Spontaneous Infraslow Fluctuations Modulate Hippocampal EPSP-PS Coupling
Open accessAbstract
Extensive trial-to-trial variability is a hallmark of most behavioral, cognitive, and physiological processes. Spontaneous brain activity (SBA), a ubiquitous phenomenon that coordinates levels and patterns of neuronal activity throughout the brain, may contribute to this variability by dynamically altering neuronal excitability. In freely-behaving male rats, we observed extensive variability of the hippocampal evoked response across 28-min recording periods despite maintaining constant stimulation parameters of the medial perforant path. This variability was related to antecedent SBA: increases in low-frequency (0.5–9 Hz) and high-frequency (40.25–100 Hz) band-limited power (BLP) in the 4-s preceding stimulation were associated with decreased slope of the field EPSP (fEPSP) and increased population spike (PS) amplitude. These fluctuations in SBA and evoked response magnitude did not appear stochastic but rather exhibited coordinated activity across infraslow timescales (0.005–0.02 Hz). Specifically, infraslow fluctuations in high- and low-frequency BLP were antiphase with changes in fEPSP slope and in phase with changes in PS amplitude. With these divergent effects on the fEPSP and PS, infraslow SBA ultimately modulates EPSP-PS coupling and thereby enables hippocampal circuitry to generate heterogeneous outputs from identical inputs. Consequently, infraslow SBA appears well suited to dynamically alter sensory selection and information processing and highlights the fundamental role of endogenous neuronal activity for shaping the brain’s response to incoming stimuli.
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?
Electrophysiological infraslow fluctuations have been shown in both cortical and subcortical tissues.
“eISFs have been shown in both cortical [65, 66, 77] and subcortical [76, 78–82] tissues”
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
Neuronal Oscillations in Cortical Networks
Buzsáki, G., & Draguhn, A. (2004) · Science · doi:10.1126/science.1099745 · Cited by 6,576 · see citing works
Correspondence of the brain's functional architecture during activation and rest
Smith, S. M., Fox, P. T., Miller, K. L., Glahn, D. C., Fox, P. M., Mackay, C. E., Filippini, N., Watkins, K. E., Toro, R., Laird, A. R., et al. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0905267106 · Cited by 5,150 · see citing works
The brain's default mode network
Raichle, M. E. (2015) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-071013-014030 · Cited by 3,904 · see citing works
Interneurons of the hippocampus
Freund, T. F., & Buzsáki, G. (1998) · Hippocampus · doi:10.1002/(sici)1098-1063(1996)6:4 · Cited by 3,423 · see citing works
<b>CircStat</b> : A <i>MATLAB</i> Toolbox for Circular Statistics
Berens, P. (2009) · Journal of Statistical Software · doi:10.18637/jss.v031.i10 · Cited by 3,099 · see citing works
Electrophysiological signatures of resting state networks in the human brain
Mantini, D., Perrucci, M. G., Del Gratta, C., Romani, G. L., & Corbetta, M. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0700668104 · Cited by 1,938 · see citing works
Pattern Separation in the Dentate Gyrus and CA3 of the Hippocampus
Leutgeb, J. K., Leutgeb, S., Moser, M.-B., & Moser, E. I. (2007) · Science · doi:10.1126/science.1135801 · Cited by 1,601 · see citing works
Low-frequency neuronal oscillations as instruments of sensory selection
Schroeder, C. E., & Lakatos, P. (2009) · Trends in Neurosciences · doi:10.1016/j.tins.2008.09.012 · Cited by 1,528 · see citing works
Competition between functional brain networks mediates behavioral variability
Kelly, A. M. C., Uddin, L. Q., Biswal, B. B., Castellanos, F. X., & Milham, M. P. (2008) · NeuroImage · doi:10.1016/j.neuroimage.2007.08.008 · Cited by 1,287 · see citing works
Slow potentials of the cerebral cortex and behavior.
