The real-time fMRI neurofeedback based stratification of Default Network Regulation Neuroimaging data repository

NeuroImage

Volumn 146, Issue , 2017, Pages 157-170

  McDonald, Amalia R ^a   Muraskin, Jordan ^a   Dam, Nicholas T Van ^a,b   Froehlich, Caroline ^a   Puccio, Benjamin ^a   Pellman, John ^b   Bauer, Clemens C C ^c   Akeyson, Alexis ^a   Breland, Melissa M ^a   Calhoun, Vince D ^d,e   Carter, Steven ^a   Chang, Tiffany P ^a   Gessner, Chelsea ^a   Gianonne, Alyssa ^a   Giavasis, Steven ^b   Glass, Jamie ^a   Homann, Steven ^a   King, Margaret ^d   Kramer, Melissa ^a   Landis, Drew ^d   Lieval, Alexis ^a   Lisinski, Jonathan ^f   Mackay Brandt, Anna ^a,g   Miller, Brittny ^d   Panek, Laura ^a   Reed, Hayley ^a   Santiago, Christine ^a   Schoell, Eszter ^a   Sinnig, Richard ^a   Sital, Melissa ^a   Taverna, Elise ^a   Tobe, Russell ^a   Trautman, Kristin ^a   Varghese, Betty ^a   Walden, Lauren ^a   Wang, Runtang ^d   Waters, Abigail B ^a   Wood, Dylan C ^d   Castellanos, F Xavier ^a,h   Leventhal, Bennett ⁱ   Colcombe, Stanley J ^a   LaConte, Stephen ^f,j   Milham, Michael P ^a,b   Craddock, R Cameron ^a,b   more..

^a NATHAN S KLINE INSTITUTE FOR PSYCHIATRIC RESEARCH   (United States)

^b CHILD MIND INSTITUTE   (United States)

^c MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^d MIND RESEARCH NETWORK   (United States)

^e University of New Mexico   (United States)

^f VIRGINIA TECH CARILION SCHOOL OF MEDICINE   (United States)

^g Howard Hughes Medical Institute   (United States)

^h NEW YORK UNIVERSITY MEDICAL CENTER   (United States)

ⁱ UNIVERSITY OF CALIFORNIA   (United States)

^j VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY   (United States)

more..

Author keywords

Data sharing; Default mode network; Functional MRI; Neurofeedback; Real time fMRI

Indexed keywords

ADULT; AGE DISTRIBUTION; ARTICLE; BEHAVIOR ASSESSMENT; BOLD SIGNAL; BRAIN FUNCTION; BRAIN RADIOGRAPHY; CLINICAL DATA REPOSITORY; DEFAULT MODE NETWORK; ECHO PLANAR IMAGING; EMOTION; ETHNIC DIFFERENCE; FEMALE; FUNCTIONAL MAGNETIC RESONANCE IMAGING; HUMAN; HUMAN EXPERIMENT; IMAGE ANALYSIS; IMAGE PROCESSING; MALE; NEUROFEEDBACK; NEUROMODULATION; NORMAL HUMAN; PRIORITY JOURNAL; RESTING STATE NETWORK; SEX DIFFERENCE; TASK PERFORMANCE; THINKING; VISUAL INFORMATION; BRAIN; BRAIN MAPPING; FACTUAL DATABASE; INDIVIDUALITY; INFORMATION DISSEMINATION; INFORMATION RETRIEVAL; MENTAL DISEASE; MIDDLE AGED; NERVE TRACT; NEUROIMAGING; NUCLEAR MAGNETIC RESONANCE IMAGING; PATHOPHYSIOLOGY; PHENOTYPE; YOUNG ADULT;

ADULT; BRAIN; BRAIN MAPPING; DATABASES, FACTUAL; ECHO-PLANAR IMAGING; FEMALE; HUMANS; INDIVIDUALITY; INFORMATION DISSEMINATION; INFORMATION STORAGE AND RETRIEVAL; MAGNETIC RESONANCE IMAGING; MALE; MENTAL DISORDERS; MIDDLE AGED; NEURAL PATHWAYS; NEUROFEEDBACK; NEUROIMAGING; PHENOTYPE; YOUNG ADULT;

