US 20210170180A1
· Dosenbach
· 2021
[cited by examiner]
Choe, A. S., Jones, C. K., Joel, S. E., Muschelli, J., Belegu, V., Caffo, B. S., Lindquist, M. A., van Zijl, P. C. M., & Pekar, J. J. (2015). Reproducibility and Temporal Structure in Weekly Resting-State fMRI over a Pe…
[cited by examiner]
Friston et al., Movement-related effects in fMRI time-series, Magnetic Resonance in Medicine, 1996, 35(3):346-355.
[cited by applicant]
Friston et al., Nonlinear responses in fMRI: the Balloon model, Volterra kernels, and other hemodynamics, NeuroImage, 2000, 12(4):466-477.
[cited by applicant]
FSL—FSLWIKI, FMRIB Software Library, Retrieved from https://fsl.fmrib.ox.ac.uk/fsl/docs/#/, Version Accessed on Nov. 16, 2023, 1 page.
[cited by applicant]
Github, ABCD-Study, nda-abcd-collection-3165, Retrieved from https://github.com/ABCD-STUDY/nda-abcd-collection-3165, Version Accessed on Nov. 16, 2023, 2 pages.
[cited by applicant]
Github, DCAN-Labs, abcd-hcp-pipeline, Retrieved from https://github.com/DCAN-Labs/abcd-hcp-pipelines, Version Accessed on Nov. 16, 2023, 2 pages.
[cited by applicant]
Github, DCAN-Labs, nda-bids-upload, Retrieved from https://github.com/DCAN-Labs/nda-bids-upload, Version Accessed on Nov. 16, 2023, 2 pages.
[cited by applicant]
Github, Issues, ABCD-STUDY, nda-abcd-collection-3165, Retrieved from https://github.com/ABCD-STUDY/nda-abcd-collection-3165/issues, Version Accessed on Nov. 16, 2023, 2 pages.
[cited by applicant]
Github, MidnightScanClub, MSCcodebase, Retrieved from https://github.com/MidnightScanClub/MSCcodebase, Version Accessed on Nov. 16, 2023, 2 pages.
[cited by applicant]
Glasser et al., Mapping human cortical areas in vivo based on myelin content as revealed by T1-and T2-weighted MRI, Journal of Neuroscience, 2011, 31(32):11597-11616.
[cited by applicant]
Glasser et al., The minimal preprocessing pipelines for the Human Connectome Project, NeuroImage, 2013, 80:105-124.
[cited by applicant]
Glasser et al., A multi-modal parcellation of human cerebral cortex, Nature, 2016, 536(7615):171-178.
[cited by applicant]
Goldstone et al., Sleep disturbance predicts depression symptoms in early adolescence: initial findings from the adolescent brain cognitive development study, Journal of Adolescent Health, 2020, 66(5):567-574.
[cited by applicant]
Gordon et al., Working memory-related changes in functional connectivity persist beyond task disengagement, Human Brain Mapping, 2014, 35(3):1004-1017.
[cited by applicant]
Gordon et al., Generation and evaluation of a cortical area parcellation from resting-state correlations, Cerebral Cortex, 2016, 26(1):288-303.
[cited by applicant]
Gordon et al., Individual variability of the system-level organization of the human brain, Cerebral Cortex, 2017, 27(1):386-399.
[cited by applicant]
Gordon et al., Individual-specific features of brain systems identified with resting state functional correlation, NeuroImage, 2017, 146:918-939.
[cited by applicant]
Gordon et al., Precision functional mapping of individual human brains, Neuron, 2017, 95(4):791-807.
[cited by applicant]
Gordon et al., Three distinct sets of connector hubs integrate human brain function, Cell Reports, 2018, 24(7):1687-1695.
[cited by applicant]
Gorgolewski et al., A high resolution 7-Tesla resting-state fMRI test-retest dataset with cognitive and physiological measures, Scientific Data, 2015, 2(1):1-13.
[cited by applicant]
Gorgolewski et al., BIDS apps: Improving ease of use, accessibility, and reproducibility of neuroimaging data analysis methods, PLoS Computation Biology, 2017, 13(3):e1005209, pp. 1-16.
