The DOI matches its Crossref record; 67 of the 67 references it cites were found in a registry or an index.
Posteromedial cortex glutamate and GABA predict intrinsic functional connectivity of the default mode network
Open accessAbstract
The balance between excitatory glutamatergic projection neurons and inhibitory GABAergic interneurons determines the function of cortical microcircuits. How these neurotransmitters relate to the functional status of an entire macro-scale network remains unknown. The posteromedial cortex (PMC) is the default mode network (DMN) node with the greatest functional connectivity; therefore, we hypothesized that PMC glutamate and GABA predict intrinsic functional connectivity (iFC) across the entire DMN. In 20 healthy men, we combined J-resolved magnetic resonance spectroscopy to measure glutamate and GABA in the PMC and resting fMRI followed by group Independent Components Analysis to extract the entire DMN. We showed that, controlling for age and partial GM volume in the MRS voxel, PMC glutamate and GABA explained about half of the variance of DMN iFC (represented by the network's beta coefficient for rest). Glutamate correlated positively and GABA correlated negatively with DMN iFC; in an alternative statistical model which included the glutamate/GABA ratio, the ratio correlated positively with DMN iFC. Age had no independent association with DMN iFC. No other network was associated with PMC glutamate or GABA. We conclude that regional neurotransmitter concentrations in a network node strongly predict network but not global brain iFC.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“Higher resting state GABA levels in the DMN are associated with enhanced task-induced deactivation of this network [165–167]”
From Apolipoprotein E4, inhibitory network dysfunction, and Alzheimer’s disease (2019) · cites this paper as [166]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Complex brain networks: graph theoretical analysis of structural and functional systems
Bullmore, E., & Sporns, O. (2009) · Nature Reviews Neuroscience · doi:10.1038/nrn2575 · Cited by 11,820
The Brain's Default Network: Anatomy, Function, and Relevance to Disease
Buckner, R. L., Andrews‐Hanna, J. R., & Schacter, D. L. (2008) · Annals of the New York Academy of Sciences · doi:10.1196/annals.1440.011 · Cited by 9,761
A fast diffeomorphic image registration algorithm
Ashburner, J. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.07.007 · Cited by 8,122
A theory of cortical responses.
Friston, K. (2005) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2005.1622 · Cited by 4,578
Mapping the structural core of human cerebral cortex
Hagmann, P., Cammoun, L., Gigandet, X., Meuli, R., Honey, C. J., Wedeen, V. J., & Sporns, O. (2008) · PLoS Biology · doi:10.1371/journal.pbio.0060159 · Cited by 4,173
Estimation of metabolite concentrations from localized in vivo proton NMR spectra
Provencher, S. W. (1993) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910300604 · Cited by 3,659
What we can do and what we cannot do with fMRI
Logothetis, N. K. (2008) · Nature · doi:10.1038/nature06976 · Cited by 3,612
Buckner, R. L., Sepulcre, J., Talukdar, T., Krienen, F. M., Liu, H., Hedden, T., Andrews-Hanna, J. R., Sperling, R. A., & Johnson, K. A. (2009) · The Journal of Neuroscience · doi:10.1523/jneurosci.5062-08.2009 · Cited by 2,862
Region of interest analysis using an SPM toolbox
Brett, M. (2002) · NeuroImage · Cited by 2,273
Resting-State Functional Connectivity Reflects Structural Connectivity in the Default Mode Network
Greicius, M. D., Supekar, K., Menon, V., & Dougherty, R. F. (2009) · Cerebral Cortex · doi:10.1093/cercor/bhn059 · Cited by 2,175
Cited by
Sorted by citations
Lener, M. S., Niciu, M. J., Ballard, E. D., Park, M., Park, L. T., Nugent, A. C., & Zarate, C. A. (2017) · Biological Psychiatry · doi:10.1016/j.biopsych.2016.05.005 · Cited by 468