EID: 84998717787     PISSN: 10538119     EISSN: 10959572     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2016.10.048     Document Type: Article

References (80)

1. Andrews-Hanna, J.R., Smallwood, J., Spreng, R.N., The default network and self-generated thought component processes, dynamic control, and clinical relevance. Ann. N. Y. Acad. Sci. 1316 (2014), 29–52, 10.1111/nyas.12360 http://www.ncbi.nlm.nih.gov/pubmed/24502540.
2. Anticevic, A., Cole, M.W., Murray, J.D., Corlett, P.R., Wang, X.-J., Krystal, J.H., The role of default network deactivation in cognition and disease. Trends Cogn. Sci. 16:12 (2012), 584–592, 10.1016/j.tics.2012.10.008.
3. Atkinson, D., Hill, D.L., Stoyle, P.N., Summers, P.E., Keevil, S.F., Automatic correction of motion artifacts in magnetic resonance images using an entropy focus criterion. IEEE Trans. Med Imaging 16:6 (1997), 903–910, 10.1109/42.650886 http://www.ncbi.nlm.nih.gov/pubmed/9533590.
4. Avants, B., Epstein, C., Grossman, M., Gee, J., Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain. Med. Image Anal. 12:1 (2008), 26–41, 10.1016/j.media.2007.06.004.
5. Behzadi, Y., Restom, K., Liau, J., Liu, T.T., A component based noise correction method (compcor) for bold and perfusion based fmri. NeuroImage 37:1 (2007), 90–101, 10.1016/j.neuroimage.2007.04.042.
6. Buckner, R.L., Andrews-Hanna, J.R., Schacter, D.L., The brains default networkanatomy, function, and relevance to disease. Ann. N. Y. Acad. Sci. 1124:1 (2008), 1–38, 10.1196/annals.1440.011.
7. Bush, G., Shin, L.M., The multi-source interference taskan fmri task that reliably activates the cingulo-frontal-parietal cognitive/attention network. Nat. Protoc. 1:1 (2006), 308–313, 10.1038/nprot.2006.48.
8. Bush, G., Shin, L.M., Holmes, J., Rosen, B.R., Vogt, B.A., The multi-source interference task validation study with fmri in individual subjects. Mol. Psychiatry 8:1 (2003), 60–70, 10.1038/sj.mp.4001217 http://www.ncbi.nlm.nih.gov/pubmed/12556909.
9. Calhoun, V.D., Maciejewski, P.K., Pearlson, G.D., Kiehl, K.A., Temporal lobe and “default” hemodynamic brain modes discriminate between schizophrenia and bipolar disorder. Hum. Brain Mapp. 29:11 (2008), 1265–1275, 10.1002/hbm.20463.
10. Cox, R.W., Afni software for analysis and visualization of functional magnetic resonance neuroimages. Comput. Biomed. Res. 29:3 (1996), 162–173, 10.1006/cbmr.1996.0014.
11. Cox, R.W., Jesmanowicz, A., Real-time 3d image registration for functional mri. Magn. Reson. Med. 42:6 (1999), 1014–1018 http://www.ncbi.nlm.nih.gov/pubmed/10571921.
12. Cox, R.W., Jesmanowicz, A., Hyde, J.S., Real-time functional magnetic resonance imaging. Magn. Reson. Med. 33:2 (1995), 230–236, 10.1002/mrm.1910330213.
13. Craddock, R.C., Lisinski, J.M., Chiu, P., Mayberg, H.S., LaConte, S.M., 2012. Real-time tracking and biofeedback of the default mode network, In: Proceedings of the 18th Annual Meeting Organization of Human Brain Mapping.
