-
1
-
-
84926500488
-
Electrophysiological signatures of spontaneous BOLD fluctuations in macaque prefrontal cortex
-
Hutchison RM, Hashemi N, Gati JS, Menon RS, Everling S, Electrophysiological signatures of spontaneous BOLD fluctuations in macaque prefrontal cortex. NeuroImage. Elsevier Inc. 2015;113: 257–267. doi: 10.1016/j.neuroimage.2015.03.062
-
(2015)
NeuroImage. Elsevier Inc
, vol.113
, pp. 257-267
-
-
Hutchison, R.M.1
Hashemi, N.2
Gati, J.S.3
Menon, R.S.4
Everling, S.5
-
2
-
-
84893550211
-
Dynamic changes of spatial functional network connectivity in healthy individuals and schizophrenia patients using independent vector analysis
-
24418507
-
Ma S, Calhoun VD, Phlypo R, Adali T, Dynamic changes of spatial functional network connectivity in healthy individuals and schizophrenia patients using independent vector analysis. NeuroImage. 2014;90: 196–206. doi: 10.1016/j.neuroimage.2013.12.063 24418507
-
(2014)
NeuroImage
, vol.90
, pp. 196-206
-
-
Ma, S.1
Calhoun, V.D.2
Phlypo, R.3
Adali, T.4
-
3
-
-
84951336011
-
Dynamic Resting-State Functional Connectivity in Major Depression
-
Kaiser RH, Whitfield-Gabrieli S, Dillon DG, Goer F, Beltzer M, Minkel J, et al. Dynamic Resting-State Functional Connectivity in Major Depression. Neuropsychopharmacology. Nature Publishing Group; 2015; 1–9. doi: 10.1038/npp.2015.352
-
(2015)
Neuropsychopharmacology. Nature Publishing Group
, pp. 1-9
-
-
Kaiser, R.H.1
Whitfield-Gabrieli, S.2
Dillon, D.G.3
Goer, F.4
Beltzer, M.5
Minkel, J.6
-
4
-
-
85016713887
-
Positive affect, surprise, and fatigue are correlates of network flexibility
-
Betzel RF, Satterthwaite TD, Gold JI, Bassett DS, Positive affect, surprise, and fatigue are correlates of network flexibility. Scientific Reports. Springer US; 2017;7: 520. doi: 10.1038/s41598-017-00425-z
-
(2017)
Scientific Reports. Springer US
, vol.7
, pp. 520
-
-
Betzel, R.F.1
Satterthwaite, T.D.2
Gold, J.I.3
Bassett, D.S.4
-
5
-
-
85019550640
-
Dynamic Brain Network Correlates of Spontaneous Fluctuations in Attention
-
Kucyi A, Hove MJ, Esterman M, Hutchison RM, Valera EM, Dynamic Brain Network Correlates of Spontaneous Fluctuations in Attention. Cerebral cortex (New York, NY: 1991). 2016; bhw029. doi: 10.1093/cercor/bhw029
-
(2016)
Cerebral cortex (New York, NY: 1991)
, pp. bhw029
-
-
Kucyi, A.1
Hove, M.J.2
Esterman, M.3
Hutchison, R.M.4
Valera, E.M.5
-
6
-
-
84941636185
-
Signature of consciousness in the dynamics of resting-state brain activity
-
Barttfeld P, Uhrig L, Sitt JD, Sigman M, Jarraya B, Dehaene S, et al., Signature of consciousness in the dynamics of resting-state brain activity. Proceedings of the National Academy of Sciences. 2015;112: E5219–E5220. doi: 10.1073/pnas.1515029112
-
(2015)
Proceedings of the National Academy of Sciences
, vol.112
, pp. E5219-E5220
-
-
Barttfeld, P.1
Uhrig, L.2
Sitt, J.D.3
Sigman, M.4
Jarraya, B.5
Dehaene, S.6
-
7
-
-
85003856211
-
On Stabilizing the Variance of Dynamic Functional Brain Connectivity Time Series
