The DOI matches its Crossref record; 75 of the 76 references it cites were found in a registry or an index.
Identification of a Functional Connectome for Long-Term Fear Memory in Mice
Open accessAbstract
Long-term memories are thought to depend upon the coordinated activation of a broad network of cortical and subcortical brain regions. However, the distributed nature of this representation has made it challenging to define the neural elements of the memory trace, and lesion and electrophysiological approaches provide only a narrow window into what is appreciated a much more global network. Here we used a global mapping approach to identify networks of brain regions activated following recall of long-term fear memories in mice. Analysis of Fos expression across 84 brain regions allowed us to identify regions that were co-active following memory recall. These analyses revealed that the functional organization of long-term fear memories depends on memory age and is altered in mutant mice that exhibit premature forgetting. Most importantly, these analyses indicate that long-term memory recall engages a network that has a distinct thalamic-hippocampal-cortical signature. This network is concurrently integrated and segregated and therefore has small-world properties, and contains hub-like regions in the prefrontal cortex and thalamus that may play privileged roles in memory expression.
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.
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?
In the citing paper
“Graph theoretical analysis has been applied to Fos datasets to characterize functional relationships in rodent neural circuits66–69.”
From Insular cortex mediates approach and avoidance responses to social affective stimuli (2018) · cites this paper as [66]
In the citing paper
“A functional connectome study further revealed that, whereas the absolute hippocampal activity decreases over time, the connectivity of the hippocampus with other brain regions is strengthened, which is associated with remote memory 31 .”
From Role of the hippocampus in systems consolidation of remote fear memory (2026) · cites this paper as [31]
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
The Mouse Brain in Stereotaxic Coordinates
Paxinos, G. (2001) · Cited by 12,859
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
A synaptic model of memory: long-term potentiation in the hippocampus
Bliss, T. V. P., & Collingridge, G. L. (1993) · Nature · doi:10.1038/361031a0 · Cited by 11,566
Complex network measures of brain connectivity: Uses and interpretations
Rubinov, M., & Sporns, O. (2010) · NeuroImage · doi:10.1016/j.neuroimage.2009.10.003 · Cited by 11,522
Error and attack tolerance of complex networks
Albert, R., Jeong, H., & Barabási, A.-L. (2000) · Nature · doi:10.1038/35019019 · Cited by 7,534
Error and attack tolerance of complex networksPreprint
Albert, R., Jeong, H., & Barabási, A.-Ĺ. (2000) · Cited by 6,554
McClelland, J. L., McNaughton, B. L., & O'Reilly, R. C. (1995) · Psychological Review · doi:10.1037/0033-295x.102.3.419 · Cited by 5,256
The Organization of Behavior; A Neuropsychological Theory.
Attneave, F., B., M., & Hebb, D. O. (1950) · The American Journal of Psychology · doi:10.2307/1418888 · Cited by 5,146
Efficient behavior of small-world networks
Latora, V., & Marchiori, M. (2001) · Physical Review Letters · doi:10.1103/physrevlett.87.198701 · Cited by 5,119
Flagged first, then by citations
1 of the 76 references couldn’t be matched to a known paper.
Research works printed but not linked: 1
- Lashley KS (1950) In search of the engram. In: Society of Experimental Biology Symposium 4. Oxford, England: Academic Press. pp 454–482.
Cited by
Sorted by citations
Memory engrams: Recalling the past and imagining the future
Josselyn, S. A., & Tonegawa, S. (2020) · Science · doi:10.1126/science.aaw4325 · Cited by 1,087
The Consolidation and Transformation of Memory
Dudai, Y., Karni, A., & Born, J. (2015) · Neuron · doi:10.1016/j.neuron.2015.09.004 · Cited by 741
Squire, L. R., Genzel, L., Wixted, J. T., & Morris, R. G. (2015) · Cold Spring Harbor Perspectives in Biology · doi:10.1101/cshperspect.a021766 · Cited by 700
Josselyn, S. A., Köhler, S., & Frankland, P. W. (2015) · Nature reviews. Neuroscience · doi:10.1038/nrn4000 · Cited by 749
Self-citationTemporal evolution of cortical ensembles promoting remote memory retrieval
DeNardo, L. A., Liu, C. D., Allen, W. E., Adams, E. L., Friedmann, D., Dadgar‐Kiani, E., Fu, L., Guenthner, C. J., Lee, J. H., Tessier‐Lavigne, M., et al. (2019) · Nature Neuroscience · doi:10.1038/s41593-018-0318-7 · Cited by 646
Metadata
- Authors
- Wheeler, A. L., Teixeira, C. M., Wang, A. H., Xiong, X., Kovacevic, N., Lerch, J. P., McIntosh, A. R., Parkinson, J., & Frankland, P. W.
- Affiliations
- University of Toronto (CA)
- Hospital for Sick Children (CA)
- Baycrest Hospital (CA)
- Corresponding author
- Frankland, Paul W.
- ORCID
- Venue
- PLoS Computational Biology
- Publisher
- Public Library of Science (PLoS)
- Published
- 2013-01-03
- Volume
- 9
- Issue
- 1
- Pages
- e1002853
- ISSN
- 1553-734X (ISSN-L)
- 1553-7358
- PMC
- PMC3536620
- OpenAlex
- W1995227930
- Cited by
- 315
- References
- 76
- Citations by year
- 2026: 20 · 2025: 30 · 2024: 31 · 2023: 42 · 2022: 33 · 2021: 36 · 2020: 20 · 2019: 22 · 2018: 21 · 2017: 24 · 2016: 6 · 2015: 11 · 2014: 13 · 2013: 5
- FWCI
- 6.37
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- PLoS Computational Biology (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Figshare (submittedVersion, cc-by)
- Funders
- Hospital for Sick Children
- Canadian Institutes of Health Research (82940_1, MOP77561, 82940)
- Fundação para a Ciência e a Tecnologia
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory Processes and Influences
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Keywords
- memory retrieval, functional connectome, Fos expression, memory age, thalamus, hippocampus, prefrontal cortex, small-world networks, hub regions, memory traces, mice
- MeSH terms
- Animals, Brain, Fear, Immunohistochemistry, Memory, Mice, Mutant Strains, Nerve Net, Mice
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