Tracking ongoing cognition in individuals using brief, whole-brain functional connectivity patterns
Functional connectivity (FC) patterns in functional MRI exhibit dynamic behavior on the scale of seconds, with rich spatiotemporal structure and limited sets of whole-brain, quasi-stable FC configurations (FC states) recurring across time and subjects. Based on previous evidence linking various aspe...
Saved in:
| Published in | Proceedings of the National Academy of Sciences - PNAS Vol. 112; no. 28; pp. 8762 - 8767 |
|---|---|
| Main Authors | , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
National Academy of Sciences
14.07.2015
National Acad Sciences |
| Subjects | |
| Online Access | Get full text |
Cover
Loading…
| Abstract | Functional connectivity (FC) patterns in functional MRI exhibit dynamic behavior on the scale of seconds, with rich spatiotemporal structure and limited sets of whole-brain, quasi-stable FC configurations (FC states) recurring across time and subjects. Based on previous evidence linking various aspects of cognition to group-level, minute-to-minute FC changes in localized connections, we hypothesized that whole-brain FC states may reflect the global, orchestrated dynamics of cognitive processing on the scale of seconds. To test this hypothesis, subjects were continuously scanned as they engaged in and transitioned between mental states dictated by tasks. FC states computed within windows as short as 22.5 s permitted robust tracking of cognition in single subjects with near perfect accuracy. Accuracy dropped markedly for subjects with the lowest task performance. Spatially restricting FC information decreased accuracy at short time scales, emphasizing the distributed nature of whole-brain FC dynamics, beyond univariate magnitude changes, as valuable markers of cognition. |
|---|---|
| AbstractList | Functional connectivity (FC) patterns in functional MRI exhibit dynamic behavior on the scale of seconds, with rich spatiotemporal structure and limited sets of whole-brain, quasi-stable FC configurations (FC states) recurring across time and subjects. Based on previous evidence linking various aspects of cognition to group-level, minute-to-minute FC changes in localized connections, we hypothesized that whole-brain FC states may reflect the global, orchestrated dynamics of cognitive processing on the scale of seconds. To test this hypothesis, subjects were continuously scanned as they engaged in and transitioned between mental states dictated by tasks. FC states computed within windows as short as 22.5 s permitted robust tracking of cognition in single subjects with near perfect accuracy. Accuracy dropped markedly for subjects with the lowest task performance. Spatially restricting FC information decreased accuracy at short time scales, emphasizing the distributed nature of whole-brain FC dynamics, beyond univariate magnitude changes, as valuable markers of cognition. Recently, it was shown that functional connectivity patterns exhibit complex spatiotemporal dynamics at the scale of tens of seconds. Of particular interest is the observation of a limited set of quasi-stable, whole-brain, recurring configurations—commonly referred to as functional connectivity states (FC states)—hypothesized to reflect the continuous flux of cognitive processes. Here, to test this hypothesis, subjects were continuously scanned as they engaged in and transitioned between mental states dictated by tasks. We demonstrate that there is a strong relationship between FC states and ongoing cognition that permits accurate tracking of mental states in individual subjects. We also demonstrate how informative changes in connectivity are not restricted solely to those regions with sustained elevations in activity during task performance. Functional connectivity (FC) patterns in functional MRI exhibit dynamic behavior on the scale of seconds, with rich spatiotemporal structure and limited sets of whole-brain, quasi-stable FC configurations (FC states) recurring across time and subjects. Based on previous evidence linking various aspects of cognition to group-level, minute-to-minute FC changes in localized connections, we hypothesized that whole-brain FC states may reflect the global, orchestrated dynamics of cognitive processing on the scale of seconds. To test this hypothesis, subjects were continuously scanned as they engaged in and transitioned between mental states dictated by tasks. FC states computed within windows as short as 22.5 s permitted robust tracking of cognition in single subjects with near perfect accuracy. Accuracy dropped markedly for subjects with the lowest task performance. Spatially restricting FC information decreased accuracy at short time scales, emphasizing the distributed nature of whole-brain FC dynamics, beyond univariate magnitude changes, as valuable markers of cognition. Functional connectivity (FC) patterns in functional MRI exhibit dynamic behavior on the scale of seconds, with rich spatiotemporal structure and limited sets of whole-brain, quasi-stable FC configurations (FC states) recurring across time and subjects. Based on previous evidence linking various aspects of cognition to group-level, minute-to-minute FC changes in localized connections, we hypothesized that whole-brain FC states may reflect the global, orchestrated dynamics of cognitive processing on the scale of seconds. To test this