[cited by applicant]
Gratton et al., Distinct stages of moment-to-moment processing in the cinguloopercular and frontoparietal networks, Cerebral Cortex, 2017, 27(3):2403-2417.
[cited by applicant]
Gratton et al., Control networks and hubs, Psychophysiology, 2018, 55(3):e13032, pp. 1-28.
[cited by applicant]
Gratton et al., Functional brain networks are dominated by stable group and individual factors, not cognitive or daily variation, Neuron, 2018, 98(2):439-452.
[cited by applicant]
Grattton et al., Defining individual-specific functional neuroanatomy for precision psychiatry, Biological Psychiatry, 2020, 88(1):28-39.
[cited by applicant]
Greene et al., Integrative and network-specific connectivity of the basal ganglia and thalamus defined in individuals, Neuron, 2020, 105(4):742-758.
[cited by applicant]
Guerrero et al., Screen time and problem behaviors in children: exploring the mediating role of sleep duration, International Journal of Behavioral Nutrition and Physical Activity, 2019, 16(105):1-10.
[cited by applicant]
Harrison et al., Large-scale probabilistic functional modes from resting state fMRI, NeuroImage, 2015, 109:217-231.
[cited by applicant]
Hermosillo et al., Polygenic risk score-derived subcortical connectivity mediates attention-deficit/hyperactivity disorder diagnosi, Biological Psychiatry: Cognitive Neuroscience and Neuroimaging, 2020, 5(3):330-341.
[cited by applicant]
Huth et al., Natural speech reveals the semantic maps that tile human cerebral cortex, Nature, 2016, 532 (7600):453-458.
[cited by applicant]
Janiri et al., Risk and protective factors for childhood suicidality: a US population-based study, The Lancet Psychiatry, 2020, 7(4):317-326.
[cited by applicant]
Ji et al., Mapping the human brain's cortical-subcortical functional network organization, NeuroImage, 2019, 185:35-57.
[cited by applicant]
Kanwisher et al., The fusiform face area: a module in human extrastriate cortex specialized for face perception, Journal of Neuroscience, 1997, 17(11):4302-4311.
[cited by applicant]
Karcher et al., Resting-state functional connectivity and psychotic-like experiences in childhood: results from the adolescent brain cognitive development study, Biological Psychiatry, 2019, 86(1):7-15.
[cited by applicant]
Kelly et al., Development of anterior cingulate functional connectivity from late childhood to early adulthood, Cerebral Cortex, 2009, 19(3):640-657.
[cited by applicant]
Keuken et al., A probabilistic atlas of the basal ganglia using 7 T MRI, Data in Brief, 2015, 4:577-582.
[cited by applicant]
Klein et al., 101 labeled brain images and a consistent human cortical labeling protocol, Frontiers in Neuroscience, 2012, 6(171):1-12.
[cited by applicant]
Kong et al., Spatial topography of individual-specific cortical networks predicts human cognition, personality, and emotion, Cerebral Cortex, 2019, 29(6):2533-2551.
[cited by applicant]
Kong et al., Individual-specific areal-level parcellations improve functional connectivity prediction of behavior, Cerebral Cortex, 2021, 31(10):4477-4500.
[cited by applicant]
Lancaster et al., A modality-independent approach to spatial normalization of tomographic images of the human brain, Human Brain Mapping, 1995, 3(3):209-223.
[cited by applicant]
Laumann et al., Functional system and areal organization of a highly sampled individual human brain, Neuron, 2015, 87(3):657-670.
[cited by applicant]
Lee et al., Learning the parts of objects by non-negative matrix factorization, Nature, 1999, 401(6755):788-791.
[cited by applicant]
Li et al., Large-scale sparse functional networks from resting state fMRI, NeuroImage, 2017, 156:1-13.
[cited by applicant]
Luciana et al., Adolescent neurocognitive development and impacts of substance use: Overview of the adolescent brain cognitive development (ABCD) baseline neurocognition battery, Developmental Cognitive Neuroscience, 20…
[cited by applicant]
Lynch et al., Precision inhibitory stimulation of individual-specific cortical hubs disrupts information processing in humans, bioRxiv preprint doi: https://doi.org/10.1101/254417, 2018, 20 pages.