Brain default-mode network dysfunction in addiction
Zhang, R., & Volkow, N. D. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.06.036 · Cited by 386
Fee, C., Banasr, M., & Sibille, E. (2017) · Biological Psychiatry · doi:10.1016/j.biopsych.2017.05.024 · Cited by 329
Ketamine has distinct electrophysiological and behavioral effects in depressed and healthy subjects
Nugent, A. C., Ballard, E. D., Gould, T. D., Park, L. T., Moaddel, R., Brutsche, N. E., & Zarate, C. A. (2019) · Molecular Psychiatry · doi:10.1038/s41380-018-0028-2 · Cited by 250
Bachtiar, V., Near, J., Johansen‐Berg, H., & Stagg, C. J. (2015) · eLife · doi:10.7554/elife.08789 · Cited by 261
Meda, S. A., Ruaño, G., Windemuth, A., O’Neil, K., Berwise, C., Dunn, S. M., Boccaccio, L. E., Narayanan, B., Kocherla, M., Sprooten, E., et al. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1313093111 · Cited by 242
Duncan, N. W., Wiebking, C., & Northoff, G. (2014) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2014.07.016 · Cited by 230
Insulin Resistance as a Link between Amyloid-Beta and Tau Pathologies in Alzheimer’s Disease
Mullins, R. J., Diehl, T. C., Chia, C. W., & Kapogiannis, D. (2017) · Frontiers in Aging Neuroscience · doi:10.3389/fnagi.2017.00118 · Cited by 227
Self-citationLocal GABA concentration is related to network-level resting functional connectivity
Stagg, C. J., Bachtiar, V., Amadi, U., Gudberg, C., Ilie, A. S., Sampaio‐Baptista, C., O’Shea, J., Woolrich, M. W., Smith, S. M., Filippini, N., et al. (2014) · eLife · doi:10.7554/elife.01465 · Cited by 222
EEG hyper-connectivity in high-risk infants is associated with later autism
The BASIS Team, Orekhova, E. V., Elsabbagh, M., Jones, E. J., Dawson, G., Charman, T., & Johnson, M. H. (2014) · Journal of Neurodevelopmental Disorders · doi:10.1186/1866-1955-6-40 · Cited by 210
As-Sanie, S., Kim, J., Schmidt-Wilcke, T., Sundgren, P. C., Clauw, D. J., Napadow, V., & Harris, R. E. (2016) · The Journal of Pain · doi:10.1016/j.jpain.2015.09.008 · Cited by 199
Jiménez-Baladó, J., & Eich, T. S. (2021) · Seminars in Cell and Developmental Biology · doi:10.1016/j.semcdb.2021.01.005 · Cited by 194
Big GABA: Edited MR spectroscopy at 24 research sites
Mikkelsen, M. E., Barker, P. B., Bhattacharyya, P. K., Brix, M. K., Buur, P. F., Cecil, K. M., Chan, K. L., Chen, D. Y. T., Craven, A. R., Cuypers, K., et al. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.07.021 · Cited by 184
Apolipoprotein E4, inhibitory network dysfunction, and Alzheimer’s disease
Najm, R., Jones, E. A., & Huang, Y. (2019) · Molecular Neurodegeneration · doi:10.1186/s13024-019-0324-6 · Cited by 183
Hu, Y., Chen, X., Gu, H., & Yang, Y. (2013) · The Journal of Neuroscience · doi:10.1523/jneurosci.1973-13.2013 · Cited by 167
Neuroimaging of Parkinson's disease: Expanding views
Weingarten, C. P., Sundman, M. H., Hickey, P., & Chen, N. (2015) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2015.09.007 · Cited by 164
Neural Noise Hypothesis of Developmental Dyslexia
Hancock, R., Pugh, K. R., & Hoeft, F. (2017) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2017.03.008 · Cited by 176
Cassady, K. E., Gagnon, H. C., Lalwani, P., Simmonite, M., Foerster, B. R., Park, D. C., Peltier, S., Petrou, M., Taylor, S. F., Weissman, D. H., et al. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.11.008 · Cited by 156
Northoff, G., & Sibille, E. L. (2014) · Molecular Psychiatry · doi:10.1038/mp.2014.68 · Cited by 148
tDCS-Induced Modulation of GABA Levels and Resting-State Functional Connectivity in Older Adults
Antonenko, D., Schubert, F., Bohm, F., Ittermann, B., Aydın, S., Hayek, D., Grittner, U., & Flöel, A. (2017) · Journal of Neuroscience · doi:10.1523/jneurosci.0079-17.2017 · Cited by 151