hypothesis, subjects were continuously scanned as they engaged in and transitioned between mental states dictated by tasks. FC states computed within windows as short as 22.5 s permitted robust tracking of cognition in single subjects with near perfect accuracy. Accuracy dropped markedly for subjects with the lowest task performance. Spatially restricting FC information decreased accuracy at short time scales, emphasizing the distributed nature of whole-brain FC dynamics, beyond univariate magnitude changes, as valuable markers of cognition.Functional connectivity (FC) patterns in functional MRI exhibit dynamic behavior on the scale of seconds, with rich spatiotemporal structure and limited sets of whole-brain, quasi-stable FC configurations (FC states) recurring across time and subjects. Based on previous evidence linking various aspects of cognition to group-level, minute-to-minute FC changes in localized connections, we hypothesized that whole-brain FC states may reflect the global, orchestrated dynamics of cognitive processing on the scale of seconds. To test this hypothesis, subjects were continuously scanned as they engaged in and transitioned between mental states dictated by tasks. FC states computed within windows as short as 22.5 s permitted robust tracking of cognition in single subjects with near perfect accuracy. Accuracy dropped markedly for subjects with the lowest task performance. Spatially restricting FC information decreased accuracy at short time scales, emphasizing the distributed nature of whole-brain FC dynamics, beyond univariate magnitude changes, as valuable markers of cognition. |
| Author | Peter A. Bandettini Daniel A. Handwerker Meghan E. Robinson Laura C. Buchanan Gonzalez-Castillo, Javier Ziad S. Saad Colin W. Hoy |
| Author_xml | – sequence: 1 givenname: Javier surname: Gonzalez-Castillo fullname: Gonzalez-Castillo, Javier email: javier.gonzalez-castillo@nih.gov organization: Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892; javier.gonzalez-castillo@nih.gov – sequence: 2 givenname: Colin W surname: Hoy fullname: Hoy, Colin W organization: Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892; Helen Wills Neuroscience Institute, University of California, Berkeley, CA 94720 – sequence: 3 givenname: Daniel A surname: Handwerker fullname: Handwerker, Daniel A organization: Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892 – sequence: 4 givenname: Meghan E surname: Robinson fullname: Robinson, Meghan E organization: Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892; Veterans Affairs Boston Healthcare System, Boston, MA 02130 – sequence: 5 givenname: Laura C surname: Buchanan fullname: Buchanan, Laura C organization: Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892 – sequence: 6 givenname: Ziad S surname: Saad fullname: Saad, Ziad S organization: Statistical and Scientific Computing Core, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892 – sequence: 7 givenname: Peter A surname: Bandettini fullname: Bandettini, Peter A organization: Section on Functional Imaging Methods, Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892; Functional MRI Facility, National Institute of Mental Health, National Institutes of Health, Bethesda, MD 20892 |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/26124112$$D View this record in MEDLINE/PubMed |
| BookMark | eNqFks1rFDEYxoO02G317Ekd8OLBafP9cRGkaC0UPNieQyaTmWadTdZkZqX_vRl2u609WAiE8P6eJ2_yvMfgIMTgAHiD4CmCgpytg8mniEGEKUYIvwALBBWqOVXwACwgxKKWFNMjcJzzEkKomIQvwRHmRVD4BbDXydhfPvRVDH2cdxv74EcfQ-Xn1fqNbycz5GrKc7lJ3nWfqj-3cXB1k0yBuinYWWCGIg7BlcPGj3fV2oyjSyG_AoddMXCvd_sJuPn29fr8e3314-Ly_MtVbTkmY62IILQx0pHWKMkUdxLZhjTENNhRQaGFtmGocx3DEAknOFOUUAyJap3DgpyAz1vf9dSsXGtdGJMZ9Dr5lUl3Ohqv_60Ef6v7uNGUQYERLwYfdwYp_p5cHvXKZ-uGwQQXp6yRREISyol8HhUlB4EwEc-jXJXbmWCooB-eoMs4pfKxW0qoXZvvHr9z_8D7VAtwtgVsijkn1-0RBPU8N3qeG_0wN0XBniisH80cavkoP_xH937XylzY34KwxlJLwWfi7ZZY5jGmR71SziFhDw6didr0yWd987Pky8vwlpSZIn8BrmLkWQ |
| CitedBy_id | crossref_primary_10_1089_neu_2024_0318 crossref_primary_10_1007_s41109_019_0178_4 crossref_primary_10_3389_fnimg_2022_825105 crossref_primary_10_1109_MSP_2015_2478915 crossref_primary_10_1016_j_neuroimage_2016_05_078 crossref_primary_10_1177_0004867420948960 crossref_primary_10_1371_journal_pcbi_1004533 crossref_primary_10_1017_S003329171900028X crossref_primary_10_1016_j_neuroimage_2017_03_064 crossref_primary_10_1162_netn_a_00168 crossref_primary_10_1016_j_neuroimage_2020_117348 crossref_primary_10_1016_j_nic_2017_06_009 crossref_primary_10_1016_j_neuroimage_2017_10_019 crossref_primary_10_1002_hbm_24335 crossref_primary_10_1002_hbm_24336 crossref_primary_10_3389_fnins_2021_683633 crossref_primary_10_1038_s41467_021_22027_0 crossref_primary_10_3389_fnhum_2023_1134012 crossref_primary_10_1016_j_neuroimage_2019_116129 crossref_primary_10_1162_netn_a_00037 crossref_primary_10_1371_journal_pbio_3002732 crossref_primary_10_1016_j_neuroimage_2017_09_010 crossref_primary_10_1016_j_neuroimage_2021_117755 crossref_primary_10_1016_j_neuroimage_2018_12_037 crossref_primary_10_1038_s41467_024_51839_z crossref_primary_10_1111_adb_13050 crossref_primary_10_1016_j_seizure_2023_04_004 crossref_primary_10_1016_j_neuron_2018_03_035 crossref_primary_10_1016_j_neuroimage_2018_01_075 crossref_primary_10_1093_cercor_bhw265 crossref_primary_10_1016_j_neuroimage_2018_01_071 crossref_primary_10_1016_j_neuroimage_2018_01_080 crossref_primary_10_1139_apnm_2020_0396 