The DOI matches its Crossref record; 68 of the 68 references it cites were found in a registry or an index.
Synaptic mechanisms of pattern completion in the hippocampal CA3 network
Abstract
The hippocampal CA3 region plays a key role in learning and memory. Recurrent CA3–CA3 synapses are thought to be the subcellular substrate of pattern completion. However, the synaptic mechanisms of this network computation remain enigmatic. To investigate these mechanisms, we combined functional connectivity analysis with network modeling. Simultaneous recording from up to eight CA3 pyramidal neurons revealed that connectivity was sparse, spatially uniform, and highly enriched in disynaptic motifs (reciprocal, convergence, divergence, and chain motifs). Unitary connections were composed of one or two synaptic contacts, suggesting efficient use of postsynaptic space. Real-size modeling indicated that CA3 networks with sparse connectivity, disynaptic motifs, and single-contact connections robustly generated pattern completion. Thus, macro- and microconnectivity contribute to efficient memory storage and retrieval in hippocampal networks.
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.
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
Collective dynamics of ‘small-world’ networks
Watts, D. J., & Strogatz, S. H. (1998) · Nature · doi:10.1038/30918 · Cited by 43,060
Neural networks and physical systems with emergent collective computational abilities.
Hopfield, J. J. (1982) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.79.8.2554 · Cited by 19,270
Erdős, P., & Rényi, A. (2022) · Publicationes Mathematicae Debrecen · doi:10.5486/pmd.1959.6.3-4.12 · Cited by 5,337
Simple memory: a theory for archicortex
Marr, D. (1971) · Philosophical Transactions of the Royal Society of London. B, Biological Sciences · doi:10.1098/rstb.1971.0078 · Cited by 2,771
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
Eichenbaum (2004) · doi:10.1016/j.neuron.2004.08.028 · Cited by 1,464
Dendritic spine changes associated with hippocampal long-term synaptic plasticity
Engert, F., & Bonhoeffer, T. (1999) · Nature · doi:10.1038/19978 · Cited by 1,412
Hippocampal synaptic enhancement and information storage within a distributed memory system
McNaughton, B. L., & Morris, R. G. M. (1987) · Trends in Neurosciences · doi:10.1016/0166-2236(87)90011-7 · Cited by 1,304
Computational analysis of the role of the hippocampus in memory
Treves, A., & Rolls, E. T. (1994) · Hippocampus · doi:10.1002/hipo.450040319 · Cited by 1,272
Carnevale, N. T., & Hines, M. L. (2006) · Cambridge University Press eBooks · doi:10.1017/cbo9780511541612 · Cited by 1,121
Cited by
Viewpoints: how the hippocampus contributes to memory, navigation and cognition
Lisman, J., Buzsáki, G., Eichenbaum, H., Nadel, L., Ranganath, C., & Redish, A. D. (2017) · Nature Neuroscience · doi:10.1038/nn.4661 · Cited by 851
Heterogeneity within classical cell types is the rule: lessons from hippocampal pyramidal neurons
Cembrowski, M. S., & Spruston, N. (2019) · Nature Reviews Neuroscience · doi:10.1038/s41583-019-0125-5 · Cited by 258
Hippocampal reactivation of random trajectories resembling brownian diffusion
Stella, F., Baracskay, P., O’Neill, J., & Csicsvari, J. (2019) · Neuron · doi:10.1016/j.neuron.2019.01.052 · Cited by 107
Dendritic Spines Prevent Synaptic Voltage Clamp
Beaulieu-Laroche, L., & Harnett, M. T. (2018) · Neuron · doi:10.1016/j.neuron.2017.11.016 · Cited by 79
The Cerebellar Mossy Fiber Synapse as a Model for High-Frequency Transmission in the Mammalian CNS
Delvendahl, I., & Hallermann, S. (2016) · Trends in Neurosciences · doi:10.1016/j.tins.2016.09.006 · Cited by 52
Metadata
- Authors
- Guzman, S. J., Schlögl, A., Frotscher, M., & Jonas, P.
- Venue
- Science
- Published
- 2016-09-09
- Volume
- 353
- Issue
- 6304
- Pages
- 1117-1123
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W2517175011
- Cited by
- 285
- References
- 68
- FWCI
- 17.04
- Type
- journal article
- Language
- en
- Open access
- closed
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Synaptic mechanisms of pattern completion in the hippocampal CA3 network. https://app.cochat.ai/papers/10.1126/science.aaf1836
- The paper
- Guzman, S. J., Schlögl, A., Frotscher, M., & Jonas, P. (2016). Synaptic mechanisms of pattern completion in the hippocampal CA3 network. Science. https://doi.org/10.1126/science.aaf1836
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.