Changing Brain Networks Through Non-invasive Neuromodulation
To, W. T., De Ridder, D., Hart Jr., J., & Vanneste, S. (2018) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2018.00128 · Cited by 135
“…are increased by tDCS (Clark et al., 2011) and that there is a strong relationship between Glx and functional connectivity (Horn et al., 2010; Kapogiannis et al., 2013), Frontiers in Human Neuroscience | www.frontiersin.org 5 April 2018 | Volume 12 | Article 128 studies have been…”
BackgroundHunter, M. A., Coffman, B. A., Gasparovic, C., Calhoun, V. D., Trumbo, M., & Clark, V. P. (2014) · Brain Research · doi:10.1016/j.brainres.2014.09.066 · Cited by 140
Di, X., Kim, E. H., Huang, C., Tsai, S., Lin, C., & Biswal, B. B. (2013) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2013.00118 · Cited by 119
Changes in functional connectivity and GABA levels with long-term motor learning
Sampaio‐Baptista, C., Filippini, N., Stagg, C. J., Near, J., Scholz, J., & Johansen‐Berg, H. (2014) · NeuroImage · doi:10.1016/j.neuroimage.2014.11.032 · Cited by 119
Magnetic resonance spectroscopy reveals abnormalities of glucose metabolism in the Alzheimer's brain
Mullins, R. J., Reiter, D. A., & Kapogiannis, D. (2018) · Annals of Clinical and Translational Neurology · doi:10.1002/acn3.530 · Cited by 98
Self-citationDeligiannidis, K. M., Fales, C. L., Kroll-Desrosiers, A. R., Shaffer, S. A., Villamarin, V., Tan, Y., Hall, J. E., Frederick, B. B., Sikoglu, E. M., Edden, R. A., et al. (2019) · Neuropsychopharmacology · doi:10.1038/s41386-018-0242-2 · Cited by 92
Napadow, V., & Harris, R. E. (2014) · Arthritis Research & Therapy · doi:10.1186/s13075-014-0425-0 · Cited by 92
Multiscale Neuroscience of Psychiatric Disorders
van den Heuvel, M. P., Scholtens, L. H., & Kahn, R. S. (2019) · Biological Psychiatry · doi:10.1016/j.biopsych.2019.05.015 · Cited by 79
The role of inhibition in human motor cortical plasticity
Bachtiar, V., & Stagg, C. J. (2014) · Neuroscience · doi:10.1016/j.neuroscience.2014.07.059 · Cited by 79
Regional balance between glutamate+glutamine and GABA+ in the resting human brain
Steel, A., Mikkelsen, M. E., Edden, R. A. E., & Robertson, C. E. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117112 · Cited by 70
Regional GABA Concentrations Modulate Inter-network Resting-state Functional Connectivity
Chen, X., Fan, X., Hu, Y., Zuo, C., Whitfield-Gabrieli, S., Holt, D., Gong, Q., Yang, Y., Pizzagalli, D. A., Du, F., et al. (2019) · Cerebral Cortex · doi:10.1093/cercor/bhy059 · Cited by 62
GABA, Resting-State Connectivity and the Developing Brain
Kwon, S. H., Scheinost, D., Lacadie, C., Benjamin, J. R., Myers, E. H., Qiu, M., Schneider, K. C., Rothman, D. L., Constable, R. T., & Ment, L. R. (2014) · Neonatology · doi:10.1159/000362433 · Cited by 62
Learning to optimize perceptual decisions through suppressive interactions in the human brain
Frangou, P., Emir, U. E., Karlaftis, V. M., Nettekoven, C., Hinson, E. L., Larcombe, S. J., Bridge, H., Stagg, C. J., & Kourtzi, Z. (2019) · Nature Communications · doi:10.1038/s41467-019-08313-y · Cited by 63
Impact of glutamate levels on neuronal response and cognitive abilities in schizophrenia
Falkenberg, L. E., Westerhausen, R., Craven, A. R., Johnsen, E., Kroken, R. A., L⊘berg, E.-M., Specht, K., & Hugdahl, K. (2014) · NeuroImage Clinical · doi:10.1016/j.nicl.2014.03.014 · Cited by 59
McGirr, A., LeDue, J. M., Chan, A. W., Xie, Y., & Murphy, T. H. (2017) · Brain · doi:10.1093/brain/awx142 · Cited by 60
Gu, H., Hu, Y., Chen, X., Yong He, A., & Yang, Y. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.10.055 · Cited by 59
Ghisleni, C., Bollmann, S., Poil, S., Brandeis, D., Martin, E., Michels, L., Tuura, R., & Klaver, P. (2015) · Journal of Neuroscience · doi:10.1523/jneurosci.4375-14.2015 · Cited by 56