crossref_primary_10_1016_j_neuroimage_2017_09_020 crossref_primary_10_3389_fnagi_2020_593648 crossref_primary_10_1016_j_neuroimage_2017_02_036 crossref_primary_10_1080_23273798_2019_1608072 crossref_primary_10_1007_s11336_023_09908_7 crossref_primary_10_3389_fpsyt_2020_00227 crossref_primary_10_1002_hbm_23268 crossref_primary_10_1016_j_neuroimage_2021_118254 crossref_primary_10_7554_eLife_32696 crossref_primary_10_1016_j_neuroimage_2021_118252 crossref_primary_10_1016_j_jneumeth_2018_08_021 crossref_primary_10_1016_j_neuroimage_2018_08_021 crossref_primary_10_1007_s10548_020_00792_3 crossref_primary_10_1016_j_clinph_2024_02_004 crossref_primary_10_1016_j_nicl_2024_103694 crossref_primary_10_1073_pnas_1912226117 crossref_primary_10_1016_j_neuroimage_2017_09_036 crossref_primary_10_1016_j_neuroimage_2021_117847 crossref_primary_10_1073_pnas_1615269114 crossref_primary_10_1089_brain_2018_0632 crossref_primary_10_1038_s41386_024_01962_8 crossref_primary_10_1371_journal_pone_0168180 crossref_primary_10_1007_s11571_019_09557_6 crossref_primary_10_1016_j_jocn_2024_110817 crossref_primary_10_1016_j_neuroimage_2021_118027 crossref_primary_10_1016_j_nicl_2020_102507 crossref_primary_10_1002_hbm_26044 crossref_primary_10_1093_cercor_bhac133 crossref_primary_10_1002_hbm_23574 crossref_primary_10_1016_j_neuroimage_2022_119288 crossref_primary_10_1038_s41593_024_01618_2 crossref_primary_10_1021_acsphotonics_3c01253 crossref_primary_10_1002_glia_23079 crossref_primary_10_1038_s41598_024_79820_2 crossref_primary_10_3389_fnhum_2022_875201 crossref_primary_10_1016_j_neuroimage_2016_12_061 crossref_primary_10_1371_journal_pcbi_1005031 crossref_primary_10_1016_j_neuroimage_2018_10_054 crossref_primary_10_3389_fnins_2023_1131062 crossref_primary_10_1523_JNEUROSCI_2948_19_2020 crossref_primary_10_1007_s11682_020_00266_x crossref_primary_10_1016_j_jad_2024_07_123 crossref_primary_10_1016_j_neuron_2019_08_025 crossref_primary_10_1016_j_neuroimage_2021_118590 crossref_primary_10_1016_j_dcn_2020_100855 crossref_primary_10_1103_PhysRevE_94_052411 crossref_primary_10_1016_j_neuroimage_2022_119279 crossref_primary_10_1093_cercor_bhw279 crossref_primary_10_3389_fnins_2022_1050240 crossref_primary_10_3389_fphys_2018_01852 crossref_primary_10_1007_s11682_023_00790_6 crossref_primary_10_1016_j_neuroimage_2021_118800 crossref_primary_10_1016_j_neuroimage_2016_12_073 crossref_primary_10_1016_j_tics_2017_09_006 crossref_primary_10_1093_cercor_bhw029 crossref_primary_10_1162_netn_a_00193 crossref_primary_10_1016_j_cobeha_2020_12_007 crossref_primary_10_1093_brain_aww337 crossref_primary_10_1002_hbm_25617 crossref_primary_10_1093_cercor_bhac396 crossref_primary_10_1002_hbm_26060 crossref_primary_10_1038_s41598_020_78276_4 crossref_primary_10_1093_scan_nsaa114 crossref_primary_10_1002_hbm_26183 crossref_primary_10_1016_j_bbr_2023_114521 crossref_primary_10_1093_schbul_sbw078 crossref_primary_10_1371_journal_pcbi_1005178 crossref_primary_10_1016_j_neuroscience_2019_10_024 crossref_primary_10_3390_brainsci10040223 crossref_primary_10_1002_hbm_25649 crossref_primary_10_1007_s11682_018_9976_z crossref_primary_10_1002_hbm_25763 crossref_primary_10_1016_j_neuroimage_2023_120221 crossref_primary_10_1523_JNEUROSCI_1324_15_2015 crossref_primary_10_1073_pnas_2110811118 crossref_primary_10_31887_DCNS_2018_20_2_osporns crossref_primary_10_1162_netn_a_00051 crossref_primary_10_1016_j_conb_2016_05_003 crossref_primary_10_1016_j_neuroimage_2019_01_063 crossref_primary_10_1016_j_neuroimage_2020_117630 crossref_primary_10_1093_cercor_bhaa305 crossref_primary_10_1523_JNEUROSCI_0723_23_2023 crossref_primary_10_1016_j_neuroimage_2018_04_070 crossref_primary_10_1002_hbm_23890 crossref_primary_10_3389_fnhum_2016_00659 crossref_primary_10_1109_TIM_2020_3019849 crossref_primary_10_1016_j_neuroimage_2022_119364 crossref_primary_10_1002_hbm_26488 crossref_primary_10_1109_TSIPN_2020_2984853 crossref_primary_10_3390_brainsci14121172 crossref_primary_10_1007_s10548_019_00719_7 crossref_primary_10_1371_journal_pone_0149849 crossref_primary_10_3389_fnut_2024_1354245 crossref_primary_10_1093_cercor_bhw089 crossref_primary_10_1162_netn_a_00321 crossref_primary_10_1038_s41380_024_02486_9 crossref_primary_10_1109_TMI_2022_3187141 crossref_primary_10_1016_j_mri_2019_11_012 crossref_primary_10_1016_j_neuroimage_2021_118310 crossref_primary_10_1162_imag_a_00366 crossref_primary_10_1002_hbm_24979 crossref_primary_10_1016_j_neuroimage_2017_08_044 crossref_primary_10_1016_j_neuroimage_2023_119890 crossref_primary_10_1007_s11695_018_3178_z crossref_primary_10_31887_DCNS_2016_18_3_efinn crossref_primary_10_1109_TMI_2020_3030047 crossref_primary_10_1016_j_celrep_2016_10_002 crossref_primary_10_1016_j_jad_2019_04_103 crossref_primary_10_1093_cercor_bhy011 crossref_primary_10_1038_s42003_022_03466_x crossref_primary_10_2174_18744400_v15_e2206270 crossref_primary_10_1007_s10548_017_0546_2 crossref_primary_10_1016_j_neuroimage_2020_117296 crossref_primary_10_1523_JNEUROSCI_0037_21_2021 crossref_primary_10_3389_fnhum_2022_868135 crossref_primary_10_1002_hbm_24721 crossref_primary_10_1016_j_neuroimage_2017_05_050 crossref_primary_10_1371_journal_pbio_3002808 crossref_primary_10_1016_j_tins_2023_04_001 crossref_primary_10_3389_fpsyg_2023_1068404 crossref_primary_10_1016_j_celrep_2023_112527 crossref_primary_10_1162_netn_a_00301 crossref_primary_10_1093_cercor_bhy282 crossref_primary_10_3389_fncir_2021_608655 