-
27784176
-
Thompson WH, Fransson P, On Stabilizing the Variance of Dynamic Functional Brain Connectivity Time Series. Brain Connectivity. 2016;6: 735–746. doi: 10.1089/brain.2016.0454 27784176
-
(2016)
Brain Connectivity
, vol.6
, pp. 735-746
-
-
Thompson, W.H.1
Fransson, P.2
-
8
-
-
85077175640
-
From static to temporal network theory—applications to functional brain connectivity
-
Thompson WH, Brantefors P, Fransson P, From static to temporal network theory—applications to functional brain connectivity. Network Neruoscience. 2017;1: 69–99. doi: 10.1162/NETN_a_00011
-
(2017)
Network Neruoscience
, vol.1
, pp. 69-99
-
-
Thompson, W.H.1
Brantefors, P.2
Fransson, P.3
-
9
-
-
84953307193
-
Dynamic fluctuations coincide with periods of high and low modularity in resting-state functional brain networks
-
26687667
-
Betzel RF, Fukushima M, He Y, Zuo XN, Sporns O, Dynamic fluctuations coincide with periods of high and low modularity in resting-state functional brain networks. NeuroImage. 2016;127: 287–297. doi: 10.1016/j.neuroimage.2015.12.001 26687667
-
(2016)
NeuroImage
, vol.127
, pp. 287-297
-
-
Betzel, R.F.1
Fukushima, M.2
He, Y.3
Zuo, X.N.4
Sporns, O.5
-
10
-
-
84937391519
-
The mean–variance relationship reveals two possible strategies for dynamic brain connectivity analysis in fMRI
-
Thompson WH, Fransson P, The mean–variance relationship reveals two possible strategies for dynamic brain connectivity analysis in fMRI. Frontiers in Human Neuroscience. 2015;9: 1–7. doi: 10.3389/fnhum.2015.00398
-
(2015)
Frontiers in Human Neuroscience
, vol.9
, pp. 1-7
-
-
Thompson, W.H.1
Fransson, P.2
-
11
-
-
85006333189
-
Bursty properties revealed in large-scale brain networks with a point-based method for dynamic functional connectivity
-
Thompson WH, Fransson P, Bursty properties revealed in large-scale brain networks with a point-based method for dynamic functional connectivity. Scientific Reports. Nature Publishing Group; 2016;6: 39156. doi: 10.1038/srep39156
-
(2016)
Scientific Reports. Nature Publishing Group
, vol.6
, pp. 39156
-
-
Thompson, W.H.1
Fransson, P.2
-
12
-
-
85030163732
-
On the Stability of BOLD fMRI Correlations
-
Laumann TO, Snyder AZ, Mitra A, Gordon EM, Gratton C, Adeyemo B, et al. On the Stability of BOLD fMRI Correlations. Cerebral Cortex. 2016; 1–14. doi: 10.1093/cercor/bhw265
-
(2016)
Cerebral Cortex
, pp. 1-14
-
-
Laumann, T.O.1
Snyder, A.Z.2
Mitra, A.3
Gordon, E.M.4
Gratton, C.5
Adeyemo, B.6
-
13
-
-
84929712322
-
Towards a statistical test for functional connectivity dynamics
-
Zalesky A, Breakspear M, Towards a statistical test for functional connectivity dynamics. NeuroImage. Elsevier Inc. 2015;114: 466–470. doi: 10.1016/j.neuroimage.2015.03.047
-
(2015)
NeuroImage. Elsevier Inc
, vol.114
, pp. 466-470
-
-
Zalesky, A.1
Breakspear, M.2
-
14
-
-
84952892201
-
Can sliding-window correlations reveal dynamic functional connectivity in resting-state fMRI?