Upregulation of cortical GABAA receptor concentration in fibromyalgia
Pomares, F. B., Roy, S., Funck, T., Feier, N. A., Thiel, A., Fitzcharles, M., & Schweinhardt, P. (2019) · Pain · doi:10.1097/j.pain.0000000000001707 · Cited by 55
The impact of a lack of mathematical education on brain development and future attainment
Zacharopoulos, G., Sella, F., & Kadosh, R. C. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2013155118 · Cited by 68
Anterior Cingulate Glutamate and GABA Associations on Functional Connectivity in Schizophrenia
Shukla, D. K., Wijtenburg, S. A., Chen, H., Chiappelli, J., Kochunov, P., Hong, L. E., & Rowland, L. M. (2018) · Schizophrenia Bulletin · doi:10.1093/schbul/sby075 · Cited by 52
Hyper-connectivity of the thalamus during early stages following mild traumatic brain injury
Sours, C., George, E. O., Zhuo, J., Roys, S., & Gullapalli, R. P. (2015) · Brain Imaging and Behavior · doi:10.1007/s11682-015-9424-2 · Cited by 52
Kraguljac, N. V., White, D. M., Hadley, J. A., Reid, M. A., & Lahti, A. C. (2014) · Hippocampus · doi:10.1002/hipo.22332 · Cited by 54
Bolo, N. R., Musen, G., Simonson, D. C., Nickerson, L. D. H., Flores, V. L., Siracusa, T., Hager, B. M., Lyoo, I. K., Renshaw, P. F., & Jacobson, A. M. (2015) · Journal of Neuroscience · doi:10.1523/jneurosci.0319-15.2015 · Cited by 53
Vidal-Piñeiro, D., Martín-Trias, P., Falcón, C., Bargalló, N., Clemente, I. C., Valls-Solé, J., Junqué, C., Pascual-Leone, A., & Bartrés-Faz, D. (2015) · Brain Stimulation · doi:10.1016/j.brs.2015.04.005 · Cited by 49
Willette, A. A., Calhoun, V. D., Egan, J. M., & Kapogiannis, D. (2014) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2014.08.005 · Cited by 52
Self-citationMoeller, S. J., London, E. D., & Northoff, G. (2015) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2015.11.010 · Cited by 50
Reckziegel, D., Raschke, F., Cottam, W. J., & Auer, D. P. (2016) · Molecular Pain · doi:10.1177/1744806916650690 · Cited by 51
Nasrallah, F. A., Lew, S. K., Low, A. S.-M., & Chuang, K. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.08.004 · Cited by 45
Naskar, A., Vattikonda, A. N., Deco, G., Roy, D., & Banerjee, A. (2021) · Network Neuroscience · doi:10.1162/netn_a_00197 · Cited by 42
Huang, Z., Davis Iv, H. H., Yue, Q., Wiebking, C., Duncan, N. W., Zhang, J., Wagner, N.-F., Wolff, A., & Northoff, G. (2015) · Human Brain Mapping · doi:10.1002/hbm.22841 · Cited by 43
Poletti, S., Riberto, M., Vai, B., Ghiglino, D., Lorenzi, C., Vitali, A., Brioschi, S., Locatelli, C., Serretti, A., Colombo, C., et al. (2018) · Journal of Molecular Neuroscience · doi:10.1007/s12031-018-1138-7 · Cited by 43
Non-Invasive Brain Stimulation in Dementia: A Complex Network Story
Pini, L., Manenti, R., Cotelli, M., Pizzini, F. B., Frisoni, G. B., & Pievani, M. (2018) · Neurodegenerative Diseases · doi:10.1159/000495945 · Cited by 41
Levar, N., van Doesum, T., Denys, D. A. J. P., & van Wingen, G. A. (2019) · Scientific Reports · doi:10.1038/s41598-018-38078-1 · Cited by 41
Nugent, A. C., Robinson, S. E., Coppola, R., & Zarate, C. A. (2016) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2016.06.006 · Cited by 42
Nantes, J. C., Proulx, S., zhong, J., Holmes, S. A., Narayanan, S., Brown, R. A., Hoge, R. D., & Koski, L. M. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.01.033 · Cited by 43
Default Mode Network Maturation and Environmental Adversities During Childhood
Rebello, K., Moura, L. M., Pinaya, W. H. L., Rohde, L. A., & Sato, J. R. (2018) · Chronic Stress · doi:10.1177/2470547018808295 · Cited by 46
van den Heuvel, M. P., Scholtens, L. H., Turk, E., Mantini, D., Vanduffel, W., & Barrett, L. F. (2016) · Human Brain Mapping · doi:10.1002/hbm.23229 · Cited by 40
Gao, F., Yin, X., Edden, R. A. E., Evans, A. C., Xu, J., Cao, G., Li, H., Li, M., Zhao, B., Wang, J., et al. (2018) · Hippocampus · doi:10.1002/hipo.23001 · Cited by 42
