Nonrandom connectivity of the epileptic dentate gyrus predicts a major role for neuronal hubs in seizures
Open accessAbstract
Many complex neuronal circuits have been shown to display nonrandom features in their connectivity. However, the functional impact of nonrandom network topologies in neurological diseases is not well understood. The dentate gyrus is an excellent circuit in which to study such functional implications because proepileptic insults cause its structure to undergo a number of specific changes in both humans and animals, including the formation of previously nonexistent granule cell-to-granule cell recurrent excitatory connections. Here, we use a large-scale, biophysically realistic model of the epileptic rat dentate gyrus to reconnect the aberrant recurrent granule cell network in four biologically plausible ways to determine how nonrandom connectivity promotes hyperexcitability after injury. We find that network activity of the dentate gyrus is quite robust in the face of many major alterations in granule cell-to-granule cell connectivity. However, the incorporation of a small number of highly interconnected granule cell hubs greatly increases network activity, resulting in a hyperexcitable, potentially seizure-prone circuit. Our findings demonstrate the functional relevance of nonrandom microcircuits in epileptic brain networks, and they provide a mechanism that could explain the role of granule cells with hilar basal dendrites in contributing to hyperexcitability in the pathological dentate gyrus.
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
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?
The previously built dentate gyrus model was used by several groups to study disparate topics including epilepsy, network mechanisms of inhibition and excitability, simulation optimization, and modeling software.
“Previously, we built a dentate gyrus model to study epileptic network dynamics (Santhakumar et al., 2005; Morgan and Soltesz, 2008) that was then used by several groups to study disparate topics including epilepsy, network mechanisms of inhibition and excitability, simulation optimization, and modeling software”
From Interneuronal mechanisms of hippocampal theta oscillations in a full-scale model of the rodent CA1 circuit (2016) · cites this paper as Morgan and Soltesz, 2008
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Collective dynamics of ‘small-world’ networks
Watts, D. J., & Strogatz, S. H. (1998) · Nature · doi:10.1038/30918 · Cited by 43,060 · see citing works
Emergence of Scaling in Random Networks
Barabási, A.-L., & Albert, R. (1999) · Science · doi:10.1126/science.286.5439.509 · Cited by 36,135 · see citing works
Statistical mechanics of complex networks
Albert, R., & Barabási, A.-L. (2002) · Reviews of Modern Physics · doi:10.1103/revmodphys.74.47 · Cited by 20,471 · see citing works
Distributed hierarchical processing in the primate cerebral cortex
Felleman, D. J., & Van Essen, D. C. (1991) · Cerebral Cortex · doi:10.1093/cercor/1.1.1 · Cited by 7,783 · see citing works
Network motifs: simple building blocks of complex networks.
Milo, R., Shen-Orr, S., Itzkovitz, S., Kashtan, N., Chklovskii, D., & Alon, U. (2002) · Science · doi:10.1126/science.298.5594.824 · Cited by 7,368 · see citing works
The structure of the nervous system of the nematode <i>Caenorhabditis elegans</i>
White, J. G., Southgate, E., Thomson, J. N., & Brenner, S. (1986) · Philosophical Transactions of the Royal Society of London. B, Biological Sciences · doi:10.1098/rstb.1986.0056 · Cited by 5,589 · cited 1× · see citing works
“For example, in the nervous system of the Caenorhabditis elegans worm, of which the complete structure has been described (1), it was shown that a number of local connectivity patterns (network motifs) are over- or underrepresented compared with what would be present in a random network (2–4).”