-
Hindriks R, Adhikari MH, Murayama Y, Ganzetti M, Mantini D, Logothetis NK, et al. Can sliding-window correlations reveal dynamic functional connectivity in resting-state fMRI?NeuroImage. The Authors; 2016;127: 242–256. doi: 10.1016/j.neuroimage.2015.11.055
-
(2016)
NeuroImage. The Authors
, vol.127
, pp. 242-256
-
-
Hindriks, R.1
Adhikari, M.H.2
Murayama, Y.3
Ganzetti, M.4
Mantini, D.5
Logothetis, N.K.6
-
15
-
-
84894232779
-
Tracking whole-brain connectivity dynamics in the resting state
-
23146964
-
Allen EA, Damaraju E, Plis SM, Erhardt EB, Eichele T, Calhoun VD, Tracking whole-brain connectivity dynamics in the resting state. Cerebral Cortex. 2014;24: 663–676. doi: 10.1093/cercor/bhs352 23146964
-
(2014)
Cerebral Cortex
, vol.24
, pp. 663-676
-
-
Allen, E.A.1
Damaraju, E.2
Plis, S.M.3
Erhardt, E.B.4
Eichele, T.5
Calhoun, V.D.6
-
16
-
-
84940528665
-
Estimation of dynamic functional connectivity using Multiplication of Temporal Derivatives
-
Shine JM, Koyejo O, Bell PT, Gorgolewski KJ, Gilat M, Poldrack RA, Estimation of dynamic functional connectivity using Multiplication of Temporal Derivatives. NeuroImage. Elsevier Inc. 2015;122: 399–407. doi: 10.1016/j.neuroimage.2015.07.064
-
(2015)
NeuroImage. Elsevier Inc
, vol.122
, pp. 399-407
-
-
Shine, J.M.1
Koyejo, O.2
Bell, P.T.3
Gorgolewski, K.J.4
Gilat, M.5
Poldrack, R.A.6
-
17
-
-
84875045497
-
Time-varying functional network information extracted from brief instances of spontaneous brain activity
-
23440216
-
Liu X, Duyn JH, Time-varying functional network information extracted from brief instances of spontaneous brain activity. Proceedings of the National Academy of Sciences of the United States of America. 2013;110: 4392–7. doi: 10.1073/pnas.1216856110 23440216
-
(2013)
Proceedings of the National Academy of Sciences of the United States of America
, vol.110
, pp. 4392-4397
-
-
Liu, X.1
Duyn, J.H.2
-
18
-
-
84886441779
-
Principal components of functional connectivity: a new approach to study dynamic brain connectivity during rest
-
Leonardi N, Richiardi J, Gschwind M, Simioni S, Annoni J-M, Schluep M, et al. Principal components of functional connectivity: a new approach to study dynamic brain connectivity during rest. NeuroImage. Elsevier Inc. 2013;83: 937–50. doi: 10.1016/j.neuroimage.2013.07.019
-
(2013)
NeuroImage. Elsevier Inc
, vol.83
, pp. 937-950
-
-
Leonardi, N.1
Richiardi, J.2
Gschwind, M.3
Simioni, S.4
Annoni, J.-M.5
Schluep, M.6
-
19
-
-
84866296479
-
Criticality in large-scale brain FMRI dynamics unveiled by a novel point process analysis
-
22347863
-
Tagliazucchi E, Balenzuela P, Fraiman D, Chialvo DR, Criticality in large-scale brain FMRI dynamics unveiled by a novel point process analysis. Frontiers in physiology. 2012;3: 15. doi: 10.3389/fphys.2012.00015 22347863
-
(2012)
Frontiers in physiology
, vol.3
, pp. 15
-
-
Tagliazucchi, E.1
Balenzuela, P.2
Fraiman, D.3
Chialvo, D.R.4
-
20
-
-
84988369308
-
The Voxel-Wise Functional Connectome Can Be Efficiently Derived from Co-activations in a Sparse Spatio-Temporal Point-Process
-
Tagliazucchi E, Siniatchkin M, Laufs H, Chialvo DR, The Voxel-Wise Functional Connectome Can Be Efficiently Derived from Co-activations in a Sparse Spatio-Temporal Point-Process. Frontiers in Neuroscience. 2016;10: 1–13. doi: 10.3389/fnins.2016.00381
-
(2016)
Frontiers in Neuroscience
, vol.10
, pp. 1-13
-
-
Tagliazucchi, E.1
Siniatchkin, M.2
Laufs, H.3
Chialvo, D.R.4
-
21
-
-
79955476785
-
Characterizing dynamic functional connectivity in the resting brain using variable parameter regression and Kalman filtering approaches
-
Kang J, Wang L, Yan C, Wang J, Liang X, He Y, Characterizing dynamic functional connectivity in the resting brain using variable parameter regression and Kalman filtering approaches. NeuroImage. Elsevier Inc. 2011;56: 1222–1234. doi: 10.1016/j.neuroimage.2011.03.033