[cited by applicant]
Mapequation, Multilevel Community Detection with Infomap, Retrieved from https://www.mapequation.org/, Copyright 2020 mathequation. org, 2 pages.
[cited by applicant]
Marek et al., Spatial and temporal organization of the individual human cerebellum, Neuron, 2018, 100(4):977-993.
[cited by applicant]
Marek et al., Identifying reproducible individual differences in childhood functional brain networks: An ABCD study, Developmental Cognitive Neuroscience, 2019, 40:100706, pp. 1-14.
[cited by applicant]
Marek et al., Towards reproducible brain-wide association studies, bioRxiv preprint doi: https://doi.org/10.1101/2020.08.21.257758, 2020, 40 pages.
[cited by applicant]
Marshall et al., Association of lead-exposure risk and family income with childhood brain outcomes, Nature Medicine, 2020, 26(1):91-97.
[cited by applicant]
Mathworks, Matlab for Artificial Intelligence, Retrieved from https://www.mathworks.com/, Version Accessed on Nov. 16, 2023, 5 pages.
[cited by applicant]
Mazziotta et al., A probabilistic atlas of the human brain: theory and rationale for its development, NeuroImage, 1995, 2(2):89-101.
[cited by applicant]
Mazziotta et al., A four-dimensional probabilistic atlas of the human brain, Journal of the American Medical Informatics Association, 2001, 8(5):401-430.
[cited by applicant]
Miezin et al., Characterizing the hemodynamic response: effects of presentation rate, sampling procedure, and the possibility of ordering brain activity based on relative timing, NeuroImage, 2000, 11(6):735-759 [In Two …
[cited by applicant]
Miranda-Dominguez et al., Connectotyping: model based fingerprinting of the functional connectome, PloS One, 2014, 9(11):e111048, pp. 1-16.
[cited by applicant]
Mueller et al., Individual variability in functional connectivity architecture of the human brain, Neuron, 2013, 77(3):586-595.
[cited by applicant]
Neta et al., Spatial and temporal characteristics of error-related activity in the human brain, Journal of Neuroscience, 2015, 35(1):253-266.
[cited by applicant]
Newton et al., Improving measurement of functional connectivity through decreasing partial vol. effects at 7 T, NeuroImage, 2012, 59(3):2511-2517.
[cited by applicant]
Noble et al., Influences on the test-retest reliability of functional connectivity MRI and its relationship with behavioral utility, Cerebral Cortex, 2017, 27(11):5415-5429.
[cited by applicant]
Öngür et al., The organization of networks within the orbital and medial prefrontal cortex of rats, monkeys and human, Cerebral Cortex, 2000, 10(3):206-219 [In Three Parts Due to File Size].
[cited by applicant]
Openfmri, The Midnight Scan Club (MSC) Dataset, Retrieved from https://www.openfmri.org/dataset/ds000224/, Version Accessed on Nov. 16, 2023, 6 pages.
[cited by applicant]
Osfhome, ABCD-Bids Community Collection (ABCC), Contributors: Feczko et al., Retrieved from https://osf.io/psv5m/, Version Accessed on Nov. 16, 2023, 4 pages.
[cited by applicant]
Pagliaccio et al., Brain volume abnormalities in youth at high risk for depression: adolescent brain and cognitive development study, Journal of the American Academy of Child & Adolescent Psychiatry, 2020, 59(10):1178-1…
[cited by applicant]
Pauli et al., A high-resolution probabilistic in vivo atlas of human subcortical brain nuclei, Scientific Data, 2018, 5(1):180063, pp. 1-13.
[cited by applicant]
Poldrack et al., Long-term neural and physiological phenotyping of a single human, Nature Communications, 2015, 6(1):8885, pp. 1-15.
[cited by applicant]
Power et al., Functional network organization of the human brain, Neuron, 2011, 72(4): 665-678.
[cited by applicant]
Power et al., Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion, NeuroImage, 2012, 59(3):2142-2154.
