Posteromedial cortex glutamate and GABA predict intrinsic functional connectivity of the default mode network
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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.
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Higher resting state GABA levels in the DMN are associated with enhanced task-induced deactivation of this network.
“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]
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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 · see citing works
<i>The Brain's Default Network</i>: <i>Anatomy, Function, and Relevance to Disease</i>
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 · see citing works
A fast diffeomorphic image registration algorithm
Ashburner, J. (2007) · NeuroImage · doi:10.1016/j.neuroimage.2007.07.007 · Cited by 8,122 · see citing works
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 · see citing works
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 · see citing works
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 · see citing works
What we can do and what we cannot do with fMRI
Logothetis, N. K. (2008) · Nature · doi:10.1038/nature06976 · Cited by 3,612 · see citing works
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 · see citing works
Region of interest analysis using an SPM toolbox
Brett, M. (2002) · NeuroImage · Cited by 2,273 · see citing works
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 · see citing works
NEURONAL CIRCUITS OF THE NEOCORTEX
Douglas, R. J., & Martin, K. A. C. (2004) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.27.070203.144152 · Cited by 1,886 · see citing works
Experimentation and Uncertainty Analysis for Engineers
Coleman, H. W., Steck, W. G., & Hurlbut, F. C. (1991) · Journal of Engineering for Industry · doi:10.1115/1.2899692 · Cited by 1,811 · see citing works
Raichle, M. E., & Mintun, M. A. (2006) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.29.051605.112819 · Cited by 1,630 · see citing works
A Baseline for the Multivariate Comparison of Resting-State Networks
Allen, E. A., Erhardt, E. B., Damaraju, E., Gruner, W. E., Segall, J. M., Silva, R. F., Havlíček, M., Rachakonda, S., Fries, J. F., Kalyanam, R., et al. (2011) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2011.00002 · Cited by 1,286 · see citing works
Neurosteroids: endogenous regulators of the GABAA receptor
Belelli, D., & Lambert, J. J. (2005) · Nature reviews. Neuroscience · doi:10.1038/nrn1703 · Cited by 1,159 · see citing works
A review of group ICA for fMRI data and ICA for joint inference of imaging, genetic, and ERP data
Calhoun, V. D., Liu, J., & Adalı, T. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2008.10.057 · Cited by 1,148 · see citing works
Uddin, L. Q., Clare Kelly, A. M., Biswal, B. B., Xavier Castellanos, F., & Milham, M. P. (2009) · Human Brain Mapping · doi:10.1002/hbm.20531 · Cited by 1,135 · see citing works
Clusters of Hyperactive Neurons Near Amyloid Plaques in a Mouse Model of Alzheimer’s Disease
Busche, M. A., Eichhoff, G., Adelsberger, H., Abramowski, D., Wiederhold, K.-H., Haass, C., Staufenbiel, M., Konnerth, A., & Garaschuk, O. (2008) · Science · doi:10.1126/science.1162844 · Cited by 1,125 · see citing works
Raichle, M. E. (2010) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2010.01.008 · Cited by 1,111 · see citing works
Efficiency of Functional Brain Networks and Intellectual Performance