-
(2011)
NeuroImage. Elsevier Inc
, vol.56
, pp. 1222-1234
-
-
Kang, J.1
Wang, L.2
Yan, C.3
Wang, J.4
Liang, X.5
He, Y.6
-
22
-
-
84946893707
-
State space modeling of time-varying contemporaneous and lagged relations in connectivity maps
-
Molenaar PCM, Beltz AM, Gates KM, Wilson SJ, State space modeling of time-varying contemporaneous and lagged relations in connectivity maps. NeuroImage. Elsevier B.V. 2016;125: 791–802. doi: 10.1016/j.neuroimage.2015.10.088
-
(2016)
NeuroImage. Elsevier B.V
, vol.125
, pp. 791-802
-
-
Molenaar, P.C.M.1
Beltz, A.M.2
Gates, K.M.3
Wilson, S.J.4
-
23
-
-
84964698383
-
DynamicBC: A MATLAB Toolbox for Dynamic Brain Connectome Analysis
-
25083734
-
Liao W, Wu G-R, Xu Q, Ji G-J, Zhang Z, Zang Y-F, et al. DynamicBC: A MATLAB Toolbox for Dynamic Brain Connectome Analysis. Brain Connectivity. 2014;4: 780–790. doi: 10.1089/brain.2014.0253 25083734
-
(2014)
Brain Connectivity
, vol.4
, pp. 780-790
-
-
Liao, W.1
Wu, G.-R.2
Xu, Q.3
Ji, G.-J.4
Zhang, Z.5
Zang, Y.-F.6
-
24
-
-
84863115584
-
Temporally-independent functional modes of spontaneous brain activity
-
22323591
-
Smith SM, Miller KL, Moeller S, Xu J, Auerbach EJ, Woolrich MW, et al. Temporally-independent functional modes of spontaneous brain activity. Proceedings of the National Academy of Sciences of the United States of America. 2012;109: 3131–6. doi: 10.1073/pnas.1121329109 22323591
-
(2012)
Proceedings of the National Academy of Sciences of the United States of America
, vol.109
, pp. 3131-3136
-
-
Smith, S.M.1
Miller, K.L.2
Moeller, S.3
Xu, J.4
Auerbach, E.J.5
Woolrich, M.W.6
-
25
-
-
84870997831
-
A sliding time-window ICA reveals spatial variability of the default mode network in time
-
22432423
-
Kiviniemi V, Vire T, Remes J, Elseoud AA, Starck T, Tervonen O, et al. A sliding time-window ICA reveals spatial variability of the default mode network in time. Brain connectivity. 2011;1: 339–47. doi: 10.1089/brain.2011.0036 22432423
-
(2011)
Brain connectivity
, vol.1
, pp. 339-347
-
-
Kiviniemi, V.1
Vire, T.2
Remes, J.3
Elseoud, A.A.4
Starck, T.5
Tervonen, O.6
-
26
-
-
84907022675
-
Evaluating dynamic bivariate correlations in resting-state fMRI: A comparison study and a new approach
-
Lindquist MA, Xu Y, Nebel MB, Caffo BS, Evaluating dynamic bivariate correlations in resting-state fMRI: A comparison study and a new approach. NeuroImage. Elsevier Inc. 2014;101: 531–546. doi: 10.1016/j.neuroimage.2014.06.052
-
(2014)
NeuroImage. Elsevier Inc
, vol.101
, pp. 531-546
-
-
Lindquist, M.A.1
Xu, Y.2
Nebel, M.B.3
Caffo, B.S.4
-
27
-
-
85012109002
-
Cortical rich club regions can organize state-dependent functional network formation by engaging in oscillatory behavior
-
Senden M, Reuter N, van den Heuvel MP, Goebel R, Deco G, Cortical rich club regions can organize state-dependent functional network formation by engaging in oscillatory behavior. NeuroImage. Elsevier; 2017;146: 561–574. doi: 10.1016/j.neuroimage.2016.10.044
-
(2017)
NeuroImage. Elsevier
, vol.146
, pp. 561-574
-
-
Senden, M.1
Reuter, N.2
van den Heuvel, M.P.3
Goebel, R.4
Deco, G.5
-
28
-
-
84938742391
-
Characterizing and Differentiating Brain State Dynamics via Hidden Markov Models
-
25331991
-
Ou J, Xie L, Jin C, Li X, Zhu D, Jiang R, et al. Characterizing and Differentiating Brain State Dynamics via Hidden Markov Models. Brain Topography. 2015;28: 666–679. doi: 10.1007/s10548-014-0406-2 25331991
-
(2015)
Brain Topography
, vol.28
, pp. 666-679
-
-
Ou, J.1
Xie, L.2
Jin, C.3
Li, X.4
Zhu, D.5
Jiang, R.6
-
29
-
-
85007574013
-
Temporal Dynamics and Developmental Maturation of Salience, Default and Central-Executive Network Interactions Revealed by Variational Bayes Hidden Markov Modeling
-
27959921
-