[cited by applicant]
Power et al., Steps toward optimizing motion artifact removal in functional connectivity MRI; a reply to Carp, NeuroImage, 2012, 76:10-1016.
[cited by applicant]
Power et al., Control-related systems in the human brain, Current Opinion in Neurobiology, 2013, 23(2):223-228.
[cited by applicant]
Power et al., Evidence for hubs in human functional brain networks, Neuron, 2013, 79(4):798-813.
[cited by applicant]
Power et al., Methods to detect, characterize, and remove motion artifact in resting state fMRI, NeuroImage, 2014, 84:320-341.
[cited by applicant]
Rajkowska et al., Cytoarchitectonic definition of prefrontal areas in the normal human cortex: II. Variability in locations of areas 9 and 46 and relationship to the Talairach Coordinate System, Cerebral Cortex, 1995, 5…
[cited by applicant]
Rosvall et al., An information-theoretic framework for resolving community structure in complex networks, Proceedings of the National Academy of Sciences, 2007, 104(18):7327-7331.
[cited by applicant]
Rosvall et al., Maps of random walks on complex networks reveal community structure, Proceedings of the National Academy of Sciences, 2008, 105(4):1118-1123.
[cited by applicant]
Rosvall et al., The Map Equation, arXiv preprint arXiv:0906.1405v2, 2009, 9 pages.
[cited by applicant]
Schaefer et al., Local-global parcellation of the human cerebral cortex from intrinsic functional connectivity MRI, Cerebral Cortex, 2018, 28(9):3095-3114.
[cited by applicant]
Scheinost et al., Fluctuations in global brain activity are associated with changes in whole-brain connectivity of functional networks, IEEE Transactions on Biomedical Engineering, 2016, 63(12):2540-2549.
[cited by applicant]
Seitzman et al., Trait-like variants in human functional brain networks, Proceedings of the National Academy of Sciences, 2019, 116(45):22851-22861.
[cited by applicant]
Seitzman et al., A set of functionally-defined brain regions with improved representation of the subcortex and cerebellum, NeuroImage, 2020, 206:116290, pp. 1-17.
[cited by applicant]
Siegel et al., Data quality influences observed links between functional connectivity and behavior, Cerebral Cortex, 2017, 27(9):4492-4502.
[cited by applicant]
Silasi et al., Stroke and the connectome: how connectivity guides therapeutic intervention, Neuron, 2014, 83(6):1354-1368.
[cited by applicant]
Smith et al., Statistical challenges in “big data” human neuroimaging, Neuron, 2018, 97(2):263-268.
[cited by applicant]
Sporns et al., Identification and classification of hubs in brain networks, PLoS One, 2007, 2(10):e1049, pp. 1-14.
[cited by applicant]
Stein et al., Multisensory integration: current issues from the perspective of the single neuron, Nature Reviews Neuroscience, 2008, 9(4):255-266.
[cited by applicant]
Sylvester et al., Individual-specific functional connectivity of the amygdala: A substrate for precision psychiatry, Proceedings of the National Academy of Sciences, 2020, 117(7):3808-3818.
[cited by applicant]
Szucs et al., Empirical assessment of published effect sizes and power in the recent cognitive neuroscience and psychology literature, PLoS Biology, 2017, 15(3):e2000797, pp. 1-18.
[cited by applicant]
The National Institute of Mental Health Data Archive, Nimh Data Archive—NDA Home Page, Retrieved from https://nda.nih.gov/, Version Accessed on Nov. 16, 2023, 5 pages.
[cited by applicant]
Thompson et al., Detection and mapping of abnormal brain structure with a probabilistic atlas of cortical surfaces, Journal of Computer Assisted Tomography, 1997, 21(4):567-581.
[cited by applicant]
Thompson et al., The structure of cognition in 9 and 10 year-old children and associations with problem behaviors: Findings from the ABCD study's baseline neurocognitive battery, Developmental Cognitive Neuroscience, 20…
[cited by applicant]
Tustison et al., N4ITK: improved N3 bias correction, IEEE Transactions on Medical Imaging, 2010, 29(6):1310-1320.