BackgroundThe Large-Scale Organization of Metabolic Networks
Jeong, H., Tombor, B., Albert, R., Oltvai, Z. N., & Barabási, A.-L. (2000) · Nature · doi:10.1038/35036627 · Cited by 4,972 · see citing works
Diameter of the World-Wide Web
Albert, R., Jeong, H., & Barabási, A.-Ĺ. (1999) · Nature · doi:10.1038/43601 · Cited by 4,240 · see citing works
The NEURON Simulation Environment
Hines, M. L., & Carnevale, N. T. (1997) · Neural Computation · doi:10.1162/neco.1997.9.6.1179 · Cited by 2,630 · see citing works
Small worlds: the dynamics of networks between order and randomness
(2000) · Choice Reviews Online · doi:10.5860/choice.37-5722 · Cited by 2,384 · see citing works
Watts, D. J. (1999) · Princeton University Press eBooks · doi:10.1515/9780691188331 · Cited by 2,106 · see citing works
Modelling disease outbreaks in realistic urban social networks
Eubank, S., Güçlü, H., Kumar, V. S. A., MARATHE, M. V., Srinivasan, A., Toroczkai, Z., & Wang, N. (2004) · Nature · doi:10.1038/nature02541 · Cited by 2,091 · see citing works
Highly nonrandom features of synaptic connectivity in local cortical circuits
Song, S., Sjöström, P. J., Reigl, M., Nelson, S., & Chklovskii, D. B. (2005) · PLoS Biology · doi:10.1371/journal.pbio.0030068 · Cited by 1,512 · see citing works
Superfamilies of Evolved and Designed Networks
Milo, R., Itzkovitz, S., Kashtan, N., Levitt, R., Shen-Orr, S. S., Ayzenshtat, I., Sheffer, M., & Alon, U. S. (2004) · Science · doi:10.1126/science.1089167 · Cited by 1,427 · see citing works
Scale-free characteristics of random networks: the topology of the world-wide web
Barabási, A.-Ĺ., Albert, R., & Jeong, H. (2000) · Physica A Statistical Mechanics and its Applications · doi:10.1016/s0378-4371(00)00018-2 · Cited by 1,426 · see citing works
Scale-free networks in cell biology
Albert, R. (2005) · Journal of Cell Science · doi:10.1242/jcs.02714 · Cited by 1,200 · see citing works
The small world inside large metabolic networks
Wagner, A., & Fell, D. A. (2001) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2001.1711 · Cited by 986 · see citing works
Sporns, O., & Kötter, R. (2004) · PLoS Biology · doi:10.1371/journal.pbio.0020369 · Cited by 805 · see citing works
FANMOD: a tool for fast network motif detection
Wernicke, S., & Rasche, F. (2006) · Bioinformatics · doi:10.1093/bioinformatics/btl038 · Cited by 750 · see citing works
Small Worlds: The Dynamics of Networks between Order and Randomness
Watts, D. J., & Bak, P. (2000) · Physics Today · doi:10.1063/1.1333299 · Cited by 602 · see citing works
Excitatory cortical neurons form fine-scale functional networks
Yoshimura, Y., Dantzker, J. L. M., & Callaway, E. M. (2005) · Nature · doi:10.1038/nature03252 · Cited by 601 · see citing works
Hilgetag, C. C., Burns, G., O’Neill, M. A., Scannell, J. W., & Young, M. P. (2000) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2000.0551 · Cited by 548 · see citing works
Dynamics and Effective Topology Underlying Synchronization in Networks of Cortical Neurons
Eytan, D., & Marom, S. (2006) · Journal of Neuroscience · doi:10.1523/jneurosci.1627-06.2006 · Cited by 402 · see citing works
Fine-scale specificity of cortical networks depends on inhibitory cell type and connectivity
Yoshimura, Y., & Callaway, E. M. (2005) · Nature Neuroscience · doi:10.1038/nn1565 · Cited by 390 · see citing works
Dynamic Properties of Network Motifs Contribute to Biological Network Organization
Prill, R. J., Iglesias, P. A., & Levchenko, A. (2005) · PLoS Biology · doi:10.1371/journal.pbio.0030343 · Cited by 371 · see citing works
Buckmaster, P. S., Zhang, G. F., & Yamawaki, R. M. (2002) · Journal of Neuroscience · doi:10.1523/jneurosci.22-15-06650.2002 · Cited by 311 · see citing works