Wagner, G., Gussew, A., Köhler, S., de la Cruz, F., Smesny, S., Reichenbach, J. R., & Bär, K. (2016) · Cortex · doi:10.1016/j.cortex.2016.03.022 · Cited by 40
Avgerinos, K. I., Mullins, R. J., Vreones, M. P., Mustapić, M., Chen, Q., Melvin, D. L., Kapogiannis, D., & Egan, J. M. (2022) · Cells · doi:10.3390/cells11213372 · Cited by 41
Self-citationGABA concentrations in the anterior temporal lobe predict human semantic processing
Jung, J., Williams, S. R., Nezhad, F. S., & Ralph, M. A. L. (2017) · Scientific Reports · doi:10.1038/s41598-017-15981-7 · Cited by 45
Haag, L. M., Quetscher, C., Dharmadhikari, S., Dydak, U., Schmidt‐Wilcke, T., & Beste, C. (2015) · Human Brain Mapping · doi:10.1002/hbm.22920 · Cited by 37
Ritchay, M. M., Huggins, A. A., Wallace, A. L., Larson, C. L., & Lisdahl, K. M. (2021) · NeuroImage Clinical · doi:10.1016/j.nicl.2021.102664 · Cited by 36
Pizzi, S. D., Chiacchiaretta, P., Mantini, D., Bubbico, G., Edden, R. A. E., ONOFRJ, M. C., Ferretti, A., & Bonanni, L. (2017) · Brain Structure and Function · doi:10.1007/s00429-017-1399-x · Cited by 37
Functional disruption in prefrontal-striatal network in obsessive-compulsive disorder
Sha, Z., Versace, A., Edmiston, E. K., Fournier, J. C. J., Graur, S., Greenberg, T., Santos, J. P. L., Chase, H. W., Stiffler, R. S., Bonar, L. K., et al. (2020) · Psychiatry Research Neuroimaging · doi:10.1016/j.pscychresns.2020.111081 · Cited by 41
Pretzsch, C. M., Floris, D. L., Voinescu, B., Elsahib, M., Méndez, M. A., Wichers, R., Ajram, L. A., Ivin, G., Heasman, M., Pretzsch, E., et al. (2021) · Molecular Autism · doi:10.1186/s13229-021-00454-6 · Cited by 35
On the relationship between GABA+ and glutamate across the brain
Rideaux, R., Ehrhardt, S. E., Wards, Y., Filmer, H. L., Jin, J., Deelchand, D. K., Marjańska, M., Mattingley, J. B., & Dux, P. E. (2022) · NeuroImage · doi:10.1016/j.neuroimage.2022.119273 · Cited by 38
Koush, Y., Rothman, D. L., Behar, K. L., de Graaf, R. A., & Hyder, F. (2022) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1177/0271678x221076570 · Cited by 36
Marsman, A., Mandl, R. C. W., Klomp, D. W. J., Cahn, W., Kahn, R. S., Luijten, P. R., & Pol, H. E. H. (2017) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2017.00154 · Cited by 38
Parrella, N.-F., Hill, A. T., Dipnall, L. M., Loke, Y. J., Enticott, P. G., & Ford, T. C. (2023) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2023.11.014 · Cited by 33
Zachariou, V., Bauer, C. E., Seago, E. R., Raslau, F. D., Powell, D. K., & Gold, B. T. (2020) · NeuroImage · doi:10.1016/j.neuroimage.2020.117309 · Cited by 33
Mattiaccio, L. M., Coman, I. L., Schreiner, M. J., Antshel, K. M., Fremont, W. P., Bearden, C. E., & Kates, W. R. (2016) · Journal of Neurodevelopmental Disorders · doi:10.1186/s11689-016-9135-z · Cited by 32
Just, N., & Sonnay, S. (2017) · Frontiers in Physiology · doi:10.3389/fphys.2017.00030 · Cited by 30
Myers, J. F., Evans, J., Kalk, N. J., Edden, R. A. E., & Lingford-Hughes, A. R. (2014) · Synapse · doi:10.1002/syn.21747 · Cited by 30
Shah, N. J., Arrubla, J., Rajkumar, R., Farrher, E., Mauler, J., Kops, E. R., Tellmann, L., Scheins, J. J., Boers, F., Dammers, J., et al. (2017) · Scientific Reports · doi:10.1038/s41598-017-05484-w · Cited by 30
Intrinsic Connectivity Networks of Glutamate-Mediated Antidepressant Response: A Neuroimaging Review
Demchenko, I., Tassone, V. K., Kennedy, S. H., Dunlop, K., & Bhat, V. (2022) · Frontiers in Psychiatry · doi:10.3389/fpsyt.2022.864902 · Cited by 29
“1H-MRS studies have demonstrated an association between altered metrics corresponding to glutamate levels and functional changes in the nodes of the DMN (108, 109, 112, 117), AN (118–123), RN (124, 125), CEN (126, 127), SN (98, 110, 116, 128), SMN (129), and CAN (130).”