14. Craddock, R.C., Sikka, S., Cheung, B., Khanuja, R., Ghosh, S., Yan, C.G., Li, Q., Lurie, D., Vogelstein, J., Burns, R., Colcombe, S., Mennes, M., Kelly, C., Martino, A.D., Castellanos, F.X., Milham, M., 2013. Towards Automated Analysis of Connectomes: the Configurable Pipeline for the Analysis of Connectomes (c-pac), Frontier Neuroinformation 7, http://dx.doi.org/10.3389/conf.fninf.2013.09.00042.
15. Duyn, J., Spontaneous fMRI activity during resting wakefulness and sleep, Prog. Brain Res. 193 (2011) 295–305, [PubMed Central: PMC3535182] [ http://dx.doi.org/10.1016/B978-0-444-53839-0.00019-3] [PubMed:21854970].
16. Ehring, T., Tuschen-Caffier, B., Schnülle, J., Fischer, S., Gross, J.J., Emotion regulation and vulnerability to depression spontaneous versus instructed use of emotion suppression and reappraisal. Emotion 10:4 (2010), 563–572, 10.1037/a0019010.
17. Ehring, T., Zetsche, U., Weidacker, K., Wahl, K., Schönfeld, S., Ehlers, A., The perseverative thinking questionnaire (ptq) validation of a content-independent measure of repetitive negative thinking. J. Behav. Ther. Exp. Psychiatry 42:2 (2011), 225–232, 10.1016/j.jbtep.2010.12.003.
18. Eskildsen, S.F., Coupe, P., Fonov, V., Manjon, J.V., Leung, K.K., Guizard, N., Wassef, S.N., Ostergaard, L.R., Collins, D.L., Alzheimer's, I., Disease neuroimaging, beast brain extraction based on nonlocal segmentation technique. Neuroimage 59:3 (2012), 2362–2373, 10.1016/j.neuroimage.2011.09.012 http://www.ncbi.nlm.nih.gov/pubmed/21945694.
19. Filippini, N., MacIntosh, B.J., Hough, M.G., Goodwin, G.M., Frisoni, G.B., Smith, S.M., Matthews, P.M., Beckmann, C.F., Mackay, C.E., Distinct patterns of brain activity in young carriers of the apoe-epsilon4 allele. Proc. Natl. Acad. Sci USA 106:17 (2009), 7209–7214, 10.1073/pnas.0811879106.
20. First, M.B., Spitzer, R.L., Gibbon, M., Williams, J.B., 2002. Structured Clinical Interview for Dsm-iv-tr Axis I Disorders, Research Version, Non-patient Edition (scid-i/np), Report, Biometrics Research, New York State Psychiatric Institute.
21. Fox, M.D., Snyder, A.Z., Vincent, J.L., Corbetta, M., Van Essen, D.C., Raichle, M.E., The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proc. Natl. Acad. Sci. USA 102:27 (2005), 9673–9678, 10.1073/pnas.0504136102 http://www.ncbi.nlm.nih.gov/pubmed/15976020.
22. Friedman, L., Glover, G.H., Krenz, D., Magnotta, V., First, B., Reducing inter-scanner variability of activation in a multicenter fmri study role of smoothness equalization. Neuroimage 32:4 (2006), 1656–1668, 10.1016/j.neuroimage.2006.03.062 http://www.ncbi.nlm.nih.gov/pubmed/16875843.
23. Friston, K., Beyond phrenology what can neuroimaging tell us about distributed circuitry?. Annu. Rev. Neurosci. 25:1 (2002), 221–250, 10.1146/annurev.neuro.25.112701.142846.
24. Friston, K.J., Williams, S., Howard, R., Frackowiak, R.S., Turner, R., Movement-related effects in fmri time-series. Magn. Reson. Med. 35:3 (1996), 346–355 http://www.ncbi.nlm.nih.gov/pubmed/8699946.
25. Giannelli, M., Diciotti, S., Tessa, C., Mascalchi, M., Characterization of nyquist ghost in epi-fmri acquisition sequences effect of readout bandwidth and echo spacing implemented on two clinical 1.5 t mr scanner systems. J. Appl. Clin. Med. Phys., 11(4), 2010, 3237 http://www.ncbi.nlm.nih.gov/pubmed/21081879.