[cited by applicant]
Tyszka et al., In vivo delineation of subdivisions of the human amygdaloid complex in a high-resolution group template, Human Brain Mapping, 2016, 37(11):3979-3998.
[cited by applicant]
University of Minnesota, Office of Academic Clinical Affairs, Masonic Institute for the Developing Brain, MIDB Precision Brain Atlas, Retrieved from https://midbatlas.io/, Version Accessed on Nov. 16, 2023, 2 pages.
[cited by applicant]
Van Den Heuvel et al., Rich-club organization of the human connectome, Journal of Neuroscience, 2011, 31(44):15775-15786.
[cited by applicant]
Van Den Heuvel et al., Network hubs in the human brain, Trends in Cognitive Sciences, 2013, 17(12):683-696.
[cited by applicant]
Van Den Heuvel et al., A cross-disorder connectome landscape of brain dysconnectivity, Nature Reviews Neuroscience, 2019, 20(7):435-446.
[cited by applicant]
Van Essen et al., A population-average, landmark-and surface-based (PALS) atlas of human cerebral cortex, NeuroImage, 2005, 38(3):635-662.
[cited by applicant]
Van Essen et al., The Human Connectome Project: a data acquisition perspective, NeuroImage, 2012, 62(4):2222-2231.
[cited by applicant]
Vesia et al., Specialization of reach function in human posterior parietal cortex, Experimental Brain Research, 2012, 221:1-18.
[cited by applicant]
Volkow et al., The conception of the ABCD study: From substance use to a broad NIH collaboration, Developmental Cognitive Neuroscience, 2018, 32:4-7.
[cited by applicant]
Wang et al., Parcellating cortical functional networks in individuals, Nature Neuroscience, 2015, 18(12):1853-1860.
[cited by applicant]
Wang et al., Probabilistic maps of visual topography in human cortex, Cerebral Cortex, 2015, 25(10):3911-3931.
[cited by applicant]
Weigand et al., Prospective validation that subgenual connectivity predicts antidepressant efficacy of transcranial magnetic stimulation sites, Biological Psychiatry, 2018, 84(1):28-37.
[cited by applicant]
Xing et al., Probabilistic MRI brain anatomical atlases based on 1,000 Chinese subjects, PLoS One, 2013, 8(1):e50939, pp. 1-6.
[cited by applicant]
Yang et al., Overlapping community detection at scale: a nonnegative matrix factorization approach, Proceedings of the Sixth ACM International Conference on Web Search and Data Mining, 2013, 10 pages.
[cited by applicant]
Yeo et al., The organization of the human cerebral cortex estimated by intrinsic functional connectivity, Journal of Neurophysiology, 2011, 106:1125-1165.
[cited by applicant]
Zhou et al., Functional connectivity of the caudal anterior cingulate cortex is decreased in autism, PLoS One, 2016, 11(3):e0151879, pp. 1-14.
[cited by applicant]
Adolescent Brain Cognitive Development, The ABCD Study®, Retrieved from https://abcdstudy.org/, Version Accessed on Nov. 16, 2023, 2 pages.
[cited by applicant]
Alexander et al., A new neonatal cortical and subcortical brain atlas: the Melbourne Children's Regional Infant Brain (M-CRIB) atlas, NeuroImage, 2017, 147:841-851.
[cited by applicant]
Alexander et al., Desikan-Killiany-Tourville atlas compatible version of M-CRIB neonatal parcellated whole brain atlas: The M-CRIB 2.0, Frontiers in Neuroscience, 2019, 13(34):1-9.
[cited by applicant]
Alvarado et al., A neural network model of multisensory integration also accounts for unisensory integration in superior colliculus, Brain Research, 2008, 1242:13-23.
[cited by applicant]
Andersen, Multimodal integration for the representation of space in the posterior parietal cortex, Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, 1997, 352(1360):1421-1428.
[cited by applicant]
Anderson et al., Reproducibility of single-subject functional connectivity measurements, American Journal of Neuroradiology, 2011, 32(3):548-555.