van den Heuvel, M. P., Stam, C. J., Kahn, R. S., & Hulshoff Pol, H. E. (2009) · Journal of Neuroscience · doi:10.1523/jneurosci.1443-09.2009 · Cited by 1,078 · see citing works
Sperling, R. A., LaViolette, P. S., O'Keefe, K., O'Brien, J., Rentz, D. M., Pihlajamaki, M., Marshall, G., Hyman, B. T., Selkoe, D. J., Hedden, T., et al. (2009) · Neuron · doi:10.1016/j.neuron.2009.07.003 · Cited by 1,027 · see citing works
Neuronal activity regulates the regional vulnerability to amyloid-β deposition
Bero, A. W., Yan, P., Roh, J. H., Cirrito, J. R., Stewart, F. R., Raichle, M. E., Lee, J.-M., & Holtzman, D. M. (2011) · Nature Neuroscience · doi:10.1038/nn.2801 · Cited by 880 · see citing works
Adaptive reconfiguration of fractal small-world human brain functional networks
Bassett, D. S., Meyer-Lindenberg, A., Achard, S., Duke, T., & Bullmore, E. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0606005103 · Cited by 814 · see citing works
Cellular mechanisms of brain energy metabolism and their relevance to functional brain imaging
Magistretti, P. J., & Pellerin, L. (1999) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.1999.0471 · Cited by 750 · see citing works
GABAergic Hub Neurons Orchestrate Synchrony in Developing Hippocampal Networks
Bonifazi, P., Goldin, M., Picardo, M. A., Jorquera, I., Cattani, A., Bianconi, G., Represa, A., Ben-Ari, Y., & Cossart, R. (2009) · Science · doi:10.1126/science.1175509 · Cited by 695 · see citing works
Homonuclear broad band decoupling and two-dimensional J-resolved NMR spectroscopy
Aue, W. P., Karhan, J., & Ernst, R. R. (1976) · The Journal of Chemical Physics · doi:10.1063/1.431994 · Cited by 676 · see citing works
Functional connectivity density mapping
Tomasi, D. G., & Volkow, N. D. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1001414107 · Cited by 640 · see citing works
Uncovering Intrinsic Modular Organization of Spontaneous Brain Activity in Humans
Yong He, A., Wang, J., Wang, L. Y., Chen, Z. J., Yan, C., Yang, H., Tang, H., Zhu, C., Gong, Q., Zang, Y., et al. (2009) · PLoS ONE · doi:10.1371/journal.pone.0005226 · Cited by 619 · see citing works
Disruption of Functional Connectivity in Clinically Normal Older Adults Harboring Amyloid Burden
Hedden, T., Van Dijk, K. R. A., Becker, J. A., Mehta, A., Sperling, R. A., Johnson, K. A., & Buckner, R. L. (2009) · The Journal of Neuroscience · doi:10.1523/jneurosci.3189-09.2009 · Cited by 598 · see citing works
Jueptner, M., & Weiller, C. (1995) · NeuroImage · doi:10.1006/nimg.1995.1017 · Cited by 522 · see citing works
Measuring functional connectivity using MEG: methodology and comparison with fcMRI
Brookes, M. J., Hale, J. R., Zumer, J. M., Stevenson, C. M., Francis, S. T., Barnes, G. R., Owen, J. P., Morris, P. G., & Nagarajan, S. S. (2011) · NeuroImage · doi:10.1016/j.neuroimage.2011.02.054 · Cited by 519 · see citing works
Localized 1H NMR measurements of gamma-aminobutyric acid in human brain in vivo.
Rothman, D. L., Petroff, O. A. C., Behar, K. L., & Mattson, R. H. (1993) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.90.12.5662 · Cited by 510 · see citing works
Buzsáki, G., Kaila, K., & Raichle, M. E. (2007) · Neuron · doi:10.1016/j.neuron.2007.11.008 · Cited by 449 · see citing works
Association between Functional Connectivity Hubs and Brain Networks
Tomasi, D. G., & Volkow, N. D. (2011) · Cerebral Cortex · doi:10.1093/cercor/bhq268 · Cited by 434 · see citing works
Neuronal-glial glucose oxidation and glutamatergic-GABAergic function.