crossref_primary_10_1371_journal_pcbi_1011007 crossref_primary_10_1016_j_neuroimage_2022_119818 crossref_primary_10_1007_s11682_020_00287_6 crossref_primary_10_1016_j_neuroimage_2020_116635 crossref_primary_10_1016_j_neuroimage_2019_04_048 crossref_primary_10_3389_fnins_2018_00994 crossref_primary_10_3389_fnins_2017_00624 crossref_primary_10_1016_j_neuroimage_2021_118531 crossref_primary_10_3389_fnhum_2022_971062 crossref_primary_10_3390_life13091852 crossref_primary_10_1007_s11682_024_00908_4 crossref_primary_10_1162_netn_a_00419 crossref_primary_10_1016_j_neuroimage_2022_119131 crossref_primary_10_1089_brain_2017_0543 crossref_primary_10_1038_s41598_022_25016_5 crossref_primary_10_1002_hbm_26258 crossref_primary_10_1007_s00429_018_1619_z crossref_primary_10_1016_j_neuroimage_2018_09_042 crossref_primary_10_1016_j_neuroimage_2018_03_074 crossref_primary_10_1007_s00429_020_02119_1 crossref_primary_10_1109_JBHI_2020_3008731 crossref_primary_10_1186_s12888_023_05009_y crossref_primary_10_1038_s41380_024_02683_6 crossref_primary_10_1016_j_neuroimage_2020_117156 crossref_primary_10_3389_fnins_2017_00072 crossref_primary_10_3389_fnhum_2020_00003 crossref_primary_10_1016_j_neuroimage_2021_118423 crossref_primary_10_1093_gigascience_giae009 crossref_primary_10_3389_fnhum_2018_00166 crossref_primary_10_1093_cercor_bhac247 crossref_primary_10_3389_fpsyt_2022_1054380 crossref_primary_10_1038_s41598_023_48656_7 crossref_primary_10_1002_hbm_24385 crossref_primary_10_1016_j_neuroimage_2023_120395 crossref_primary_10_1038_s41598_023_44001_0 crossref_primary_10_1016_j_neuroimage_2017_08_006 crossref_primary_10_1002_hbm_24381 crossref_primary_10_1016_j_neuroimage_2021_117784 crossref_primary_10_1016_j_neuroimage_2019_116398 crossref_primary_10_3389_fneur_2019_01242 crossref_primary_10_1126_sciadv_abq8566 crossref_primary_10_1002_hbm_24374 crossref_primary_10_1016_j_neuroimage_2018_05_040 crossref_primary_10_1002_hbm_25225 crossref_primary_10_1038_srep46072 crossref_primary_10_1162_netn_a_00116 crossref_primary_10_1162_netn_a_00117 crossref_primary_10_1162_netn_a_00238 crossref_primary_10_3389_fnagi_2017_00152 crossref_primary_10_3389_fnins_2020_00645 crossref_primary_10_1162_jocn_a_01779 crossref_primary_10_1038_s41467_018_03664_4 crossref_primary_10_1016_j_cobeha_2021_04_002 crossref_primary_10_1038_s41467_022_31965_2 crossref_primary_10_1002_hbm_70024 crossref_primary_10_1093_braincomms_fcae154 crossref_primary_10_1016_j_neuroimage_2017_08_010 crossref_primary_10_1007_s11682_020_00405_4 crossref_primary_10_1016_j_neuroimage_2019_116059 crossref_primary_10_1162_NETN_a_00028 crossref_primary_10_1016_j_nicl_2021_102726 crossref_primary_10_3389_fnins_2019_01333 crossref_primary_10_3389_fnsys_2017_00029 crossref_primary_10_1016_j_neuroimage_2017_09_065 crossref_primary_10_1016_j_neuroimage_2022_118928 crossref_primary_10_1038_s41598_021_93190_z crossref_primary_10_1038_nrn_2017_149 crossref_primary_10_1016_j_neubiorev_2025_106024 crossref_primary_10_1002_hbm_24831 crossref_primary_10_3389_fpsyt_2020_00663 crossref_primary_10_1038_s41598_017_06389_4 crossref_primary_10_1038_s41598_017_06866_w crossref_primary_10_3389_fnins_2019_01220 crossref_primary_10_24835_1607_0763_2020_2_119_130 crossref_primary_10_1016_j_nicl_2022_103207 crossref_primary_10_1080_19312458_2020_1860206 crossref_primary_10_1016_j_neuroimage_2018_01_040 crossref_primary_10_1093_cercor_bhac209 crossref_primary_10_1016_j_neuroimage_2020_117111 crossref_primary_10_1016_j_neulet_2018_09_008 |
| Cites_doi | 10.1089/brain.2012.0115 10.1002/1522-2594(200007)44:1<162::AID-MRM23>3.0.CO;2-E 10.1016/j.neuroimage.2010.01.093 10.1371/journal.pone.0039731 10.1126/science.282.5395.1846 10.1016/j.nicl.2014.07.003 10.1093/cercor/bhs352 10.1016/j.neuroimage.2012.06.036 10.1002/hbm.22058 10.1016/j.neuroimage.2012.06.078 10.1016/S0167-8760(97)00098-6 10.3389/fnins.2014.00138 10.3389/fnhum.2012.00339 10.1006/cbmr.1996.0014 10.1093/cercor/bhr099 10.1016/S1364-6613(00)01819-2 10.1016/j.neuroimage.2013.01.049 10.1037/1082-989X.9.3.386 10.1093/brain/121.6.1013 10.1016/j.neuroimage.2010.04.246 10.1523/JNEUROSCI.1604-12.2012 10.1007/BF01908075 10.1073/pnas.1121049109 10.1073/pnas.1007841107 10.1016/j.neuroimage.2006.02.048 10.1016/j.neuroimage.2010.05.081 10.1016/j.neuroimage.2013.04.083 10.1002/hbm.21333 10.1063/1.4790830 10.1016/j.neuroimage.2012.02.031 10.1016/j.neuroimage.2009.12.011 10.1073/pnas.1311149110 10.1016/j.neuroimage.2008.09.029 10.1016/j.neuroimage.2012.10.076 10.1016/j.neuroimage.2013.05.079 10.1016/j.neuroimage.2010.02.052 10.1073/pnas.0905267106 10.1016/j.neuron.2014.10.015 10.3174/ajnr.A2894 10.1371/journal.pone.0085929 10.1016/j.neuroimage.2012.03.070 10.1371/journal.pcbi.1002441 10.1016/j.brainresbull.2009.11.014 10.1016/j.neuroimage.2014.09.007 10.1038/nmeth.1635 10.1016/j.neuroimage.2013.07.036 10.1073/pnas.1121329109 |
| ContentType | Journal Article |
| Copyright | Volumes 1–89 and 106–112, copyright as a collective work only; author(s) retains copyright to individual articles Copyright National Academy of Sciences Jul 14, 2015 |
| Copyright_xml | – notice: Volumes 1–89 and 106–112, copyright as a collective work only; author(s) retains copyright to individual articles – notice: Copyright National Academy of Sciences Jul 14, 2015 |
| DBID | FBQ AAYXX CITATION CGR CUY CVF ECM EIF NPM 7QG 7QL 7QP 7QR 7SN 7SS 7T5 7TK 7TM 7TO 7U9 8FD C1K FR3 H94 M7N P64 RC3 7X8 7S9 L.6 5PM |