26. Gorgolewski, K.J., Auer, T., Calhoun, V.D., Craddock, R.C., Das, S., Duff, E.P., Flandin, G., Ghosh, S.S., Glatard, T., Halchenko, Y.O., Handwerker, D.A., Hanke, M., Keator, D., Li, X., Michael, Z., Maumet, C., Nichols, B.N., Nichols, T.E., Pellman, J., Poline, J.-B., Rokem, A., Schaefer, G., Sochat, V., Triplett, W., Turner, J.A., Varoquaux, G., Poldrack, R.A., The brain imaging data structure, a format for organizing and describing outputs of neuroimaging experiments. Sci. Data, 3, 2016, 160044, 10.1038/sdata.2016.44.
27. Gorgolewski, K., Burns, C.D., Madison, C., Clark, D., Halchenko, Y.O., Waskom, M.L., Ghosh, S.S., Nipype: A Flexible, Lightweight and Extensible Neuroimaging Data Processing Framework in Python, Frontier Neuroinformation 5, http://dx.doi.org/10.3389/fninf.2011.00013.
28. Greicius, M.D., Krasnow, B., Reiss, A.L., Menon, V., 2002. Functional connectivity in the resting brain: A network analysis of the default mode hypothesis, In: Proceedings of the National Academy of Sciences, vol. 100, 1, pp. 253–258, http://dx.doi.org/10.1073/pnas.0135058100.
29. Greve, D.N., Fischl, B., Accurate and robust brain image alignment using boundary-based registration. NeuroImage 48:1 (2009), 63–72, 10.1016/j.neuroimage.2009.06.060.
30. Griswold, M.A., Jakob, P.M., Heidemann, R.M., Nittka, M., Jellus, V., Wang, J., Kiefer, B., Haase, A., Generalized autocalibrating partially parallel acquisitions (grappa). Magn. Reson. Med. 47:6 (2002), 1202–1210, 10.1002/mrm.10171.
31. Gross, J.J., John, O.P., Individual differences in two emotion regulation processes: implications for affect, relationships, and well-being. J. Personal. Soc. Psychol. 85:2 (2003), 348–362, 10.1037/0022-3514.85.2.348.
32. Hamilton, J.P., Furman, D.J., Chang, C., Thomason, M.E., Dennis, E., Gotlib, I.H., Default-mode and task-positive network activity in major depressive disorder implications for adaptive and maladaptive rumination. Biol. Psychiatry 70:4 (2011), 327–333, 10.1016/j.biopsych.2011.02.003 http://www.ncbi.nlm.nih.gov/pubmed/21459364.
33. Harrison, B.J., Pujol, J., Lopez-Sola, M., Hernandez-Ribas, R., Deus, J., Ortiz, H., Soriano-Mas, C., Yucel, M., Pantelis, C., Cardoner, N., 2008. Consistency and functional specialization in the default mode brain network, In: Proceedings of the National Academy of Sciences, vol. 105, 28, pp. 9781–9786, http://dx.doi.org/10.1073/pnas.0711791105.
34. Huba, G.J., Aneshensel, C.S., Singer, J.L., Development of scales for three second-order factors of inner experience. Multivar. Behav. Res. 16:2 (1981), 181–206, 10.1207/s15327906mbr1602_4.
35. Insel, T., Cuthbert, B., Garvey, M., Heinssen, R., Pine, D.S., Quinn, K., Sanislow, C., Wang, P., Research domain criteria (rdoc) toward a new classification framework for research on mental disorders. Am. J. Psychiatry 167:7 (2010), 748–751, 10.1176/appi.ajp.2010.09091379.