Birbaumer, N., Elbert, T. R., Canavan, A. G. M., & Rockstroh, B. S. (1990) · Physiological Reviews · doi:10.1152/physrev.1990.70.1.1 · Cited by 1,099 · see citing works
Cross-frequency coupling between neuronal oscillations
Jensen, O., & Colgin, L. L. (2007) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2007.05.003 · Cited by 991 · see citing works
Spatial selectivity of unit activity in the hippocampal granular layer
Jung, M. W., & McNaughton, B. L. (1993) · Hippocampus · doi:10.1002/hipo.450030209 · Cited by 789 · see citing works
Learning sculpts the spontaneous activity of the resting human brain
Lewis, C. M., Baldassarre, A., Committeri, G., Romani, G. L., & Corbetta, M. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0902455106 · Cited by 777 · see citing works
Raichle, M. E. (2011) · Brain Connectivity · doi:10.1089/brain.2011.0019 · Cited by 672 · see citing works
Fox, M. D., Snyder, A. Z., Zacks, J. M., & Raichle, M. E. (2006) · Nature Neuroscience · doi:10.1038/nn1616 · Cited by 660 · see citing works
Fluctuating synaptic conductances recreate in vivo-like activity in neocortical neurons
Destexhe, A., Rudolph, M., Fellous, J.-M., & Sejnowski, T. J. (2001) · Neuroscience · doi:10.1016/s0306-4522(01)00344-x · Cited by 642 · see citing works
Relating Hippocampal Circuitry to Function
Lisman, J. E. (1999) · Neuron · doi:10.1016/s0896-6273(00)81085-5 · Cited by 607 · see citing works
Long-Term Plasticity of Intrinsic Excitability: Learning Rules and MechanismsPreprint
Daoudal, G., & Debanne, D. (2003) · Learning & Memory · doi:10.1101/lm.64103 · Cited by 537 · see citing works
Vanhatalo, S., Palva, J. M., Holmes, M., Miller, J. W., Voipio, J., & Kaila, K. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0305375101 · Cited by 517 · see citing works
Single granule cells reliably discharge targets in the hippocampal CA3 network in vivo
Henze, D. A., Wittner, L., & Buzsáki, G. (2002) · Nature Neuroscience · doi:10.1038/nn887 · Cited by 480 · see citing works
Monto, S., Palva, S., Voipio, J., & Palva, J. M. (2008) · The Journal of Neuroscience · doi:10.1523/jneurosci.1910-08.2008 · Cited by 453 · see citing works
Hyman, J. M., Wyble, B., Goyal, V., Rossi, C. A., & Hasselmo, M. E. (2003) · Journal of Neuroscience · doi:10.1523/jneurosci.23-37-11725.2003 · Cited by 404 · see citing works
Mitchell, S., Rawlins, J. N. P., Steward, O., & Olton, D. S. (1982) · Journal of Neuroscience · doi:10.1523/jneurosci.02-03-00292.1982 · Cited by 401 · see citing works
Wulff, P., Ponomarenko, A. A., Bartos, M., Korotkova, T. M., Fuchs, E. C., Bähner, F., Both, M., Tort, A. B. L., Kopell, N. J., Wisden, W., et al. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0813176106 · Cited by 400 · see citing works
The neural bases of multistable perception
Sterzer, P., Kleinschmidt, A. K., & Rees, G. E. (2009) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2009.04.006 · Cited by 396 · see citing works
The fMRI signal, slow cortical potential and consciousness
He, B. J., & Raichle, M. E. (2009) · Trends in Cognitive Sciences · doi:10.1016/j.tics.2009.04.004 · Cited by 324 · see citing works
Spontaneous local variations in ongoing neural activity bias perceptual decisions
Hesselmann, G., Kell, C. A., Eger, E., & Kleinschmidt, A. K. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0712043105 · Cited by 315 · see citing works
