Distant brain regions are organized into large-scale functional networks specialized for specific cognitive processes. The brain’s functional-network architecture and its development can be investigated using functional connectivity MRI (fcMRI), which measures correlations in spontaneous fluctuations of brain activity. fcMRI studies have provided important insights into typical brain organization and development, as well as insights into the atypical organization of the brain in neuropsychiatric disorders. fcMRI data can be easily collected and carry much information. Therefore, they are now being analyzed using powerful multivariate-pattern-analysis (MVPA) methods, with the goal of one day being able to diagnose disease states in individuals. However, great care must be taken during these analyses to eliminate confounds such as head movement.
BarnesK. A.NelsonS. M.CohenA. L.PowerJ. D.CoalsonR. S.MiezinF. M.. . . & SchlaggarB. L. (2012). Parcellation in left lateral parietal cortex is similar in adults and children. Cerebral Cortex, 22, 1148–1158.
BiswalB.YetkinF. Z.HaughtonV. M.HydeJ. S. (1995). Functional connectivity in the motor cortex of resting human brain using echo-planar MRI. Magnetic Resonance in Medicine, 34, 537–541.
4.
BrayS.ChangC.HoeftF. (2009). Applications of multivariate pattern classification analyses in developmental neuroimaging of healthy and clinical populations. Frontiers in Human Neuroscience, 3, Article 32.
5.
ChurchJ. A.PetersenS. E.SchlaggarB. L. (2010). The “Task B problem” and other considerations in developmental functional neuroimaging. Human Brain Mapping, 31, 852–862.
6.
CohenA. L.FairD. A.DosenbachN. U. F.MiezinF. M.DierkerD.Van EssenD. C.. . . & PetersenS. E. (2008). Defining functional areas in individual human brains using resting functional connectivity MRI. NeuroImage, 41, 45–57.
7.
DosenbachN. U. F.FairD. A.CohenA. L.SchlaggarB. L.PetersenS. E. (2008). A dual-networks architecture of top-down control. Trends in Cognitive Sciences, 12, 99–105.
8.
DosenbachN. U. F.FairD. A.MiezinF. M.CohenA. L.WengerK. K.DosenbachR. A.. . . & PetersenS. E. (2007). Distinct brain networks for adaptive and stable task control in humans. Proceedings of the National Academy of Sciences, USA, 104, 11073–11078.
9.
DosenbachN. U. F.NardosB.CohenA. L.FairD. A.PowerJ. D.ChurchJ. A.. . . & SchlaggarB. L. (2010). Prediction of individual brain maturity using fMRI. Science, 329, 1358–1361.
10.
DosenbachN. U. F.VisscherK. M.PalmerE. D.MiezinF. M.WengerK. K.KangH. C.. . . & PetersenS. E. (2006). A core system for the implementation of task sets. Neuron, 50, 799–812.
11.
EckerC.MarquandA.Mourao-MirandaJ.JohnstonP.DalyE. M.BrammerM. J.. . . & MurphyD. G. M. (2010). Describing the brain in autism in five dimensions—Magnetic resonance imaging-assisted diagnosis of autism spectrum disorder using a multiparameter classification approach. Journal of Neuroscience, 30, 10612–10623.
12.
FairD. A.BathulaD.NikolasM. A.NiggJ. T. (2012). Distinct neuropsychological subgroups in typically developing youth inform heterogeneity in children with ADHD. Proceedings of the National Academy of Sciences, USA, 109, 6769–6774.
FairD. A.DosenbachN. U. F.ChurchJ. A.CohenA. L.BrahmbhattS.MiezinF. M.. . . & SchlaggarB. L. (2007). Development of distinct control networks through segregation and integration. Proceedings of the National Academy of Sciences, USA, 104, 13507–13512.
15.
FairD. A.NiggJ. T.IyerS.BathulaD.MillsK. L.DosenbachN. U. F.. (2013). Distinct neural signatures detected for ADHD subtypes after controlling for micro-movements in resting state functional connectivity MRI data. Frontiers in Systems Neuroscience, 6, Article 90.
16.
FoxM. D.SnyderA. Z.VincentJ. L.CorbettaM.Van EssenD. C.RaichleM. E. (2005). The human brain is intrinsically organized into dynamic, anticorrelated functional networks. Proceedings of the National Academy of Sciences, USA, 102, 9673–9678.
17.
GreiciusM. D.KrasnowB.ReissA. L.MenonV. (2003). Functional connectivity in the resting brain: A network analysis of the default mode hypothesis. Proceedings of the National Academy of Sciences, USA, 100, 253–258.
18.
HagmannP.GrantP. E.FairD. A. (2012). MR connectomics: A conceptual framework for studying the developing brain. Frontiers in Systems Neuroscience, 6, Article 43.
19.