Hyder, F., Patel, A. B., Gjedde, A., Rothman, D. L., Behar, K. L., & Shulman, R. G. (2006) · Journal of Cerebral Blood Flow & Metabolism · doi:10.1038/sj.jcbfm.9600263 · Cited by 408 · see citing works
Experimentation and Uncertainty Analysis for Engineers
Jacobs, T. (1991) · Journal of Testing and Evaluation · doi:10.1520/jte12616j · Cited by 398 · see citing works
GABA concentrations in the human anterior cingulate cortex predict negative BOLD responses in fMRI
Northoff, G., Walter, M., Schulte, R. F., Beck, J., Dydak, U., Henning, A., Boeker, H., Grimm, S., & Boesiger, P. (2007) · Nature Neuroscience · doi:10.1038/nn2001 · Cited by 359 · see citing works
Cerebral energetics and spiking frequency: The neurophysiological basis of fMRI
Smith, A. J., Blumenfeld, H., Behar, K. L., Rothman, D. L., Shulman, R. G., & Hyder, F. (2002) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.132272199 · Cited by 349 · see citing works
Magri, C., Schridde, U., Murayama, Y., Panzeri, S., & Logothetis, N. K. (2012) · Journal of Neuroscience · doi:10.1523/jneurosci.3985-11.2012 · Cited by 337 · see citing works
Hemodynamic and metabolic responses to neuronal inhibition
Stefanovic, B., Warnking, J. M., & Pike, G. B. (2004) · NeuroImage · doi:10.1016/j.neuroimage.2004.01.036 · Cited by 306 · see citing works
Horn (2010) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2010.00033 · Cited by 276 · see citing works
Quantitative proton MR spectroscopic imaging of the human brain
Soher, B. J., van Zijl, P. C. M., Duyn, J. H., & Barker, P. B. (1996) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910350313 · Cited by 271 · see citing works
Characterizing variation in the functional connectome: promise and pitfalls
Kelly, C. A. M., Biswal, B. B., Craddock, R. C., Castellanos, F. X., & Milham, M. P. (2012) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2012.02.001 · Cited by 250 · see citing works
Homonuclear 1H double-resonance difference spectroscopy of the rat brain in vivo.
Rothman, D. L., Behar, K. L., Hetherington, H. P., & Shulman, R. G. (1984) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.81.20.6330 · Cited by 209 · see citing works
Koch, W., Teipel, S. J., Mueller, S., Büerger, K., Bokde, A. L. W., Hampel, H. J., Coates, U., Reiser, M., & Meindl, T. (2009) · NeuroImage · doi:10.1016/j.neuroimage.2009.12.008 · Cited by 203 · see citing works
ProFit: two‐dimensional prior‐knowledge fitting of J‐resolved spectra
Schulte, R. F., & Boesiger, P. (2006) · NMR in Biomedicine · doi:10.1002/nbm.1026 · Cited by 177 · see citing works
Baseline GABA concentration and fMRI response
Donahue, M. J., Near, J., Blicher, J. U., & Jezzard, P. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2010.07.017 · Cited by 174 · see citing works
Behar, K. L., & Ogino, T. (1991) · Magnetic Resonance in Medicine · doi:10.1002/mrm.1910170202 · Cited by 173 · see citing works
Translating Glutamate: From Pathophysiology to Treatment
Javitt, D. C., Schoepp, D., Kalivas, P. W., Volkow, N. D., Zarate, C., Merchant, K., Bear, M. F., Umbricht, D., Hajos, M., Potter, W. Z., et al. (2011) · Science Translational Medicine · doi:10.1126/scitranslmed.3002804 · Cited by 168 · see citing works
Denoising Source SeparationPreprint
Särelä, J., & Harri Valpola, B. (2005) · CogPrints (University of Southampton) · Cited by 162 · see citing works
Representation, inference, and transcendent encoding in neurocognitive networks of the human brain
Mesulam, M. M. (2008) · Annals of Neurology · doi:10.1002/ana.21534 · Cited by 158 · see citing works
Talairach, J., Tournoux, P., & Missir, O. (1993) · Medical Entomology and Zoology · Cited by 156 · see citing works
Granger causal influence predicts BOLD activity levels in the default mode network
Jiao, Q., Lu, G., Zhang, Z., Zhong, Y., Wang, Z., Guo, Y., Li, K., Ding, M., & Liu, Y. (2010) · Human Brain Mapping · doi:10.1002/hbm.21065 · Cited by 141 · see citing works
Chen, S., Ross, T. J., Zhan, W., Myers, C. S., Chuang, K.-S., Heishman, S. J., Stein, E. A., & Yang, Y. (2008) · Brain Research · doi:10.1016/j.brainres.2008.08.028 · Cited by 139 · see citing works
Muthukumaraswamy, S. D., Evans, J., Edden, R. A. E., Wise, R. G., & Singh, K. D. (2011) · Human Brain Mapping · doi:10.1002/hbm.21223 · Cited by 131 · see citing works
Differential modulation of the default mode network via serotonin-1A receptors
Hahn, A., Wadsak, W., Windischberger, C., Baldinger, P., Höflich, A. S., Lošák, J., Nics, L., Philippe, C., Kranz, G. S., Kraus, C., et al. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1117104109 · Cited by 129 · see citing works
Experimentation and Uncertainty Analysis for Engineers, 2nd Ed.