The organization of neural systems in the primate cerebral cortex
Young, M. P. (1993) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.1993.0040 · Cited by 276 · see citing works
Computational analysis of functional connectivity between areas of primate cerebral cortex
Stephan, K. E., Hilgetag, C. C., Burns, G., O’Neill, M. A., Young, M. P., & Kötter, R. (2000) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2000.0552 · Cited by 269 · see citing works
Buckmaster, P. S., & Jongen‐Rêlo, A. L. (1999) · Journal of Neuroscience · doi:10.1523/jneurosci.19-21-09519.1999 · Cited by 267 · see citing works
Santhakumar, V., Aradi, I., & Soltesz, I. (2005) · Journal of Neurophysiology · doi:10.1152/jn.00777.2004 · Cited by 262 · see citing works
Self-citationJamming is limited in scale-free systems
Toroczkai, Z., & Bassler, K. E. (2004) · Nature · doi:10.1038/428716a · Cited by 230 · see citing works
Dyhrfjeld-Johnsen, J., Santhakumar, V., Morgan, R. J., Huerta, R., Tsimring, L., & Soltesz, I. (2007) · Journal of Neurophysiology · doi:10.1152/jn.00950.2006 · Cited by 230 · see citing works
Self-citationWalter, C., Murphy, B. L., Pun, R. Y. K., Spieles-Engemann, A. L., & Danzer, S. C. (2007) · Journal of Neuroscience · doi:10.1523/jneurosci.0431-07.2007 · Cited by 189 · see citing works
Topology of biological networks and reliability of information processing
Klemm, K., & Bornholdt, S. (2005) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0509132102 · Cited by 184 · see citing works
In Vivo Intracellular Analysis of Granule Cell Axon Reorganization in Epileptic Rats
Buckmaster, P. S., & Dudek, F. E. (1999) · Journal of Neurophysiology · doi:10.1152/jn.1999.81.2.712 · Cited by 182 · see citing works
Dentate granule cells form novel basal dendrites in a rat model of temporal lobe epilepsy
Spigelman, I., Yan, X., Obenaus, A., et al. (1998) · Neuroscience · doi:10.1016/s0306-4522(98)00028-1 · Cited by 176 · see citing works
Tanaka, R. J. (2005) · Physical Review Letters · doi:10.1103/physrevlett.94.168101 · Cited by 147 · see citing works
Highly nonrandom features of synaptic connectivity in local cortical circuits (vol 3, pg e68, 2005)
Song, S.-F., Sjöström, P. J., Reigl, M., Nelson, S. B., & Chklovskii, D. B. (2005) · UCL Discovery (University College London) · Cited by 147 · see citing works
Desmond, N. L., & Levy, W. B. (1982) · The Journal of Comparative Neurology · doi:10.1002/cne.902120204 · Cited by 115 · see citing works
Search for computational modules in the C. elegansbrain
Reigl, M., Alon, U. S., & Chklovskii, D. B. (2004) · BMC Biology · doi:10.1186/1741-7007-2-25 · Cited by 102 · see citing works
Right‐sided Vagus Nerve Stimulation as a Treatment for Refractory Epilepsy in Humans
McGregor, A., Wheless, J. W., Baumgartner, J. E., & Bettis, D. B. (2005) · Epilepsia · doi:10.1111/j.0013-9580.2005.16404.x · Cited by 101 · see citing works
Dynamical Motifs: Building Blocks of Complex Dynamics in Sparsely Connected Random Networks
Zhigulin, V. P. (2004) · Physical Review Letters · doi:10.1103/physrevlett.92.238701 · Cited by 44 · see citing works
Distribution of mRNAs encoding CRF receptors in brain and pituitary of rat and mouse
Van Pett, K., Viau, V., Bittencourt, J. C., Chan, R. K. W., Li, H.-Y., Arias, C., Prins, G. S., Perrin, M., Vale, W., & Sawchenko, P. E. (2000) · The Journal of Comparative Neurology · doi:10.1002/1096-9861(20001211)428:2
Flagged first, then by citations
Research works printed but not linked: 1