[cited by applicant]
Avants et al., Advanced normalization tools (ANTS), The Insight Journal, 2009, 2(365):1-35.
[cited by applicant]
Bagarinao et al., Identifying the brain's connector hubs at the voxel level using functional connectivity overlap ratio, NeuroImage, 2020, 222:117241, 11 pages.
[cited by applicant]
Bertolero et al., The modular and integrative functional architecture of the human brain, Proceedings of the National Academy of Sciences, 2015, 112(49):E6798-E6807.
[cited by applicant]
Braga et al., Parallel interdigitated distributed networks within the individual estimated by intrinsic functional connectivity, Neuron, 2017, 95(2):457-471.
[cited by applicant]
Braga et al., Parallel distributed networks resolved at high resolution reveal close juxtaposition of distinct regions, Journal of Neurophysiology, 2019, 121(4):1513-1534.
[cited by applicant]
Brain Imaging Data Stucture, Governance and Decision Making, Retrieved from https://bids.neuroimaging.io/collaboration/governance.html, Version Accessed on Nov. 16, 2023, 11 pages.
[cited by applicant]
Buckner et al., Cortical hubs revealed by intrinsic functional connectivity: mapping, assessment of stability, and relation to Alzheimer's disease, The Journal of Neuroscience, 2009, 29(6):1860-1873.
[cited by applicant]
Buckner et al., The evolution of distributed association networks in the human brain, Trends in Cognitive Sciences, 2013, 17(12):648-665.
[cited by applicant]
Carmichael et al., Connectional networks within the orbital and medial prefrontal cortex of macaque monkeys, The Journal of Comparative Neurology, 1996, 371(2):179-207.
[cited by applicant]
Casey et al., The adolescent brain cognitive development (ABCD) study: imaging acquisition across 21 sites, Developmental Cognitive Neuroscience, 2018, 32:43-54.
[cited by applicant]
Cash et al., Subgenual functional connectivity predicts antidepressant treatment response to transcranial magnetic stimulation: independent validation and evaluation of personalization, Biological Psychiatry, 2019, 86(2…
[cited by applicant]
Cash et al., Functional magnetic resonance imaging-guided personalization of transcranial magnetic stimulation treatment for depression, JAMA Psychiatry, 2021, 78(3):337-339.
[cited by applicant]
Cash et al., Personalized connectivity-guided DLPFC-TMS for depression: Advancing computational feasibility, precision and reproducibility, Human Brain Mapping, 2021, 42(13):4155-4172.
[cited by applicant]
Cash et al., Using brain imaging to improve spatial targeting of transcranial magnetic stimulation for depression, Biological Psychiatry, 2021, 90(10):689-700.
[cited by applicant]
Caspers et al., The human inferior parietal cortex: cytoarchitectonic parcellation and interindividual variability, NeuroImage, 2006, 33(2):430-448.
[cited by applicant]
Churchland et al., Perspectives on cognitive neuroscience, Science, 1988, 242(4879):741-745.
[cited by applicant]
Ciric et al., Benchmarking of participant-level confound regression strategies for the control of motion artifact in studies of functional connectivity, NeuroImage, 2017, 154:174-187.
[cited by applicant]
Cole et al., Stanford neuromodulation therapy (SNT): a double-blind randomized controlled trial, American Journal of Psychiatry, 2022, 179(2):132-141.
[cited by applicant]
Collection 3165—ABCD-Bids Community Collection (ABCC), ABCD-Bids Community Collection (ABCC) Documentation Summary, Retrieved from https://collection3165.readthedocs.io/en/stable/, Version Accessed on Nov. 16, 2023, 2 p…
[cited by applicant]
Connectome Coordination Facility, Using Conenctome Workbench, Retrieved from https://www.humanconnectome.org/software/connectome-workbench, Version Accessed on Nov. 16, 2023, 8 pages.
[cited by applicant]
Connectome Coordination Facility, What is the Connectome Coordination Facility?, Retrieved from https://www.humanconnectome.org/, Version Accessed on Nov. 16, 2023, 12 pages.