Ryali S, Supekar K, Chen T, Kochalka J, Cai W, Nicholas J, et al. Temporal Dynamics and Developmental Maturation of Salience, Default and Central-Executive Network Interactions Revealed by Variational Bayes Hidden Markov Modeling. PLOS Computational Biology. 2016;12: e1005138. doi: 10.1371/journal.pcbi.1005138 27959921
-
(2016)
PLOS Computational Biology
, vol.12
, pp. e1005138
-
-
Ryali, S.1
Supekar, K.2
Chen, T.3
Kochalka, J.4
Cai, W.5
Nicholas, J.6
-
33
-
-
34247493236
-
Matplotlib: A 2D graphics environment
-
Hunter JD, Matplotlib: A 2D graphics environment. Computing in Science and Engineering. 2007;9: 99–104. doi: 10.1109/MCSE.2007.55
-
(2007)
Computing in Science and Engineering
, vol.9
, pp. 99-104
-
-
Hunter, J.D.1
-
34
-
-
85006481322
-
-
Waskom M, Botvinnik O, Drewokane, Hobson P, David, Halchenko Y, et al. (June 2016). Zenodo
-
Waskom M, Botvinnik O, Drewokane, Hobson P, David, Halchenko Y, et al. seaborn: v0.7.1 (June 2016). doiorg. Zenodo;
-
(2016)
seaborn: v0.7.1
-
-
-
35
-
-
84926317380
-
On spurious and real fluctuations of dynamic functional connectivity during rest
-
Leonardi N, Van De Ville D, On spurious and real fluctuations of dynamic functional connectivity during rest. NeuroImage. Elsevier Inc. 2015;104: 430–436. doi: 10.1016/j.neuroimage.2014.09.007
-
(2015)
NeuroImage. Elsevier Inc
, vol.104
, pp. 430-436
-
-
Leonardi, N.1
Van De Ville, D.2
-
36
-
-
85040453272
-
A common framework for the problem of deriving estimates of dynamic functional brain connectivity
-
Thompson WH, Fransson P, A common framework for the problem of deriving estimates of dynamic functional brain connectivity. NeuroImage. Elsevier Ltd; 2018;172: 896–902. doi: 10.1016/j.neuroimage.2017.12.057
-
(2018)
NeuroImage. Elsevier Ltd
, vol.172
, pp. 896-902
-
-
Thompson, W.H.1
Fransson, P.2
-
37
-
-
84929702956
-
A jackknife approach to quantifying single-trial correlation between covariance-based metrics undefined on a single-trial basis
-
Richter CG, Thompson WH, Bosman CA, Fries P, A jackknife approach to quantifying single-trial correlation between covariance-based metrics undefined on a single-trial basis. NeuroImage. Elsevier B.V. 2015;114: 57–70. doi: 10.1016/j.neuroimage.2015.04.040
-
(2015)
NeuroImage. Elsevier B.V
, vol.114
, pp. 57-70
-
-
Richter, C.G.1
Thompson, W.H.2
Bosman, C.A.3
Fries, P.4
-
38
-
-
84901687683
-
The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo
-
Hoffman M, Gelman A, The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo. Journal of Machine Learning Research. 2014;15: 30.
-
(2014)
Journal of Machine Learning Research
, vol.15
, pp. 30
-
-
Hoffman, M.1
Gelman, A.2
-
39
-
-
84876235301
-
A Widely Applicable Bayesian Information Criterion
-
.;: –. Available:
-
Watanabe S, A Widely Applicable Bayesian Information Criterion. Journal of Machine Learning Research. 2013;14: 867–897. Available: http://arxiv.org/abs/1208.6338
-
(2013)
Journal of Machine Learning Research
, vol.14
, pp. 867-897
-
-
Watanabe, S.1
-
40
-
-
4344705249
-
Statistical parametric maps in functional imaging: A general linear approach
-
Friston KJ, Holmes aP, Worsley KJ, Poline J-P, Frith CD, Frackowiak RSJ, Statistical parametric maps in functional imaging: A general linear approach. Human Brain Mapping. 1995;2: 189–210. doi: 10.1002/hbm.460020402
-
(1995)
Human Brain Mapping
, vol.2
, pp. 189-210
-
-
Friston, K.J.1
Holmes, A.2
Worsley, K.J.3
Poline, J.-P.4
Frith, C.D.5
Frackowiak, R.S.J.6
-
41
-
-
84961788993
-
Evaluation of sliding window correlation performance for characterizing dynamic functional connectivity and brain states
-
26952197
-
Shakil S, Lee CH, Keilholz SD, Evaluation of sliding window correlation performance for characterizing dynamic functional connectivity and brain states. NeuroImage. 2016;133: 111–128. doi: 10.1016/j.neuroimage.2016.02.074 26952197
-
(2016)
NeuroImage
, vol.133
, pp. 111-128
-
-
Shakil, S.1
Lee, C.H.2
Keilholz, S.D.3
|