Wahl, T. L. (1999) · Journal of Hydraulic Engineering · doi:10.1061/(asce)0733-9429(1999)125:12(1320 · Cited by 114 · see citing works
Bruyn, G. W. (1994) · Journal of the Neurological Sciences · doi:10.1016/0022-510x(94)90227-5 · Cited by 110 · see citing works
Pfefferbaum, A., Chanraud, S., Pitel, A.-L., Muller-Oehring, E., Shankaranarayanan, A., Alsop, D. C., Rohlfing, T., & Sullivan, E. V. (2011) · Cerebral Cortex · doi:10.1093/cercor/bhq090 · Cited by 104 · see citing works
Improved two‐dimensional J‐resolved spectroscopy
Schulte, R. F., Lange, T., Beck, J., Meier, D., & Boesiger, P. (2006) · NMR in Biomedicine · doi:10.1002/nbm.1027 · Cited by 89 · see citing works
Falkenberg, L. E., Westerhausen, R., Specht, K., & Hugdahl, K. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1115628109 · Cited by 81 · see citing works
Duncan, N. W., Enzi, B., Wiebking, C., & Northoff, G. (2011) · Human Brain Mapping · doi:10.1002/hbm.21179 · Cited by 68 · see citing works
Homeostatic Disinhibition in the Aging Brain and Alzheimer's Disease
Gleichmann, M., Chow, V. W., & Mattson, M. P. (2011) · Journal of Alzheimer s Disease · doi:10.3233/jad-2010-101674 · Cited by 58 · see citing works
Self-citationNonsynaptic Receptors for GABA and Glutamate
Vizi, E. S., & Mike, Á. (2006) · Current Topics in Medicinal Chemistry · doi:10.2174/156802606777323782 · Cited by 35 · see citing works
Benarroch, E. E. (2007) · Neurology · doi:10.1212/01.wnl.0000257836.09570.e1 · Cited by 31 · see citing works
DiNuzzo, M., Gili, T., Maraviglia, B., & Giove, F. (2011) · Journal of Neurophysiology · doi:10.1152/jn.00416.2011 · Cited by 22 · see citing works
Competition Through Selective Inhibitory Synchrony
Rutishauser, U., Slotine, J.-J. E., & Douglas, R. J. (2012) · Neural Computation · doi:10.1162/neco_a_00304 · Cited by 17 · see citing works
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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 · see citing works
Brain default-mode network dysfunction in addiction
Zhang, R., & Volkow, N. D. (2019) · NeuroImage · doi:10.1016/j.neuroimage.2019.06.036 · Cited by 365 · see citing works
Fee, C., Banasr, M., & Sibille, E. (2017) · Biological Psychiatry · doi:10.1016/j.biopsych.2017.05.024 · Cited by 329 · see citing works
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 · see citing works
Bachtiar, V., Near, J., Johansen‐Berg, H., & Stagg, C. J. (2015) · eLife · doi:10.7554/elife.08789 · Cited by 250 · see citing works
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 · see citing works
Duncan, N. W., Wiebking, C., & Northoff, G. (2014) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2014.07.016 · Cited by 217 · see citing works
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 213 · see citing works
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 213 · see citing works
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 · see citing works
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 · see citing works
Jiménez-Baladó, J., & Eich, T. S. (2021) · Seminars in Cell and Developmental Biology · doi:10.1016/j.semcdb.2021.01.005 · Cited by 185 · see citing works
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 · see citing works
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 · see citing works
Hu, Y., Chen, X., Gu, H., & Yang, Y. (2013) · The Journal of Neuroscience · doi:10.1523/jneurosci.1973-13.2013 · Cited by 167 · see citing works
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 156 · see citing works
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 167 · see citing works
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 149 · see citing works
Northoff, G., & Sibille, E. L. (2014) · Molecular Psychiatry · doi:10.1038/mp.2014.68 · Cited by 145 · see citing works
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 143 · see citing works
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 · see citing works
“…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 132 · see citing works
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 118 · see citing works
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 111 · see citing works
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 100 · see citing works
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 · see citing works
Napadow, V., & Harris, R. E. (2014) · Arthritis Research & Therapy · doi:10.1186/s13075-014-0425-0 · Cited by 92 · see citing works
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 74 · see citing works
The role of inhibition in human motor cortical plasticity.
