel pattern analysis of fMRI data predicts clinical symptom severity. Neuroimage. 2011; 57: 113-23
|
|
|
|
|
|
17）Weiskopf N. Real-time fMRI and its application to neurofeedback. Neuroimage. 2012; 62: 682-92
|
|
|
|
|
|
18）deCharms RC. Applications of real-time fMRI. Nat Rev Neurosci. 2008; 9: 720-9
|
|
|
|
|
|
19）Shibata K, Watanabe T, Sasaki Y, et al. Perceptual learning incepted by decoded fMRI neurofeedback without stimulus presentation. Science. 2011; 334: 1413-5
|
|
|
|
|
|
20）Linden DE, Habes I, Johnston SJ, et al. Real-time self-regulation of emotion networks in patients with depression. PloS One. 2012; 7: e38115
|
|
|
|
|
|
21）deCharms RC, Maeda F, Glover GH, et al. Control over brain activation and pain learned by using real-time functional MRI. Proc Natl Acad Sci U S A. 2005; 102: 18626-31
|
|
|
|
|
|
22）Subramanian L, Hindle JV, Johnston S, et al. Real-time functional magnetic resonance imaging neurofeedback for treatment of Parkinsonʼs disease. J Neurosci. 2011; 31: 16309-17
|
|
|
|
|
|
23）Ruiz S, Lee S, Soekadar SR, et al. Acquired self-control of insula cortex modulates emotion recognition and brain network connectivity in schizophrenia. Hum Brain Mapp. 2013; 34: 200-12
|
|
|
|
|