36. Jenkinson, M., Smith, S., A global optimisation method for robust affine registration of brain images. Med. Image Anal. 5:2 (2001), 143–156 http://www.ncbi.nlm.nih.gov/pubmed/11516708.
37. Jenkinson, M., Bannister, P., Brady, M., Smith, S., Improved optimization for the robust and accurate linear registration and motion correction of brain images. Neuroimage 17:2 (2002), 825–841 http://www.ncbi.nlm.nih.gov/pubmed/12377157.
38. Jenkinson, M., 1999. Measuring Transformation Error by Rms Deviation. Internal technical report TR99MJ1, oxford centre for functional magnetic resonance imaging of the brain.
39. LaConte, S.M., Decoding fmri brain states in real-time. NeuroImage 56:2 (2011), 440–454, 10.1016/j.neuroimage.2010.06.052.
40. LaConte, S.M., Peltier, S.J., Hu, X.P., Real-time fmri using brain-state classification. Hum. Brain Mapp. 28:10 (2007), 1033–1044, 10.1002/hbm.20326.
41. LaConte, S.M., Strother, S.C., Cherkassky, V., Anderson, J., Hu, X., Support vector machines for temporal classification of block design fmri data. NeuroImage 26:2 (2005), 317–329, 10.1016/j.neuroimage.2005.01.048.
42. Larsen, R.J., Diener, E., Emmons, R.A., Affect intensity and reactions to daily life events. J. Personal. Social. Psychol. 51:4 (1986), 803–814, 10.1037/0022-3514.51.4.803.
43. Lund, T.E., Madsen, K.H., Sidaros, K., Luo, W.-L., Nichols, T.E., Non-white noise in fmri does modelling have an impact?. NeuroImage 29:1 (2006), 54–66, 10.1016/j.neuroimage.2005.07.005.
44. Magnotta, V.A., Friedman, L., First, B., Measurement of signal-to-noise and contrast-to-noise in the fbirn multicenter imaging study. J Digit. Imaging 19:2 (2006), 140–147, 10.1007/s10278-006-0264-x http://www.ncbi.nlm.nih.gov/pubmed/16598643.
45. Makris, N., Goldstein, J.M., Kennedy, D., Hodge, S.M., Caviness, V.S., Faraone, S.V., Tsuang, M.T., Seidman, L.J., Decreased volume of left and total anterior insular lobule in schizophrenia. Schizophr. Res. 83:2–3 (2006), 155–171, 10.1016/j.schres.2005.11.020 http://www.ncbi.nlm.nih.gov/pubmed/16448806.
46. Meyer, T.J., Miller, M.L., Metzger, R.L., Borkovec, T.D., Development and validation of the penn state worry questionnaire. Behav. Res Ther. 28:6 (1990), 487–495 http://www.ncbi.nlm.nih.gov/pubmed/2076086.
47. Mortamet, B., Bernstein, M.A., Jack, J., C. R., Gunter, J.L., Ward, C., Britson, P.J., Meuli, R., Thiran, J.P., Krueger, G., Alzheimer's, I., 2009. Disease neuroimaging, automatic quality assessment in structural brain magnetic resonance imaging, Magn Reson Med vol. 62, 2, pp. 365–72. http://dx.doi.org/10.1002/mrm.21992 URL 〈 http://www.ncbi.nlm.nih.gov/pubmed/19526493〉.
48. Mugler, J.P., Brookeman, J. R., 1990. Three-Dimensional Magnetization-prepared Rapid Gradient-echo Imaging (3d mp rage), Magn Reson Med, vol. 15, 1, pp. 152–7, URL 〈 http://www.ncbi.nlm.nih.gov/pubmed/2374495〉.
49. Nichols, T.E., 2012. Standardizing Dvars, URL 〈 http://blogs.warwick.ac.uk/nichols/entry/standardizing_dvars〉 ( accessed 16.08.16).