The Dynamical Balance of the Brain at Rest
Deco, G., & Corbetta, M. (2010) · The Neuroscientist · doi:10.1177/1073858409354384 · Cited by 312 · see citing works
Natural stimuli evoke dynamic sequences of states in sensory cortical ensembles
Jones, L. M., Fontanini, A., Sadacca, B. F., Miller, P. C., & Katz, D. B. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0705546104 · Cited by 287 · see citing works
McNaughton, B. L., & Barnes, C. A. (1977) · The Journal of Comparative Neurology · doi:10.1002/cne.901750404 · Cited by 280 · see citing works
Fellous, J.-M., Rudolph, M., Destexhe, A., & Sejnowski, T. J. (2003) · Neuroscience · doi:10.1016/j.neuroscience.2003.08.027 · Cited by 273 · see citing works
Large-Scale Calcium Waves Traveling through Astrocytic Networks In Vivo
Kuga, N., Sasaki, T., Takahara, Y., Matsuki, N., & Ikegaya, Y. (2011) · Journal of Neuroscience · doi:10.1523/jneurosci.5319-10.2011 · Cited by 262 · see citing works
Shirvalkar, P. R., Rapp, P. R., & Shapiro, M. L. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0911184107 · Cited by 235 · see citing works
Theta–gamma coupling in the entorhinal–hippocampal system
Colgin, L. L. (2014) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2014.08.001 · Cited by 226 · see citing works
Subthreshold Dendritic Signal Processing and Coincidence Detection in Dentate Gyrus Granule Cells
Schmidt‐Hieber, C., Jónás, P., & Bischofberger, J. (2007) · Journal of Neuroscience · doi:10.1523/jneurosci.1787-07.2007 · Cited by 179 · see citing works
The dentate gyrus as a filter or gate: a look back and a look ahead
Hsu, D. (2007) · Progress in brain research · doi:10.1016/s0079-6123(07)63032-5 · Cited by 177 · see citing works
Behavioral States, Network States, and Sensory Response Variability
Fontanini, A., & Katz, D. B. (2008) · Journal of Neurophysiology · doi:10.1152/jn.90592.2008 · Cited by 170 · see citing works
Palva, J. M., & Palva, S. (2012) · NeuroImage · doi:10.1016/j.neuroimage.2012.02.060 · Cited by 163 · see citing works
Synaptic plasticity in the hippocampus is modulated by behavioral state
Bramham, C. R., & Srebro, B. (1989) · Brain Research · doi:10.1016/0006-8993(89)91001-9 · Cited by 154 · see citing works
Functional interactions between intrinsic brain activity and behavior
Sadaghiani, S., & Kleinschmidt, A. (2013) · NeuroImage · doi:10.1016/j.neuroimage.2013.04.100 · Cited by 147 · see citing works
Novelty‐elicited, Noradrenaline‐dependent Enhancement of Excitability in the Dentate Gyrus
Kitchigina, V. F., Vankov, A., Harley, C. W., & Sara, S. J. (1997) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.1997.tb01351.x · Cited by 145 · see citing works
Stochastic Simulations on the Reliability of Action Potential Propagation in Thin Axons
Faisal, A. A., & Laughlin, S. B. (2007) · PLoS Computational Biology · doi:10.1371/journal.pcbi.0030079 · Cited by 144 · see citing works
Winson, J., & Abzug, C. (1977) · Science · doi:10.1126/science.193192 · Cited by 143 · see citing works
ATP-Dependent Infra-Slow (<0.1 Hz) Oscillations in Thalamic Networks
Lőrincz, M. L., Geall, F., Bao, Y., Crunelli, V., & Hughes, S. W. (2009) · PLoS ONE · doi:10.1371/journal.pone.0004447 · Cited by 103 · see citing works