- [38]Buckmaster PS, Thind K. Quantifying routes of positive-feedback among granule cells in a model of temporal lobe epilepsy. Epilepsia. 2005;46:91–131. [[Google Scholar](https://scholar.google.com/scholar_lookup?journal=Epilepsia&title=Quantifying%20routes%20of%20positive-feedback%20among%20granule%20cells%20in%20a%20model%20of%20temporal%20lobe%20epilepsy&author=PS%20Buckmaster&author=K%20Thind&volume=46&publication_year=2005&pages=91-131&)]
Cited by
Sorted by citations
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
Aberrant hippocampal neurogenesis contributes to epilepsy and associated cognitive decline
Cho, K.-O., Lybrand, Z. R., Ito, N., Brulet, R., Tafacory, F., Zhang, L., Good, L., Ure, K., Kernie, S. G., Birnbaum, S. G., et al. (2015) · Nature Communications · doi:10.1038/ncomms7606 · Cited by 451 · see citing works
Bezaire, M. J., & Soltesz, I. (2013) · Hippocampus · doi:10.1002/hipo.22141 · Cited by 373 · see citing works
Self-citationBezaire, M. J., Raikov, I., Burk, K., Vyas, D., & Soltesz, I. (2016) · eLife · doi:10.7554/elife.18566 · Cited by 198 · see citing works
Pioneer GABA Cells Comprise a Subpopulation of Hub Neurons in the Developing Hippocampus
Picardo, M. A., Guigue, P., Bonifazi, P., Batista-Brito, R., Allene, C., Ribas, A., Fishell, G., Baude, A., & Cossart, R. (2011) · Neuron · doi:10.1016/j.neuron.2011.06.018 · Cited by 167 · see citing works
Peng, Z., Zhang, N., Wei, W., Huang, C. S., Cetina, Y., Otis, T. S., & Houser, C. R. (2013) · The Journal of Neuroscience · doi:10.1523/jneurosci.2045-13.2013 · Cited by 114 · see citing works
Neurogliaform and Ivy Cells: A Major Family of nNOS Expressing GABAergic Neurons
Armstrong, C., Krook-Magnuson, E., & Soltesz, I. (2012) · Frontiers in Neural Circuits · doi:10.3389/fncir.2012.00023 · Cited by 88 · see citing works
Self-citationArmstrong, C., Szabadics, J., Tamás, G., & Soltesz, I. (2011) · Journal of Comparative Neurology · doi:10.1002/cne.22577 · Cited by 86 · see citing works
Self-citationYu, J., Proddutur, A., Elgammal, F. S., Ito, T., & Santhakumar, V. (2013) · Journal of Neurophysiology · doi:10.1152/jn.00891.2012 · Cited by 62 · see citing works
Fast and accurate low-dimensional reduction of biophysically detailed neuron models
Marasco, A., Limongiello, A., & Migliore, M. (2012) · Scientific Reports · doi:10.1038/srep00928 · Cited by 28 · see citing works
- Authors
- Morgan, R. J., & Soltesz, I.
- Affiliations
- University of California, Irvine (US)
- Department of Anatomy and Neurobiology, University of California, 193 Irvine Hall, Irvine, CA 92697
- Venue
- Proceedings of the National Academy of Sciences
- Publisher
- National Academy of Sciences
- Published
- 2008-04-22
- Volume
- 105
- Issue
- 16
- Pages
- 6179-6184
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- PMC
- PMC2299224
- OpenAlex
- W2131705496
- Cited by
- 347
- References
- 43
- Citations by year
- 2026: 5 · 2025: 6 · 2024: 4 · 2023: 11 · 2022: 12 · 2021: 16 · 2020: 11 · 2019: 16 · 2018: 12 · 2017: 16 · 2016: 19 · 2015: 23 · 2014: 28 · 2013: 32 · 2012: 49
- FWCI
- 20.32
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Proceedings of the National Academy of Sciences (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (NS35915)
- University of California, Irvine
- National Institute of Neurological Disorders and Stroke (R29NS035915, R01NS035915, NS-35915, R37NS035915)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Epilepsy research and treatment
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Keywords
- granule cells, network hyperexcitability, seizure generation
- MeSH terms
- Animals, Models, Biological, Nerve Net, Neurons, Seizures, Dentate Gyrus, Rats
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