50. Nooner, K.B., Colcombe, S.J., Tobe, R.H., Mennes, M., Benedict, M.M., Moreno, A.L., Panek, L.J., Brown, S., Zavitz, S.T., Li, Q., Sikka, S., Gutman, D., Bangaru, S., Schlachter, R.T., Kamiel, S.M., Anwar, A.R., Hinz, C.M., Kaplan, M.S., Rachlin, A.B., Adelsberg, S., Cheung, B., Khanuja, R., Yan, C., Craddock, C.C., Calhoun, V., Courtney, W., King, M., Wood, D., Cox, C.L., Kelly, A.M.C., Martino, A.D., Petkova, E., Reiss, P.T., Duan, N., Thomsen, D., Biswal, B., Coffey, B., Hoptman, M.J., Javitt, D.C., Pomara, N., Sidtis, J.J., Koplewicz, H.S., Castellanos, F.X., Leventhal, B.L., Milham, M.P., 2012. The Nki-rockland Sample: A Model for Accelerating the Pace of Discovery Science in psychiatry, Frontiers Neuroscience 6, http://dx.doi.org/10.3389/fnins.2012.00152.
51. O. C., For Functional Mri of the Brain, Correspondence between Brainmap and Resting-fmri Ica Components, http://fsl.fmrib.ox.ac.uk/analysis/brainmap+rsns/ (accessed 07.10.16).
52. Pagnoni, G., Dynamical properties of bold activity from the ventral posteromedial cortex associated with meditation and attentional skills. J. Neurosci. 32:15 (2012), 5242–5249, 10.1523/JNEUROSCI.4135-11.2012.
53. Peirce, J.W., 2008. Generating Stimuli for Neuroscience Using Psychopy, Frontier. Neuroinformation 2, http://dx.doi.org/10.3389/neuro.11.010.2008.
54. Power, J.D., Barnes, K.A., Snyder, A.Z., Schlaggar, B.L., Petersen, S.E., Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. Neuroimage 59:3 (2012), 2142–2154.
55. Puccio, B., Pooley, J.P., Pellman, J.S., Taverna, E.C., Craddock, R.C., 2016. The Preprocessed Connectomes Project Repository of Manually Corrected Skull-stripped T1-weighted Anatomical Mri Data, Giga Science 5, 45 http://dx.doi.org/10.1186/s13742-016-0150-5.
56. Raichle, M.E., Snyder, A.Z., A default mode of brain function a brief history of an evolving idea. Neuroimage 37:4 (2007), 1083–1090, 10.1016/j.neuroimage.2007.02.041 (discussion 1097–9.) http://www.ncbi.nlm.nih.gov/pubmed/17719799.
57. Raichle, M.E., MacLeod, A.M., Snyder, A.Z., Powers, W.J., Gusnard, D.A., Shulman, G.L., A default mode of brain function. Proc. Natl. Acad. Sci. USA 98:2 (2001), 676–682, 10.1073/pnas.98.2.676 http://www.ncbi.nlm.nih.gov/pubmed/11209064.
58. Saad, Z.S., Reynolds, R.C., Jo, H.J., Gotts, S.J., Chen, G., Martin, A., Cox, R.W., Correcting brain-wide correlation differences in resting-state fmri. Brain Connect. 3:4 (2013), 339–352, 10.1089/brain.2013.0156 http://www.ncbi.nlm.nih.gov/pubmed/23705677.
59. Sahakian, B.J., Owen, A.M., Computerized assessment in neuropsychiatry using cantab discussion paper. J. R. Soc. Med. 85:7 (1992), 399–402 http://www.ncbi.nlm.nih.gov/pubmed/1629849.
60. Salimi-Khorshidi, G., Smith, S.M., Nichols, T.E., Adjusting the effect of nonstationarity in cluster-based and tfce inference. NeuroImage 54:3 (2011), 2006–2019, 10.1016/j.neuroimage.2010.09.088.
61. Scott, A., Courtney, W., Wood, D., de la Garza, R., Lane, S., King, M., Wang, R., Roberts, J., Turner, J.A., Calhoun, V.D., 2011. Coins: An innovative informatics and Neuroimaging Tool Suite Built for Large Heterogeneous Datasets, Frontiers Neuroinformation 5, http://dx.doi.org/10.3389/fninf.2011.00033.