BackgroundPredicting learning and achievement using GABA and glutamate concentrations in human development
Zacharopoulos, G., Sella, F., Kadosh, K. C., Hartwright, C. E., Emir, U. E., & Kadosh, R. C. (2021) · PLoS Biology · doi:10.1371/journal.pbio.3001325 · Cited by 31
Maximo, J. O., Briend, F., Armstrong, W. P., Kraguljac, N. V., & Lahti, A. C. (2021) · NeuroImage Clinical · doi:10.1016/j.nicl.2021.102845 · Cited by 29
Modulatory Interactions of Resting-State Brain Functional Connectivity
Di, X., & Biswal, B. B. (2013) · PLoS ONE · doi:10.1371/journal.pone.0071163 · Cited by 29
P osterior dopamine D2/3 receptors and brain network functional connectivity
Nagano‐Saito, A., Lissemore, J. I., Gravel, P., Leyton, M., Carbonell, F., & Benkelfat, C. (2017) · Synapse · doi:10.1002/syn.21993 · Cited by 29
Turk, E., Scholtens, L. H., & van den Heuvel, M. P. (2016) · Human Brain Mapping · doi:10.1002/hbm.23141 · Cited by 27
Kanagasabai, K., Palaniyappan, L. K., & Théberge, J. (2023) · NMR in Biomedicine · doi:10.1002/nbm.5071 · Cited by 27
Chen, Y., & Zhang, J. (2021) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2021.648860 · Cited by 39
GABA Concentration in Posterior Cingulate Cortex Predicts Putamen Response during Resting State fMRI
Arrubla, J., Tse, D. H. Y., Amkreutz, C., Neuner, I., & Shah, N. J. (2014) · PLoS ONE · doi:10.1371/journal.pone.0106609 · Cited by 27
Cleve, M., Gussew, A., Wagner, G., Bär, K., & Reichenbach, J. R. (2017) · Neuroscience · doi:10.1016/j.neuroscience.2017.09.037 · Cited by 27
Cognitive function: holarchy or holacracy?
