Cited by 198Neural dynamics and brain functionMemory and Neural MechanismsNeuroscience and Neuropharmacology Research

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Interneuronal mechanisms of hippocampal theta oscillations in a full-scale model of the rodent CA1 circuit

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Published version of a preprint

Abstract

The hippocampal theta rhythm plays important roles in information processing; however, the mechanisms of its generation are not well understood. We developed a data-driven, supercomputer-based, full-scale (1:1) model of the rodent CA1 area and studied its interneurons during theta oscillations. Theta rhythm with phase-locked gamma oscillations and phase-preferential discharges of distinct interneuronal types spontaneously emerged from the isolated CA1 circuit without rhythmic inputs. Perturbation experiments identified parvalbumin-expressing interneurons and neurogliaform cells, as well as interneuronal diversity itself, as important factors in theta generation. These simulations reveal new insights into the spatiotemporal organization of the CA1 circuit during theta oscillations.

Overview

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Written from the paper’s full text.

TL;DR

A data-driven, full-scale model of the isolated rodent CA1 spontaneously generated theta (~7.8 Hz) and phase-locked gamma oscillations without rhythmic external inputs. Perturbation experiments implicated PV+ interneurons, neurogliaform cells, pyramidal recurrent connections, and interneuronal diversity itself in theta generation.

Key findings

  • The model contained 338,740 cells (311,500 pyramidal cells and 27,240 interneurons), 454,700 artificial stimulating afferents, and 5.19 billion synapses; it spontaneously produced stable theta at 7.8 Hz and gamma oscillations (25–80 Hz), with gamma amplitude phase-locked to the theta trough.
  • Distinct interneuron types showed phase-preferential firing: PV+ basket, bistratified, and O-LM cells fired near the theta trough, whereas ivy, neurogliaform, CCK+ basket, and axo-axonic cells fired least around the trough; 71% (5/7) of interneuron types with experimental data matched anesthetized in vivo phase maxima.
  • Muting pyramidal cell output or CA1 pyramidal-to-pyramidal connections collapsed theta; muting PV-family, CCK+ basket, or neurogliaform cell output strongly reduced theta, while muting O-LM, ivy, or SC-A cells had no effect. Partial PV+ muting disrupted theta more than partial SOM+ muting.
  • Reducing interneuron diversity abolished theta: giving all interneurons one electrophysiological profile, or morphing them toward PV+ basket cells, did not restore theta. Removing the GABAB component of neurogliaform synapses reduced theta power, but replacing it with a scaled-up fast GABAA conductance with equivalent charge transfer restored theta.

Methods

  • The CA1 network was implemented in parallel NEURON 7.4 with one multicompartmental pyramidal cell type and eight interneuron types; connectivity and cell numbers were taken from Bezaire and Soltesz (2013), and simulations used fixed time steps of 0.01–0.025 ms for 2000 or 4000 ms on supercomputers.
  • CA3 and entorhinal afferents were modeled as independent Poisson spike trains; control theta emerged at a mean afferent firing rate of 0.65 Hz, and analyses included spike density functions, Welch periodograms, spectrograms, an LFP analog, Rayleigh tests for phase modulation, and ANOVA for GABAB-related simulations.
  • Perturbation experiments muted each cell type’s output, altered pyramidal-to-pyramidal connection numbers, reduced interneuron diversity, and manipulated neurogliaform GABAB/GABAA signaling.

Limitations

  • Stated: about 30% of known CA1 interneurons were omitted due to paucity of quantitative data, likely making inhibition weaker than biological; pyramidal cells fired more than in vivo, and although scaled-up inhibition produced only 1% active pyramidal cells firing at 1.8 Hz, it was not used because the source of the additional inhibition was unidentified.
  • Stated: the model did not include neuromodulators, gap junctions, short-term plasticity, glial dynamics, pyramidal cell diversity, or cell-to-cell variability; the emergent theta likely resembled the atropine-resistant form, some single-cell electrophysiology came from mouse while the network was rat, and no isolated-CA1 data were available for interneuron phase preferences, so comparisons used anesthetized in vivo data.
  • Evident: theta appeared only within particular afferent excitation levels (around 0.65 Hz; lower or higher levels disrupted it), gamma was not examined further, and the authors note they could not rule out a hypothetical theta regime somewhere in the low-diversity parameter space.

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Registry

Crossref · 10.7554/elife.18566

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Show all 91 claims

  • It may state two separate claims as one. 23
  • Probably not a substantial claim. 37
53 of 53
  • The paper relies on this without support.

    The CA1 area is one of the most extensively studied brain regions, with abundant anatomical and electrophysiological data about its organization.