62. Shehzad, Z., Giavasis, S., Li, Q., Benhajali, Y., Yan, C., Yang, Z., Milham, M., Bellec, P., Craddock, R.C., 2015. The preprocessed connectomes project quality assessment protocol - a resource for measuring the quality of mri data. Frontier Neuroscience 9, http://dx.doi.org/10.3389/conf.fnins.2015.91.00047.
63. Sheline, Y.I., Barch, D.M., Price, J.L., Rundle, M.M., Vaishnavi, S.N., Snyder, A.Z., Mintun, M.A., Wang, S., Coalson, R.S., Raichle, M.E., 2009. The default mode network and self-referential processes in depression, In: Proceedings of the National Academy of Sciences, vol. 106, 6 pp. 1942–1947, http://dx.doi.org/10.1073/pnas.0812686106.
64. Smith, S.M., Jenkinson, M., Woolrich, M.W., Beckmann, C.F., Behrens, T.E.J., Johansen-Berg, H., Bannister, P.R., Luca, M.D., Drobnjak, I., Flitney, D.E., Niazy, R.K., Saunders, J., Vickers, J., Zhang, Y., Stefano, N.D., Brady, J.M., Matthews, P.M., Advances in functional and structural mr image analysis and implementation as fsl. NeuroImage 23 (2004), S208–S219, 10.1016/j.neuroimage.2004.07.051.
65. 9 Smith, S.M., Fox, P.T., Miller, K.L., Glahn, D.C., Fox, P.M., Mackay, C.E., Filippini, N., Watkins, K.E., Toro, R., Laird, A.R., Beckmann, C.F., 2009. Correspondence of the brain's functional architecture during activation and rest, In: Proceedings of the National Academy of Sciences, vol. 106, 31, pp. 13040–13045. http://dx.doi.org/10.1073/pnas.0905267106.
66. Soldati, N., Calhoun, V.D., Bruzzone, L., Jovicich, J., 2013. The Use of a Priori Information in Ica-based Techniques for Real-time Fmri: an Evaluation of Static/dynamic and Spatial/temporal Characteristics, Frontiers in Human Neuroscience 7, http://dx.doi.org/10.3389/fnhum.2013.00064.
67. Stanislaw, H., Todorov, N., Calculation of signal detection theory measures. Behav. Res. Methods Instrum. Comput. 31:1 (1999), 137–149, 10.3758/bf03207704.
68. Stoeckel, L.E., Garrison, K.A., Ghosh, S., Wighton, P., Hanlon, C.A., Gilman, J.M., Greer, S., Turk-Browne, N.B., deBettencourt, M.T., Scheinost, D., Craddock, C., Thompson, T, Calderon, V., Bauer, C.C., George, M., Breiter, H.C., Whitfield-Gabrieli, S., Gabrieli, J.D., LaConte, S.M., Hirshberg, L., Brewer, J.A., Hampson, M., Van Der Kouwe, A., Mackey, S., Evins, A.E., Optimizing real time fmri neurofeedback for therapeutic discovery and development. Neuroimage Clin. 5 (2014), 245–255, 10.1016/j.nicl.2014.07.002 http://www.ncbi.nlm.nih.gov/pubmed/25161891.
69. Straw, A.D., Vision egg: An Open-Source Library for Realtime Visual Stimulus Generation, Frontier Neuroinformation 2, http://dx.doi.org/10.3389/neuro.11.004.2008.
70. Sylvester, C.M., Corbetta, M., Raichle, M.E., Rodebaugh, T.L., Schlaggar, B.L., Sheline, Y.I., Zorumski, C.F., Lenze, E.J., Functional network dysfunction in anxiety and anxiety disorders. Trends Neurosci. 35:9 (2012), 527–535, 10.1016/j.tins.2012.04.012.