Bachtiar, V., & Stagg, C. (2014) · Neuroscience · doi:10.1016/j.neuroscience.2014.07.059 · Cited by 64 · see citing works
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 · see citing works
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 · see citing works
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 · see citing works
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 61 · see citing works
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 · see citing works
McGirr, A., LeDue, J. M., Chan, A. W., Xie, Y., & Murphy, T. H. (2017) · Brain · doi:10.1093/brain/awx142 · Cited by 58 · see citing works
Gu, H., Hu, Y., Chen, X., Yong He, A., & Yang, Y. (2018) · NeuroImage · doi:10.1016/j.neuroimage.2018.10.055 · Cited by 56 · see citing works
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 54 · see citing works
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 · see citing works
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 58 · see citing works
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 · see citing works
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 50 · see citing works
Kraguljac, N. V., White, D. M., Hadley, J. A., Reid, M. A., & Lahti, A. C. (2014) · Hippocampus · doi:10.1002/hipo.22332 · Cited by 52 · see citing works
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 · see citing works
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 · see citing works
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 50 · see citing works
Self-citationMoeller, S. J., London, E. D., & Northoff, G. (2015) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2015.11.010 · Cited by 48 · see citing works
Reckziegel, D., Raschke, F., Cottam, W. J., & Auer, D. P. (2016) · Molecular Pain · doi:10.1177/1744806916650690 · Cited by 47 · see citing works
Nasrallah, F. A., Lew, S. K., Low, A. S.-M., & Chuang, K. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.08.004 · Cited by 46 · see citing works
Naskar, A., Vattikonda, A. N., Deco, G., Roy, D., & Banerjee, A. (2021) · Network Neuroscience · doi:10.1162/netn_a_00197 · Cited by 40 · see citing works
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 · see citing works
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 · see citing works
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 · see citing works
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 · see citing works
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 · see citing works
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 42 · see citing works
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 42 · see citing works
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 · see citing works
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 41 · see citing works
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 39 · see citing works
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 40 · see citing works
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 38 · see citing works
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 · see citing works
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 34 · see citing works
Pizzi, S., Chiacchieretta, P., Mantini, D., Bubbico, G., Edden, R., Onofrj, M., Ferretti, A., & Bonanni, L. (2017) · Brain Structure and Function · doi:10.1007/s00429-017-1399-x · Cited by 27 · see citing works
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 37 · see citing works
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 · see citing works
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 · see citing works
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 · see citing works
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 33 · see citing works
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 32 · see citing works
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 31 · see citing works
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 29 · see citing works
Just, N., & Sonnay, S. (2017) · Frontiers in Physiology · doi:10.3389/fphys.2017.00030 · Cited by 30 · see citing works
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 · see citing works
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 · see citing works
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 · see citing works
“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 · see citing works
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 · see citing works
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 · see citing works
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 · see citing works
Turk, E., Scholtens, L. H., & van den Heuvel, M. P. (2016) · Human Brain Mapping · doi:10.1002/hbm.23141 · Cited by 27 · see citing works
Kanagasabai, K., Palaniyappan, L. K., & Théberge, J. (2023) · NMR in Biomedicine · doi:10.1002/nbm.5071 · Cited by 27 · see citing works
Chen, Y., & Zhang, J. (2021) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2021.648860 · Cited by 27 · see citing works
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 · see citing works
Cleve, M., Gussew, A., Wagner, G., Bär, K., & Reichenbach, J. R. (2017) · Neuroscience · doi:10.1016/j.neuroscience.2017.09.037 · Cited by 27 · see citing works
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 26 · see citing works
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 · see citing works
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 · see citing works
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 · see citing works
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 · see citing works
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 25 · see citing works
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 · see citing works
Rideaux, R. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118191 · Cited by 23 · see citing works
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 · see citing works
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 26 · see citing works
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 · see citing works
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 · see citing works
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 21 · see citing works
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 · see citing works
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 22 · see citing works
- 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 · 2012: 1
- 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
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