    “Because the CA1 area is one of the most extensively studied brain regions, there are abundant anatomical and electrophysiological data about its organization, making it a logical choice for the development of a full-scale model.”
  • The paper relies on this without support.

    The model parameters that could not be constrained by experimental data do not critically affect the model's conclusions.

    “In addition, the remaining parameters that could not be constrained by experimental data were documented, with the assumptions used to arrive at them explicitly listed in Table 2 of Bezaire and Soltesz (2013) and additional parameter calculations described in the Appendix of the present paper, section 'Inhibitory connectivity'.”
  • The paper relies on this without support.

    The missing 30% of interneurons do not qualitatively alter the generation of theta oscillations in the model.

    “The remaining 30% of the interneurons were not included in the model due to paucity of quantitative data (Bezaire and Soltesz, 2013).”
  • The paper relies on this without support.

    The experimental phase preferences from anesthetized rats are comparable to the model's conditions.

    “Firing probability by cell type as a function of theta phase for (A) model and (B) experimental cells under anesthesia (histograms adapted with permission from Figure 2, Figure 5B left, and Figure 6F respectively from Klausberger and Somogyi, 2008; Fuentealba et al., 2008; Fuentealba et al., 2010).”
  • The paper relies on this without support.

    The phase preferences of interneurons in anesthetized animals are comparable to those in the model's conditions for the purpose of validating the model.

    “because no data are available on the phase preferential firing of morphologically identified interneurons from the isolated CA1 preparation, comparison is made here with results from anesthetized animals, from which the most complete data sets are available”
  • The paper relies on this without support.

    The parameter space explored for low-diversity configurations is sufficient to conclude that interneuronal diversity is necessary for spontaneous theta oscillations.

    “While we could not rule out a hypothetical theta regime somewhere in the parameter space of such low-diversity configurations, any theta solution space would likely be smaller and more elusive than we were able to determine in the control configuration (Figure 6A).”
  • The paper relies on this without support.

    The phase of LFP theta recorded in the stratum radiatum is approximately 180 degrees out of phase with the pyramidal cell layer theta used in this paper.

    “note that Ferguson and colleagues used LFP theta recorded in the stratum radiatum as reference, which is approximately 180 degrees out of phase with the pyramidal cell layer theta used in this paper”
  • The paper relies on this without support.

    Model neurons sometimes behave much differently than expected when subjected to current sweep protocols or synaptic inputs that are outside the range of the original protocols used to construct the model.

    “Model neurons sometimes behave much differently than expected when subjected to current sweep protocols or synaptic inputs that are outside the range of the original protocols used to construct the model”
  • The authors state this as an assumption.

    All available incoming inhibitory synapses onto interneurons in a layer have an equal chance of being innervated by the available inhibitory boutons targeting interneurons in that layer.

    “All available incoming inhibitory synapses onto interneurons in a layer have an equal chance of being innervated by the available inhibitory boutons targeting interneurons in that layer”
  • The paper relies on this without support.

    There is no reported evidence for major, systematic differences in key parameters such as the phase specific firing of rat and mouse interneurons in vivo.

    “there is no reported evidence for major, systematic differences in key parameters such as the phase specific firing of rat and mouse interneurons in vivo”
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Metadata

Authors
Bezaire, M. J., Raikov, I., Burk, K., Vyas, D., & Soltesz, I.
Affiliations
  • University of California, Irvine (US)
  • Department of Neurosurgery, Stanford University, Stanford, United States
Venue
eLife
Published
2016-12-23
Volume
5
ISSN
2050-084X (ISSN-L)
OpenAlex
W2561068888
Cited by
198
References
160
Citations by year
2026: 8 · 2025: 16 · 2024: 27 · 2023: 26 · 2022: 32 · 2021: 25 · 2020: 15 · 2019: 28 · 2018: 15 · 2017: 5 · 2016: 1
FWCI
10.39
Type
journal article
Language
en
Open access
Locations
  • eLife (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • National Institutes of Health (F32NS090753, NS35915, NS090583)
  • National Science Foundation (DGE-0808392, XSEDE Allocations - TG-IBN140007, XSEDE Allocations - TG-IBN130022, XSEDE Allocations - TG-IBN100011, IOS-1310378)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
  • Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
Keywords
hippocampal theta rhythm, interneurons, parvalbumin interneurons, neurogliaform cells, gamma oscillations, phase locking, computational neuroscience, spontaneous oscillations
MeSH terms
Animals, Interneurons, Neuroglia, Theta Rhythm, Neural Networks, Computer, Mice, Rats, CA1 Region, Hippocampal, Spatio-Temporal Analysis

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