HaxbyJ. V.GobbiniM. I.FureyM. L.IshaiA.SchoutenJ. L.PietriniP. (2001). Distributed and overlapping representations of faces and objects in ventral temporal cortex. Science, 293, 2425–2430.
20.
LewisC. M.BaldassarreA.CommitteriG.RomaniG. L.CorbettaM. (2009). Learning sculpts the spontaneous activity of the resting human brain. Proceedings of the National Academy of Sciences, USA, 106, 17558–17563.
21.
MitchellT. M.ShinkarevaS. V.CarlsonA.ChangK. M.MalaveV. L.MasonR. A.JustM. A. (2008). Predicting human brain activity associated with the meanings of nouns. Science, 320, 1191–1195.
22.
NelsonS. M.CohenA. L.PowerJ. D.WigG. S.MiezinF. M.WheelerM. E.PetersenS. E. (2010). A parcellation scheme for human left lateral parietal cortex. Neuron, 67, 156–170.
23.
NormanK. A.PolynS. M.DetreG. J.HaxbyJ. V. (2006). Beyond mind-reading: Multi-voxel pattern analysis of fMRI data. Trends in Cognitive Sciences, 10, 424–430.
24.
PereiraF.MitchellT.BotvinickM. (2009). Machine learning classifiers and fMRI: A tutorial overview. NeuroImage, 45, S199–S209.
25.
PetersenS. E.PosnerM. I. (2012). The attention system of the human brain: 20 years after. Annual Review of Neuroscience, 35, 73–89.
26.
PizoliC. E.ShahM. N.SnyderA. Z.ShimonyJ. S.LimbrickD. D.RaichleM. E.. . . & SmythM. D. (2011). Resting-state activity in development and maintenance of normal brain function. Proceedings of the National Academy of Sciences, USA, 108, 11638–11643.
27.
PosnerM. I.PetersenS. E. (1990). The attention system of the human brain. Annual Review of Neuroscience, 13, 25–42.
28.
PowerJ. D.BarnesK. A.SnyderA. Z.SchlaggarB. L.PetersenS. E. (2012a). Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. NeuroImage, 59, 2142–2154.
29.
PowerJ. D.BarnesK. A.SnyderA. Z.SchlaggarB. L.PetersenS. E. (2012b). Steps toward optimizing motion artifact removal in functional connectivity MRI; a reply to Carp. NeuroImage. Advance online publication. Retrieved from http://www.sciencedirect.com/science/article/pii/S105381191200290X
30.
PowerJ. D.CohenA. L.NelsonS. M.WigG. S.BarnesK. A.ChurchJ. A.PetersenS. E. (2011). Functional network organization of the human brain. Neuron, 72, 665–678.
31.
SatterthwaiteT. D.WolfD. H.LougheadJ.RuparelK.ElliottM. A.HakonarsonH.GurR. E. (2012). Impact of in-scanner head motion on multiple measures of functional connectivity: Relevance for studies of neurodevelopment in youth. NeuroImage, 60, 623–632.
32.
SchlaggarB. L.BrownT. T.LugarH. M.VisscherK. M.MiezinF. M.PetersenS. E. (2002). Functional neuroanatomical differences between adults and school-age children in the processing of single words. Science, 296, 1476–1479.
33.
ShehzadZ.KellyA. M. C.ReissP. T.GeeD. G.GotimerK.UddinL. Q.MilhamM. P. (2009). The resting brain: Unconstrained yet reliable. Cerebral Cortex, 19, 2209–2229.
34.
ShmuelA.LeopoldD. A. (2008). Neuronal correlates of spontaneous fluctuations in fMRI signals in monkey visual cortex: Implications for functional connectivity at rest. Human Brain Mapping, 29, 751–761.
35.
SnyderA. Z.RaichleM. E. (2012). A brief history of the resting state: The Washington University perspective. NeuroImage, 62, 902–910.
36.
SomervilleL. H.CaseyB. J. (2010). Developmental neurobiology of cognitive control and motivational systems. Current Opinion in Neurobiology, 20, 236–241.
37.
Van DijkK. R. A.SabuncuM. R.BucknerR. L. (2012). The influence of head motion on intrinsic functional connectivity MRI. NeuroImage, 59, 431–438.
38.
Van EssenD. C.UgurbilK.AuerbachE.BarchD.BehrensT. E. J.BucholzR., . . . & WU-Minn HCP Consortium (2012). The Human Connectome Project: A data acquisition perspective. NeuroImage, 62, 2222–2231.
39.
VincentJ. L.PatelG. H.FoxM. D.SnyderA. Z.BakerJ. T.EssenD. C. V.RaichleM. E. (2007). Intrinsic functional architecture in the anaesthetized monkey brain. Nature, 447, 83–86.
40.
ZhangD.RaichleM. E. (2010). Disease and the brain’s dark energy. Nature Reviews Neurology, 6, 15–28.