71. Tagliazucchi, E., Laufs, H., Decoding wakefulness levels from typical fmri resting-state data reveals reliable drifts between wakefulness and sleep. Neuron 82:3 (2014), 695–708, 10.1016/j.neuron.2014.03.020 http://www.ncbi.nlm.nih.gov/pubmed/24811386.
72. Treynor, W., Gonzalez, R., Nolen-Hoeksema, S., Rumination reconsidered a psychometric analysis. Cogn. Ther. Res. 27:3 (2003), 247–259, 10.1023/a:1023910315561.
73. Turner, D.C., Robbins, T.W., Clark, L., Aron, A.R., Dowson, J., Sahakian, B.J., Cognitive enhancing effects of modafinil in healthy volunteers. Psychopharmacol. (Berl.) 165:3 (2003), 260–269, 10.1007/s00213-002-1250-8 http://www.ncbi.nlm.nih.gov/pubmed/12417966.
74. United States Census Bureau, Rockland county, URL 〈 http://www.census.gov/quickfacts/table/PST045215/36087,00〉 ( accessed 21.07.16).
75. Watson, D., Clark, L.A., Tellegen, A., Development and validation of brief measures of positive and negative affect the panas scales. J. Personal. Soc. Psychol. 54:6 (1988), 1063–1070, 10.1037//0022-3514.54.6.1063.
76. Whitfield-Gabrieli, S., Ford, J.M., Default mode network activity and connectivity in psychopathology. Annu. Rev. Clin. Psychol. 8:1 (2012), 49–76, 10.1146/annurev-clinpsy-032511-143049.
77. Wood, D., King, M., Landis, D., Courtney, W., Wang, R., Kelly, R., Turner, J.A., Calhoun, V.D., 2014. Harnessing Modern Web Application Technology to Create Intuitive and Efficient Data Visualization and Sharing Tools, Frontiers Neuroinformation 8, http://dx.doi.org/10.3389/fninf.2014.00071.
78. Yan, C.G., Cheung, B., Kelly, C., Colcombe, S., Craddock, R.C., Di Martino, A., Li, Q., Zuo, X.N., Castellanos, F.X., Milham, M.P., A comprehensive assessment of regional variation in the impact of head micromovements on functional connectomics. Neuroimage 76 (2013), 183–201.
79. Zhang, Y., Brady, M., Smith, S., Segmentation of brain mr images through a hidden markov random field model and the expectation-maximization algorithm. IEEE Trans. Med. Imaging 20:1 (2001), 45–57, 10.1109/42.906424.
80. Zuo, X.-N., Anderson, J.S., Bellec, P., Birn, R.M., Biswal, B.B., Blautzik, J., Breitner, J.C.S., Buckner, R.L., Calhoun, V.D., Castellanos, F.X., Chen, A., Chen, B., Chen, J., Chen, X., Colcombe, S.J., Courtney, W., Craddock, R.C., Martino, A.D., Dong, H.-M., Fu, X., Gong, Q., Gorgolewski, K.J., Han, Y., He, Y., He, Y., Ho, E., Holmes, A., Hou, X.-H., Huckins, J., Jiang, T., Jiang, Y., Kelley, W., Kelly, C., King, M., LaConte, S.M., Lainhart, J.E., Lei, X., Li, H.-J., Li, K., Li, K., Lin, Q., Liu, D., Liu, J., Liu, X., Liu, Y., Lu, G., Lu, J., Luna, B., Luo, J., Lurie, D., Mao, Y., Margulies, D.S., Mayer, A.R., Meindl, T., Meyerand, M.E., Nan, W., Nielsen, J.A., O'Connor, D., Paulsen, D., Prabhakaran, V., Qi, Z., Qiu, J., Shao, C., Shehzad, Z., Tang, W., Villringer, A., Wang, H., Wang, K., Wei, D., Wei, G.-X., Weng, X.-C., Wu, X., Xu, T., Yang, N., Yang, Z., Zang, Y.-F., Zhang, L., Zhang, Q., Zhang, Z., Zhang, Z., Zhao, K., Zhen, Z., Zhou, Y., Zhu, X.-T., Milham, M.P., An open science resource for establishing reliability and reproducibility in functional connectomics. Sci. Data, 1, 2014, 140049, 10.1038/sdata.2014.49.