| DOI | 10.1073/pnas.1501242112 |
| DatabaseName | AGRIS CrossRef Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed Animal Behavior Abstracts Bacteriology Abstracts (Microbiology B) Calcium & Calcified Tissue Abstracts Chemoreception Abstracts Ecology Abstracts Entomology Abstracts (Full archive) Immunology Abstracts Neurosciences Abstracts Nucleic Acids Abstracts Oncogenes and Growth Factors Abstracts Virology and AIDS Abstracts Technology Research Database Environmental Sciences and Pollution Management Engineering Research Database AIDS and Cancer Research Abstracts Algology Mycology and Protozoology Abstracts (Microbiology C) Biotechnology and BioEngineering Abstracts Genetics Abstracts MEDLINE - Academic AGRICOLA AGRICOLA - Academic PubMed Central (Full Participant titles) |
| DatabaseTitle | CrossRef MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) Virology and AIDS Abstracts Oncogenes and Growth Factors Abstracts Technology Research Database Nucleic Acids Abstracts Ecology Abstracts Neurosciences Abstracts Biotechnology and BioEngineering Abstracts Environmental Sciences and Pollution Management Entomology Abstracts Genetics Abstracts Animal Behavior Abstracts Bacteriology Abstracts (Microbiology B) Algology Mycology and Protozoology Abstracts (Microbiology C) AIDS and Cancer Research Abstracts Chemoreception Abstracts Immunology Abstracts Engineering Research Database Calcium & Calcified Tissue Abstracts MEDLINE - Academic AGRICOLA AGRICOLA - Academic |
| DatabaseTitleList | Neurosciences Abstracts MEDLINE AGRICOLA Virology and AIDS Abstracts MEDLINE - Academic CrossRef |
| Database_xml | – sequence: 1 dbid: NPM name: PubMed url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 2 dbid: EIF name: MEDLINE url: https://proxy.k.utb.cz/login?url=https://www.webofscience.com/wos/medline/basic-search sourceTypes: Index Database – sequence: 3 dbid: FBQ name: AGRIS url: http://www.fao.org/agris/Centre.asp?Menu_1ID=DB&Menu_2ID=DB1&Language=EN&Content=http://www.fao.org/agris/search?Language=EN sourceTypes: Publisher |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Sciences (General) |
| DocumentTitleAlternate | Tracking ongoing cognition with fMRI connectivity |
| EISSN | 1091-6490 |
| EndPage | 8767 |
| ExternalDocumentID | PMC4507216 3750355881 26124112 10_1073_pnas_1501242112 112_28_8762 26466035 US201600201759 |
| Genre | Journal Article Research Support, N.I.H., Intramural Feature |
| GrantInformation_xml | – fundername: Intramural NIH HHS |
| GroupedDBID | --- -DZ -~X .55 .GJ 0R~ 123 29P 2AX 2FS 2WC 3O- 4.4 53G 5RE 5VS 692 6TJ 79B 85S AACGO AAFWJ AANCE AAYJJ ABBHK ABOCM ABPLY ABPPZ ABPTK ABTLG ABZEH ACGOD ACIWK ACKIV ACNCT ACPRK ADULT ADZLD AENEX AEUPB AEXZC AFDAS AFFNX AFOSN AFRAH ALMA_UNASSIGNED_HOLDINGS ASUFR AS~ BKOMP CS3 D0L DCCCD DIK DNJUQ DOOOF DU5 DWIUU E3Z EBS EJD F20 F5P FBQ FRP GX1 HGD HH5 HQ3 HTVGU HYE JAAYA JBMMH JENOY JHFFW JKQEH JLS JLXEF JPM JSG JSODD JST KQ8 L7B LU7 MVM N9A NEJ NHB N~3 O9- OK1 P-O PNE PQQKQ R.V RHF RHI RNA RNS RPM RXW SA0 SJN TAE TN5 UKR VOH VQA W8F WH7 WHG WOQ WOW X7M XFK XSW Y6R YBH YKV YSK ZA5 ZCA ZCG ~02 ~KM ABXSQ ACHIC ADQXQ AQVQM H13 IPSME - 02 0R 1AW 55 AAPBV ABFLS ADACO DZ KM PQEST X XHC AAYXX CITATION CGR CUY CVF ECM EIF NPM 7QG 7QL 7QP 7QR 7SN 7SS 7T5 7TK 7TM 7TO 7U9 8FD C1K FR3 H94 M7N P64 RC3 7X8 7S9 L.6 5PM |
| ID | FETCH-LOGICAL-c623t-93734ba8e3da98596e81cb3b3ab2e4740c0cb51fef52017e76594342039dee273 |
| ISSN | 0027-8424 1091-6490 |
| IngestDate | Thu Aug 21 14:01:46 EDT 2025 Fri Jul 11 02:30:10 EDT 2025 Fri Jul 11 15:17:44 EDT 2025 Fri Jul 11 05:36:13 EDT 2025 Mon Jun 30 08:30:32 EDT 2025 Mon Jul 21 05:56:25 EDT 2025 Tue Jul 01 01:53:29 EDT 2025 Thu Apr 24 23:08:14 EDT 2025 Wed Nov 11 00:29:40 EST 2020 Fri May 30 12:01:37 EDT 2025 Wed Dec 27 19:00:54 EST 2023 |
| IsDoiOpenAccess | false |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 28 |
| Keywords | cognitive states fMRI functional connectivity states connectivity dynamics classification |
| Language | English |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-c623t-93734ba8e3da98596e81cb3b3ab2e4740c0cb51fef52017e76594342039dee273 |
| Notes | http://dx.doi.org/10.1073/pnas.1501242112 SourceType-Scholarly Journals-1 ObjectType-Feature-1 content type line 14 ObjectType-Article-1 ObjectType-Feature-2 content type line 23 1J.G.-C. and C.W.H. contributed equally to this work. Author contributions: J.G.-C., C.W.H., D.A.H., M.E.R., and P.A.B. designed research; J.G.-C., C.W.H., M.E.R., and L.C.B. performed research; Z.S.S. contributed new reagents/analytic tools; J.G.-C., C.W.H., D.A.H., M.E.R., and L.C.B. analyzed data; and J.G.-C., C.W.H., D.A.H., Z.S.S., and P.A.B. wrote the paper. Edited by Russell A. Poldrack, University of Texas at Austin, Austin, TX, and accepted by the Editorial Board June 1, 2015 (received for review January 21, 2015) |
| OpenAccessLink | https://www.pnas.org/content/pnas/112/28/8762.full.pdf |
| PMID | 26124112 |
| PQID | 1697797216 |
| PQPubID | 42026 |
| PageCount | 6 |
| ParticipantIDs | proquest_miscellaneous_1697215751 pubmed_primary_26124112 proquest_miscellaneous_1709171237 pubmedcentral_primary_oai_pubmedcentral_nih_gov_4507216 proquest_journals_1697797216 crossref_citationtrail_10_1073_pnas_1501242112 pnas_primary_112_28_8762 fao_agris_US201600201759 proquest_miscellaneous_1817834638 crossref_primary_10_1073_pnas_1501242112 jstor_primary_26466035 |
| ProviderPackageCode | RNA PNE CITATION AAYXX |