Jetti, S. K., Vendrell-Llopis, N., & Yaksi, E. (2014) · Current Biology · doi:10.1016/j.cub.2014.01.015 · Cited by 94 · see citing works
Chan, A. W., Mohajerani, M. H., LeDue, J. M., Wang, Y. T., & Murphy, T. H. (2015) · Nature Communications · doi:10.1038/ncomms8738 · Cited by 79 · see citing works
Green, E., McNaughton, B. L., & Barnes, C. A. (1990) · Journal of Neuroscience · doi:10.1523/jneurosci.10-05-01455.1990 · Cited by 77 · see citing works
Ultra-slow oscillation (0.025 Hz) triggers hippocampal afterdischarges in Wistar rats
Penttonen, M., Nurminen, N., Miettinen, R. A., Sirviö, J., Henze, D. A., Csicsvari, J. L., & Buzsáki, G. (1999) · Neuroscience · doi:10.1016/s0306-4522(99)00367-x · Cited by 74 · see citing works
Lindquist, B. E., & Shuttleworth, C. W. (2012) · Neuroscience · doi:10.1016/j.neuroscience.2012.07.053 · Cited by 68 · see citing works
Frequency analysis of rat hippocampal electrical activity
Coenen, A. M. L. (1975) · Physiology & Behavior · doi:10.1016/0031-9384(75)90053-0 · Cited by 67 · see citing works
Synaptic potentiation in the rat dentate gyrus during exploratory learning
Moser, E. I., Moser, M., & Andersen, P. (1993) · Neuroreport · doi:10.1097/00001756-199312000-00035 · Cited by 64 · see citing works
Scaglione, A., Moxon, K. A., Aguilar, J., & Foffani, G. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1103168108 · Cited by 54 · see citing works
Broyd, S. J., Helps, S. K., & Sonuga-Barke, E. J. S. (2011) · PLoS ONE · doi:10.1371/journal.pone.0017325 · Cited by 48 · see citing works
Schall, K. P., Kerber, J., & Dickson, C. T. (2007) · Journal of Neurophysiology · doi:10.1152/jn.00915.2007 · Cited by 42 · see citing works
Background Synaptic Conductance and Precision of EPSP-Spike Coupling at Pyramidal Cells
Zsiros, V., & Hestrin, S. (2005) · Journal of Neurophysiology · doi:10.1152/jn.01027.2004 · Cited by 41 · see citing works
Klančnik, J. M., & Phillips, A. G. (1991) · Brain Research · doi:10.1016/0006-8993(91)90140-q · Cited by 33 · see citing works
Epinephrine converts long‐term potentiation from transient to durable form in awake rats
Korol, D. L., & Gold, P. E. (2007) · Hippocampus · doi:10.1002/hipo.20372 · Cited by 23 · see citing works
Self-citationBerretta, N., Rossokhin, A. V., Kasyanov, A. M., Sokolov, M., Cherubini, E., & Voronin, L. L. (2000) · Neuropharmacology · doi:10.1016/s0028-3908(00)00076-9 · Cited by 22 · see citing works
Filippov, I. V., Williams, W. C., & Frolov, V. A. (2004) · Neuroscience Letters · doi:10.1016/j.neulet.2004.03.048 · Cited by 20 · see citing works
Zylbertal, A., Yarom, Y., & Wagner, S. (2017) · Journal of Neuroscience · doi:10.1523/jneurosci.3107-16.2017 · Cited by 20 · see citing works
Ferguson, A. L., & Stone, T. W. (2010) · European Journal of Neuroscience · doi:10.1111/j.1460-9568.2010.07157.x · Cited by 17 · see citing works
Bramham, C. R. (1998) · Journal of Neurophysiology · doi:10.1152/jn.1998.79.6.2825 · Cited by 14 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
Cognitive and Physiologic Impacts of the Infraslow Oscillation
Watson, B. O. (2018) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2018.00044 · Cited by 74 · see citing works
Low Frequency Phase-locking of Brain Signals Contribute to Efficient Face Recognition
Wang, Y., Huang, X., Yang, X., Yang, Q., Wang, X., Northoff, G., Pang, Y., Wang, C., Cui, Q., & Chen, H. (2019) · Neuroscience · doi:10.1016/j.neuroscience.2019.10.024 · Cited by 16 · see citing works