Bîrle, C., Slăvoacă, D., Balea, M., Popa, L. L., Mureșanu, I. A., Ștefănescu, E., Văcăraș, V., Dina, C., Strilciuc, Ș., Popescu, B. O., et al. (2020) · Neurological Sciences · doi:10.1007/s10072-020-04737-3 · Cited by 36
Dynamic Recovery: GABA Agonism Restores Neural Variability in Older, Poorer Performing Adults
Lalwani, P., Garrett, D. D., & Polk, T. A. (2021) · Journal of Neuroscience · doi:10.1523/jneurosci.0335-21.2021 · Cited by 22
Su, Y. Y., Zhang, X. D., Schoepf, U. J., Varga‐Szemes, Á., Stubenrauch, A. C., Liang, X., Zheng, L. J., Zheng, G., Kong, X., Xu, Q., et al. (2016) · Brain Imaging and Behavior · doi:10.1007/s11682-016-9556-z · Cited by 25
Pini, L., Salvalaggio, A., Wennberg, A. M. V., Dimakou, A., Matteoli, M., & Corbetta, M. (2023) · Ageing Research Reviews · doi:10.1016/j.arr.2023.101867 · Cited by 26
Schreiner, S. J., Kirchner, T., Wyss, M., Bergen, J. M. G. V., Quevenco, F. C., Steininger, S. C., Griffith, E. Y., Meier, I. B., Michels, L., Gietl, A. F., et al. (2016) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2016.08.022 · Cited by 25
GABAergic effect on resting-state functional connectivity: Dynamics under pharmacological antagonism
Nasrallah, F. A., Singh, K. K. D. O. R., Yeow, L. Y., & Chuang, K. (2017) · NeuroImage · doi:10.1016/j.neuroimage.2017.01.040 · Cited by 27
Pizzi, S. D., Franciotti, R., Ferretti, A., Edden, R. A. E., Zöllner, H. J., Esposito, R., Bubbico, G., Aiello, C., Calvanese, F., Sensi, S. L., et al. (2020) · Movement Disorders · doi:10.1002/mds.28221 · Cited by 22
Rideaux, R. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118191 · Cited by 26
Ironside, M., Moser, A. D., Holsen, L. M., Zuo, C. S., Du, F., Perlo, S., Richards, C. E., Duda, J. M., Chen, X., Nickerson, L. D. H., et al. (2021) · Neuropsychopharmacology · doi:10.1038/s41386-021-01127-x · Cited by 23
Mawla, I., Huang, Z., Kaplan, C. M., Ichesco, E., Waller, N., Larkin, T. E., Zöllner, H. J., Edden, R. A. E., Harte, S. E., Clauw, D. J., et al. (2023) · Pain · doi:10.1097/j.pain.0000000000002973 · Cited by 27
Plasticity–stability dynamics during post-training processing of learning
Yamada, T., Watanabe, T., & Sasaki, Y. (2023) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2023.09.002 · Cited by 23
Degnan, A. J., Ceschin, R. C., Lee, V., Schmithorst, V. J., Blüml, S., & Panigrahy, A. (2014) · The Journal of Comparative Neurology · doi:10.1002/cne.23634 · Cited by 22
Čolić, L., Li, M., Demenescu, L. R., Li, S., Müller, I., Richter, A., Behnisch, G., Seidenbecher, C. I., Speck, O., Schott, B. H., et al. (2018) · Journal of Neuroscience · doi:10.1523/jneurosci.1985-17.2018 · Cited by 22
Qin, P., Duncan, N. W., Wiebking, C., Gravel, P., Lyttelton, O. C., Hayes, D. J., Verhaeghe, J. A. J., Kostikov, A. P., Schirrmacher, R., Reader, A. J., et al. (2012) · Frontiers in Human Neuroscience · doi:10.3389/fnhum.2012.00337 · Cited by 22
Lord, A., Li, M., Demenescu, L. R., van der Meer, J. N., Borchardt, V., Krause, A. L., Heinze, H., Breakspear, M. J., & Walter, M. (2017) · Frontiers in Neuroscience · doi:10.3389/fnins.2017.00184 · Cited by 23
Metadata
- Authors
- Kapogiannis, D., Reiter, D. A., Willette, A. A., & Mattson, M. P.
- Affiliations
- National Institute on Aging (US)
- Corresponding author
- Kapogiannis, Dimitrios
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2013-01
- Volume
- 64
- Pages
- 112-119
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC3801193
- OpenAlex
- W1971032414
- Cited by
- 211
- References
- 67
- Citations by year
- 2026: 11 · 2025: 14 · 2024: 12 · 2023: 15 · 2022: 15 · 2021: 23 · 2020: 19 · 2019: 17 · 2018: 18 · 2017: 19 · 2016: 14 · 2015: 11 · 2014: 18 · 2013: 4
- FWCI
- 5.57
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute on Aging
- National Institutes of Health
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
- Keywords
- posteromedial cortex, default mode network, intrinsic functional connectivity, glutamate, GABA, glutamate/GABA ratio, neurotransmitter concentrations, cortical microcircuits, excitation-inhibition balance, resting-state functional connectivity, age effects
- MeSH terms
- Brain Mapping, Cerebral Cortex, gamma-Aminobutyric Acid, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Nerve Net, Neural Pathways, Magnetic Resonance Spectroscopy, Tissue Distribution, Neurotransmitter Agents, Glutamic Acid, Connectome
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review