| PublicationCentury | 2000 |
| PublicationDate | 2015-07-14 |
| PublicationDateYYYYMMDD | 2015-07-14 |
| PublicationDate_xml | – month: 07 year: 2015 text: 2015-07-14 day: 14 |
| PublicationDecade | 2010 |
| PublicationPlace | United States |
| PublicationPlace_xml | – name: United States – name: Washington |
| PublicationTitle | Proceedings of the National Academy of Sciences - PNAS |
| PublicationTitleAlternate | Proc Natl Acad Sci U S A |
| PublicationYear | 2015 |
| Publisher | National Academy of Sciences National Acad Sciences |
| Publisher_xml | – name: National Academy of Sciences – name: National Acad Sciences |
| References | Richiardi J (e_1_3_4_18_2) 2011; 56 Baars BJ (e_1_3_4_40_2) 2002; 6 Tononi G (e_1_3_4_22_2) 2010; 148 Chang C (e_1_3_4_47_2) 2009; 44 Yarkoni T (e_1_3_4_38_2) 2011; 8 Milazzo AC (e_1_3_4_37_2) 2014; 2014 Gonzalez-Castillo J (e_1_3_4_15_2) 2014; 8 Tagliazucchi E (e_1_3_4_6_2) 2012; 6 Shirer WR (e_1_3_4_17_2) 2012; 22 Smith SM (e_1_3_4_7_2) 2012; 109 Gonzalez-Castillo J (e_1_3_4_21_2) 2012; 109 Thompson GJ (e_1_3_4_12_2) 2013; 83 Delamillieure P (e_1_3_4_23_2) 2010; 81 Leonardi N (e_1_3_4_39_2) 2015; 104 Glover GH (e_1_3_4_45_2) 2000; 44 Birn RM (e_1_3_4_46_2) 2006; 31 Craddock RC (e_1_3_4_26_2) 2012; 33 Mesulam MM (e_1_3_4_20_2) 1998; 121 Yuan H (e_1_3_4_35_2) 2012; 60 Pantazatos SP (e_1_3_4_28_2) 2012; 8 Steinley D (e_1_3_4_25_2) 2004; 9 Keilholz SD (e_1_3_4_10_2) 2013; 3 Hutchison RM (e_1_3_4_9_2) 2013; 34 Calhoun VD (e_1_3_4_16_2) 2014; 84 Hubert L (e_1_3_4_24_2) 1985; 2 Britz J (e_1_3_4_34_2) 2010; 52 e_1_3_4_41_2 Schlegel A (e_1_3_4_31_2) 2013; 110 Musso F (e_1_3_4_36_2) 2010; 52 Cribben I (e_1_3_4_29_2) 2012; 61 Bassett DS (e_1_3_4_14_2) 2013; 23 Castellanos FX (e_1_3_4_3_2) 2013; 80 Gonzalez-Castillo J (e_1_3_4_49_2) 2013; 67 Damaraju E (e_1_3_4_43_2) 2014; 5 Smith SM (e_1_3_4_1_2) 2009; 106 Lehmann D (e_1_3_4_32_2) 1998; 29 Chou YH (e_1_3_4_2_2) 2012; 33 Hutchison RM (e_1_3_4_4_2) 2013; 80 Jones DT (e_1_3_4_42_2) 2012; 7 Cox RW (e_1_3_4_44_2) 1996; 29 Chang C (e_1_3_4_5_2) 2010; 50 Chang C (e_1_3_4_11_2) 2013; 72 Allen EA (e_1_3_4_13_2) 2014; 24 Zilverstand A (e_1_3_4_27_2) 2014; 9 Heinzle J (e_1_3_4_30_2) 2012; 32 Jo HJ (e_1_3_4_48_2) 2010; 52 Van de Ville D (e_1_3_4_33_2) 2010; 107 Handwerker DA (e_1_3_4_8_2) 2012; 63 Tagliazucchi E (e_1_3_4_19_2) 2012; 63 |
| References_xml | – volume: 3 start-page: 31 year: 2013 ident: e_1_3_4_10_2 article-title: Dynamic properties of functional connectivity in the rodent publication-title: Brain Connect doi: 10.1089/brain.2012.0115 – volume: 44 start-page: 162 year: 2000 ident: e_1_3_4_45_2 article-title: Image-based method for retrospective correction of physiological motion effects in fMRI: RETROICOR publication-title: Magn Reson Med doi: 10.1002/1522-2594(200007)44:1<162::AID-MRM23>3.0.CO;2-E – volume: 52 start-page: 1149 year: 2010 ident: e_1_3_4_36_2 article-title: Spontaneous brain activity and EEG microstates: A novel EEG/fMRI analysis approach to explore resting-state networks publication-title: Neuroimage doi: 10.1016/j.neuroimage.2010.01.093 – volume: 7 start-page: e39731 year: 2012 ident: e_1_3_4_42_2 article-title: Non-stationarity in the “resting brain’s” modular architecture publication-title: PLoS ONE doi: 10.1371/journal.pone.0039731 – ident: e_1_3_4_41_2 doi: 10.1126/science.282.5395.1846 – volume: 5 start-page: 298 year: 2014 ident: e_1_3_4_43_2 article-title: Dynamic functional connectivity analysis reveals transient states of dysconnectivity in schizophrenia publication-title: Neuroimage Clin doi: 10.1016/j.nicl.2014.07.003 – volume: 24 start-page: 663 year: 2014 ident: e_1_3_4_13_2 article-title: Tracking whole-brain connectivity dynamics in the resting state publication-title: Cereb Cortex doi: 10.1093/cercor/bhs352 – volume: 63 start-page: 63 year: 2012 ident: e_1_3_4_19_2 article-title: Automatic sleep staging using fMRI functional connectivity data publication-title: Neuroimage doi: 10.1016/j.neuroimage.2012.06.036 – volume: 34 start-page: 2154 year: 2013 ident: e_1_3_4_9_2 article-title: Resting-state networks show dynamic functional connectivity in awake humans and anesthetized macaques publication-title: Hum Brain Mapp doi: 10.1002/hbm.22058 – volume: 63 start-page: 1712 year: 2012 ident: e_1_3_4_8_2 article-title: Periodic changes in fMRI connectivity publication-title: Neuroimage doi: 10.1016/j.neuroimage.2012.06.078 – volume: 29 start-page: 1 year: 1998 ident: e_1_3_4_32_2 article-title: Brain electric microstates and momentary conscious mind states as building blocks of spontaneous thinking: I. Visual imagery and abstract thoughts publication-title: Int J Psychophysiol doi: 10.1016/S0167-8760(97)00098-6 – volume: 8 start-page: 138 year: 2014 ident: e_1_3_4_15_2 article-title: The spatial structure of resting state connectivity stability on the scale of minutes publication-title: Front Neurosci doi: 10.3389/fnins.2014.00138 – volume: 6 start-page: 339 year: 2012 ident: e_1_3_4_6_2 article-title: Dynamic BOLD functional connectivity in humans and its electrophysiological correlates publication-title: Front Hum Neurosci doi: 10.3389/fnhum.2012.00339 – volume: 29 start-page: 162 year: 1996 ident: e_1_3_4_44_2 article-title: AFNI: Software for analysis and visualization of functional magnetic resonance neuroimages publication-title: Comput Biomed Res doi: 10.1006/cbmr.1996.0014 – volume: 22 start-page: 158 