Persistent changes in extracellular lactate dynamics following synaptic potentiation
Bingul, D., Kalra, K., Murata, E. M., Belser, A., & Dash, M. B. (2020) · Neurobiology of Learning and Memory · doi:10.1016/j.nlm.2020.107314 · Cited by 10 · see citing works
Self-citationPerez, T. M., Glue, P., Adhia, D. B., Navid, M. S., Zeng, J., Dillingham, P., Smith, M., Niazi, I. K., Young, C. K., & De Ridder, D. (2022) · Trials · doi:10.1186/s13063-022-06863-z · Cited by 8 · see citing works
Infraslow coordination of slow wave activity through altered neuronal synchrony
Dash, M. B. (2019) · SLEEP · doi:10.1093/sleep/zsz170 · Cited by 8 · see citing works
Self-citationMeasuring synaptic transmission and plasticity with fEPSP recordings in behaving mice
Heim, L. R., Shoob, S., de Marcas, L., Zarhin, D., & Slutsky, I. (2022) · STAR Protocols · doi:10.1016/j.xpro.2021.101115 · Cited by 6 · see citing works
Maza, F. J., Urbano, F. J., & Delorenzi, A. (2022) · Scientific Reports · doi:10.1038/s41598-022-15502-1 · Cited by 5 · see citing works
Goldenberg, J. E., Lentzou, S., Ackert-Smith, L. A., Knowlton, H., & Dash, M. B. (2020) · Hippocampus · doi:10.1002/hipo.23258 · Cited by 5 · see citing works
Self-citationPerez, T. M., Glue, P., Adhia, D. B., Smith, M. J., Ridder, D. D., Zeng, J., Dillingham, P. W., & Niazi, I. K. (2021) · Research Square · doi:10.21203/rs.3.rs-173667/v1 · Cited by 3 · see citing works
Altunkaya, S. (2024) · Journal of Applied Biomedicine · doi:10.1016/j.bbe.2024.09.005 · Cited by 2 · see citing works
Perez, T. M., Adhia, D. B., Glue, P., Zeng, J., Dillingham, P. W., Navid, M. S., Niazi, I. K., Young, C. K., Smith, M. L., & Ridder, D. J. M. K. D. (2025) · Cognitive Affective & Behavioral Neuroscience · doi:10.3758/s13415-025-01279-z · Cited by 1 · see citing works
Koşar, B., Yaylalı, O., Baş, D., ÇİMEN, A., Dursun, N., & Süer, C. (2026) · Cognitive Neurodynamics · doi:10.1007/s11571-026-10499-z
- Authors
- Dash, M. B., Ajayi, S., Folsom, L., Gold, P. E., & Korol, D. L.
- Affiliations
- Middlebury College (US)
- Syracuse University (US)
- Corresponding author
- Dash, Michael B.
- Venue
- eneuro
- Publisher
- Society for Neuroscience
- Published
- 2018-01
- Volume
- 5
- Issue
- 1
- Pages
- ENEURO.0403-17.2017
- ISSN
- 2373-2822 (ISSN-L)
- PMC
- PMC5771682
- OpenAlex
- W2783813419
- Cited by
- 14
- References
- 63
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 1 · 2022: 4 · 2021: 1 · 2020: 3 · 2019: 2 · 2018: 1
- FWCI
- 1.04
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- eNeuro (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- National Science Foundation (IOS 0843175, IOS 1318490)
- HHS | National Institutes of Health (P50 AT006268)
- Syracuse University Center for Aging and Policy Studies (NIA P30 AG034464)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Keywords
- spontaneous brain activity, hippocampus, field EPSP, population spike, medial perforant path, trial-to-trial variability, neuronal excitability
- MeSH terms
- Electrocorticography, Animals, Electric Stimulation, Electrodes, Implanted, Hippocampus, Male, Neural Pathways, Time Factors, Rats, Sprague-Dawley, Excitatory Postsynaptic Potentials
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