[cited by applicant]
Cui et al., Individual variation in functional topography of association networks in youth, Neuron, 2020, 106(2):340-353.
[cited by applicant]
Desikan et al., An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest, NeuroImage, 2006, 31(3):968-980.
[cited by applicant]
Destrieux et al., Automatic parcellation of human cortical gyri and sulci using standard anatomical nomenclature, NeuroImage, 2010, 53(1):1-15.
[cited by applicant]
Diedrichsen et al., A probabilistic MR atlas of the human cerebellum, NeuroImage, 2009, 46(1):39-46.
[cited by applicant]
Dosenbach et al., Real-time motion analytics during brain MRI improve data quality and reduce costs, NeuroImage, 2017, 161:80-93.
[cited by applicant]
Driver et al., Multisensory interplay reveals crossmodal influences on ‘sensory-specific’ brain regions, neural responses, and judgments, Neuron, 2008, 57(1):11-23.
[cited by applicant]
Du et al., Group information guided ICA for fMRI data analysis, NeuroImage, 2013, 69:157-197.
[cited by applicant]
Dubis et al., Tasks driven by perceptual information do not recruit sustained BOLD activity in cingulo-opercular regions, Cerebral Cortex, 2016, 26(1):192-201.
[cited by applicant]
Dworetsky et al., Probabilistic mapping of human functional brain networks identifies regions of high group consensus, NeuroImage, 2021, 237:118164, pp. 1-10.
[cited by applicant]
Eickhoff et al., Imaging-based parcellations of the human brain, Nature Reviews Neuroscience, 2018, 19(11):672-686.
[cited by applicant]
Elliott et al., General functional connectivity: Shared features of resting-state and task fMRI drive reliable and heritable individual differences in functional brain networks, NeuroImage, 2019, 189:516-532.
[cited by applicant]
Evans et al., 3D statistical neuroanatomical models from 305 MRI vols. 1993 IEEE Conference Record Nuclear Science Symposium and Medical Imaging Conference, IEEE, 1993, pp. 1813-1817.
[cited by applicant]
Fair et al., Functional brain networks develop from a “local to distributed” organization, PLoS Computational Biology, 2009, 5(5):e1000381, pp. 1-14.
[cited by applicant]
Fair et al., Correction of respiratory artifacts in MRI head motion estimates, NeuroImage, 2020, 208:116400, pp. 1-17.
[cited by applicant]
Fan et al., The human brainnetome atlas: a new brain atlas based on connectional architecture, Cerebral Cortex, 2016, 26(8):3508-3526.
[cited by applicant]
Faraone et al., Attention-deficit/hyperactivity disorder, Nature Reviews, Disease Primers, 2015, 1:15020, pp. 1-23.
[cited by applicant]
Feczko et al., Adolescent brain cognitive development (ABCD) community MRI collection and utilities, bioRxiv preprint doi: https://doi.org/10.1101/2021.07.09.451638, 2021, 33 pages.
[cited by applicant]
Felleman et al., Distributed hierarchical processing in the primate cerebral cortex, Cerebral Cortex, 1991, 1(1):1-47, Jun. 9, 2025.
[cited by applicant]
Finn et al., Functional connectome fingerprinting: identifying individuals using patterns of brain connectivity, Nature Neuroscience, 2015, 18(11):1664-1671.
[cited by applicant]
Fonov et al., Unbiased average age-appropriate atlases for pediatric studies, NeuroImage, 2011, 54(1):313-327.
[cited by applicant]
Fox et al., Efficacy of transcranial magnetic stimulation targets for depression is related to intrinsic functional connectivity with the subgenual cingulate, Biological Psychiatry, 2012, 72(7):595-603.
[cited by applicant]
Fox et al., Measuring and manipulating brain connectivity with resting state functional connectivity magnetic resonance imaging (fcMRI) and transcranial magnetic stimulation (TMS), NeuroImage, 2012, 62(4):2232-2243.
[cited by applicant]
Freesurfer, FreeSurfer Software Suite, Retrieved from https://surfer.nmr.mgh.harvard.edu/, Version Accessed on Nov. 16, 2023, 2 pages.
[cited by applicant]