year: 2012 ident: e_1_3_4_17_2 article-title: Decoding subject-driven cognitive states with whole-brain connectivity patterns publication-title: Cereb Cortex doi: 10.1093/cercor/bhr099 – volume: 6 start-page: 47 year: 2002 ident: e_1_3_4_40_2 article-title: The conscious access hypothesis: Origins and recent evidence publication-title: Trends Cogn Sci doi: 10.1016/S1364-6613(00)01819-2 – volume: 72 start-page: 227 year: 2013 ident: e_1_3_4_11_2 article-title: EEG correlates of time-varying BOLD functional connectivity publication-title: Neuroimage doi: 10.1016/j.neuroimage.2013.01.049 – volume: 9 start-page: 386 year: 2004 ident: e_1_3_4_25_2 article-title: Properties of the Hubert-Arabie adjusted Rand index publication-title: Psychol Methods doi: 10.1037/1082-989X.9.3.386 – volume: 121 start-page: 1013 year: 1998 ident: e_1_3_4_20_2 article-title: From sensation to cognition publication-title: Brain doi: 10.1093/brain/121.6.1013 – volume: 52 start-page: 571 year: 2010 ident: e_1_3_4_48_2 article-title: Mapping sources of correlation in resting state FMRI, with artifact detection and removal publication-title: Neuroimage doi: 10.1016/j.neuroimage.2010.04.246 – volume: 32 start-page: 9960 year: 2012 ident: e_1_3_4_30_2 article-title: Visuomotor functional network topology predicts upcoming tasks publication-title: J Neurosci doi: 10.1523/JNEUROSCI.1604-12.2012 – volume: 2 start-page: 193 year: 1985 ident: e_1_3_4_24_2 article-title: Comparing partitions publication-title: J Classif doi: 10.1007/BF01908075 – volume: 109 start-page: 5487 year: 2012 ident: e_1_3_4_21_2 article-title: Whole-brain, time-locked activation with simple tasks revealed using massive averaging and model-free analysis publication-title: Proc Natl Acad Sci USA doi: 10.1073/pnas.1121049109 – volume: 107 start-page: 18179 year: 2010 ident: e_1_3_4_33_2 article-title: EEG microstate sequences in healthy humans at rest reveal scale-free dynamics publication-title: Proc Natl Acad Sci USA doi: 10.1073/pnas.1007841107 – volume: 31 start-page: 1536 year: 2006 ident: e_1_3_4_46_2 article-title: Separating respiratory-variation-related fluctuations from neuronal-activity-related fluctuations in fMRI publication-title: Neuroimage doi: 10.1016/j.neuroimage.2006.02.048 – volume: 56 start-page: 616 year: 2011 ident: e_1_3_4_18_2 article-title: Decoding brain states from fMRI connectivity graphs publication-title: Neuroimage doi: 10.1016/j.neuroimage.2010.05.081 – volume: 80 start-page: 527 year: 2013 ident: e_1_3_4_3_2 article-title: Clinical applications of the functional connectome publication-title: Neuroimage doi: 10.1016/j.neuroimage.2013.04.083 – volume: 33 start-page: 1914 year: 2012 ident: e_1_3_4_26_2 article-title: A whole brain fMRI atlas generated via spatially constrained spectral clustering publication-title: Hum Brain Mapp doi: 10.1002/hbm.21333 – volume: 23 start-page: 013142 year: 2013 ident: e_1_3_4_14_2 article-title: Robust detection of dynamic community structure in networks publication-title: Chaos doi: 10.1063/1.4790830 – volume: 60 start-page: 2062 year: 2012 ident: e_1_3_4_35_2 article-title: Spatiotemporal dynamics of the brain at rest: Exploring EEG microstates as electrophysiological signatures of BOLD resting state networks publication-title: Neuroimage doi: 10.1016/j.neuroimage.2012.02.031 – volume: 50 start-page: 81 year: 2010 ident: e_1_3_4_5_2 article-title: Time-frequency dynamics of resting-state brain connectivity measured with fMRI publication-title: Neuroimage doi: 10.1016/j.neuroimage.2009.12.011 – volume: 110 start-page: 16277 year: 2013 ident: e_1_3_4_31_2 article-title: Network structure and dynamics of the mental workspace publication-title: Proc Natl Acad Sci USA doi: 10.1073/pnas.1311149110 – volume: 44 start-page: 857 year: 2009 ident: e_1_3_4_47_2 article-title: Influence of heart rate on the BOLD signal: The cardiac response function publication-title: Neuroimage doi: 10.1016/j.neuroimage.2008.09.029 – volume: 67 start-page: 163 year: 2013 ident: e_1_3_4_49_2 article-title: Effects of image contrast on functional MRI image registration publication-title: Neuroimage doi: 10.1016/j.neuroimage.2012.10.076 – volume: 80 start-page: 360 year: 2013 ident: e_1_3_4_4_2 article-title: Dynamic functional connectivity: Promise, issues, and interpretations publication-title: Neuroimage doi: 10.1016/j.neuroimage.2013.05.079 – volume: 52 start-page: 1162 year: 2010 ident: e_1_3_4_34_2 article-title: BOLD correlates of EEG topography reveal rapid resting-state network dynamics publication-title: Neuroimage doi: 10.1016/j.neuroimage.2010.02.052 – volume: 106 start-page: 13040 year: 2009 ident: e_1_3_4_1_2 article-title: Correspondence of the brain’s functional architecture during activation and rest publication-title: Proc Natl Acad Sci USA doi: 10.1073/pnas.0905267106 – volume: 84 start-page: 262 year: 2014 ident: e_1_3_4_16_2 article-title: The chronnectome: Time-varying connectivity networks as the next frontier in fMRI data discovery publication-title: Neuron doi: 10.1016/j.neuron.2014.10.015 – volume: 33 start-page: 833 year: 2012 ident: e_1_3_4_2_2 article-title: Investigation of long-term reproducibility of intrinsic connectivity network mapping: A resting-state fMRI study publication-title: AJNR Am J Neuroradiol doi: 10.3174/ajnr.A2894 – volume: 148 start-page: 299 year: 2010 ident: e_1_3_4_22_2 article-title: Information integration: Its relevance to brain function and consciousness publication-title: Arch Ital Biol – volume: 9 start-page: e85929 year: 2014 ident: e_1_3_4_27_2 article-title: Windowed correlation: A suitable tool for providing dynamic fMRI-based functional connectivity neurofeedback on task difficulty publication-title: PLoS ONE doi: 10.1371/journal.pone.0085929 – volume: 61 start-page: 907 year: 2012 ident: e_1_3_4_29_2 article-title: Dynamic connectivity regression: Determining state-related changes in brain connectivity publication-title: Neuroimage doi: 10.1016/j.neuroimage.2012.03.070 – volume: 8 start-page: e1002441 year: 2012 ident: e_1_3_4_28_2 article-title: Decoding unattended fearful faces with whole-brain correlations: An approach to identify condition-dependent large-scale functional connectivity publication-title: PLOS Comput Biol doi: 10.1371/journal.pcbi.1002441 – volume: 81 start-page: 565 year: 2010 ident: e_1_3_4_23_2 article-title: The resting state questionnaire: An introspective questionnaire for evaluation of inner experience during the conscious resting state publication-title: Brain Res Bull doi: 10.1016/j.brainresbull.2009.11.014 – volume: 104 start-page: 430 year: 2015 ident: e_1_3_4_39_2 article-title: On spurious and real fluctuations of dynamic functional connectivity during rest publication-title: Neuroimage doi: 10.1016/j.neuroimage.2014.09.007 – volume: 2014 start-page: bhu255 year: 2014 ident: e_1_3_4_37_2 article-title: Identification of mood-relevant brain connections using a continuous, subject-driven rumination paradigm publication-title: Cereb Cortex – volume: 8 start-page: 665 year: 2011 ident: e_1_3_4_38_2 article-title: Large-scale automated synthesis of human functional neuroimaging data publication-title: Nat Methods doi: 10.1038/nmeth.1635 – volume: 83 start-page: 826 year: 2013 ident: e_1_3_4_12_2 article-title: Neural correlates of time-varying functional connectivity in the rat publication-title: Neuroimage doi: 10.1016/j.neuroimage.2013.07.036 – volume: 109 start-page: 3131 year: 2012 ident: e_1_3_4_7_2 article-title: Temporally-independent functional modes of spontaneous brain activity publication-title: Proc Natl Acad Sci USA doi: 10.1073/pnas.1121329109 |
| SSID | ssj0009580 |
| Score | 2.5956483 |
| Snippet | Functional connectivity (FC) patterns in functional MRI exhibit dynamic behavior on the scale of seconds, with rich spatiotemporal structure and limited sets... Recently, it was shown that functional connectivity patterns exhibit complex spatiotemporal dynamics at the scale of tens of seconds. Of particular interest is... |
| SourceID | pubmedcentral proquest pubmed crossref pnas jstor fao |
| SourceType | Open Access Repository Aggregation Database Index Database Enrichment Source Publisher |
| StartPage | 8762 |
| SubjectTerms | Accuracy Behavior Biological Sciences Brain Brain - physiology classification Cognition Cognition & reasoning cognitive states connectivity dynamics fMRI functional connectivity states Humans Information processing Magnetic Resonance Imaging |
| Title | Tracking ongoing cognition in individuals using brief, whole-brain functional connectivity patterns |
| URI | https://www.jstor.org/stable/26466035 http://www.pnas.org/content/112/28/8762.abstract https://www.ncbi.nlm.nih.gov/pubmed/26124112 https://www.proquest.com/docview/1697797216 https://www.proquest.com/docview/1697215751 https://www.proquest.com/docview/1709171237 https://www.proquest.com/docview/1817834638 https://pubmed.ncbi.nlm.nih.gov/PMC4507216 |
| Volume | 112 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV3da9RAEF-u9cUXsWpttEoEHypnziSbz8dyVIvQo2AP-xaym831qOaO-6Bw_4z_qjP7lVxtiwpHOJLNJmR-mZmdzPyGkPc0ZGAX0trza5p4UUVTjzHBvLgswX1N4jhLsHb4bJScjqOvl_Flr_erk7W0XrEB39xZV_I_UoV9IFeskv0HydpJYQf8B_nCFiQM27-T8aLk1zJtuZnMVPWsTAZS6YtTW2u17K9lSIDBuliSMN5gV1yPYXuIPlo2HRDkmPXCdT-JuWTe1ME87b6eW3O3NMkFIxNNPG5rU7TCWPa9_vmo7XT8ZdZswB5tvGEJisV89CnRMlt0qdDgEFsJ9b-36rGpbsRCJ4Coqvg2CNstYTsTkyvQWCfdYEYQY5RUFZEOhFLA4L94SaRaiFoNHYQdKOpi8qW21kqZ_2EJQHVh--KmXA7A5w3wy3ewNRJEOf8pgYEsapG5xjb5tjm0Qx6FsA6hJhxkWZ0z3_BFpfTTrash0bQ-f8vr2anLmUl_RU5dOOuu9c3tNN2O33PxlDzRCxb3WKFvj_RE84zsGQm7R5q3_MNzwg0cXQ1H18LRneLPwtGVcHQlHD-6HTC6LRjdLhhdA8YXZPz55GJ46ukeHh4Hx3rlgfdLI1ZmglZlnsV5IrKAM8poyUIRpZHPfc7ioBZ1DHhIBagHZCwMfZpXQoBvvU92m1kjDohL_VqEYVXxSvAohEVhlgiR1T6L8iCPwsghA_OMC64J7rHPyo9CJlqktMAnXbTycciRPWGuuF3uH3oAQivKCVjeYvwtRF5GH284zh2yLyVpp4AlRpL4NIZz5Cx26iAswqxAxDrk0Ii70PoErpbAWkySaTnknT0M2h4_4ZWNmK3VGHDS0zh4YEwK71AKHmn6wJgswA47YHwd8lKhrHP_CrMOSbfwZwcgI_32kWZ6JZnpoxjpFpNX9875mjxuX_tDsrtarMUb8OpX7K18s34DkVz3ew |
| linkProvider | National Library of Medicine |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Tracking+ongoing+cognition+in+individuals+using+brief%2C+whole-brain+functional+connectivity+patterns&rft.jtitle=Proceedings+of+the+National+Academy+of+Sciences+-+PNAS&rft.au=Gonzalez-Castillo%2C+Javier&rft.au=Hoy%2C+Colin+W&rft.au=Handwerker%2C+Daniel+A&rft.au=Robinson%2C+Meghan+E&rft.date=2015-07-14&rft.eissn=1091-6490&rft.volume=112&rft.issue=28&rft.spage=8762&rft_id=info:doi/10.1073%2Fpnas.1501242112&rft_id=info%3Apmid%2F26124112&rft.externalDocID=26124112 |
| thumbnail_m | http://utb.summon.serialssolutions.com/2.0.0/image/custom?url=http%3A%2F%2Fwww.pnas.org%2Fcontent%2F112%2F28.cover.gif |
| thumbnail_s | http://utb.summon.serialssolutions.com/2.0.0/image/custom?url=http%3A%2F%2Fwww.pnas.org%2Fcontent%2F112%2F28.cover.gif |