Improved Reversal Learning and Working Memory and Enhanced Reactivity to Novelty in Mice with Enhanced GABAergic Innervation in the Dentate Gyrus
Open accessAbstract
The balance between excitation and inhibition controls fundamental aspects of the hippocampal function. Here, we report an increase in the ratio of inhibitory to excitatory neurons in the dentate gyrus, accompanied by γ-aminobutyric acid(A) (GABA(A)) receptor-dependent impairment of synaptic plasticity and enhancement of activity-dependent changes in excitability in anesthetized adult mice deficient for the extracellular matrix glycoprotein tenascin-R (TNR). TNR-deficient mice showed faster reversal learning, improved working memory, and enhanced reactivity to novelty than wild-type littermates. Remarkably, in wild-type and TNR-deficient mice, faster reversal learning rates correlated at the individual animal level with ratios of parvalbumin-positive interneurons to granule cells and densities of parvalbumin-positive terminals on somata of granule cells. Our data demonstrate that modification of the extracellular matrix by ablation of TNR leads to a new structural and functional design of the dentate gyrus, with enhanced GABAergic innervation, that is, enhanced ratio of inhibitory to excitatory cells, and altered plasticity, promoting working memory and reversal learning. In wild-type mice, the enhanced ratio of inhibitory to excitatory cells in the dentate gyrus also positively correlated with reversal learning, indicating that level of inhibition regulates specific aspects of learning independent of the TNR gene.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
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?
Significantly enhanced working memory and reversal learning in the Morris water maze task is found in TNR -/- global knockout mice.
“Similarly, significantly enhanced working memory and reversal learning in the Morris water maze task is found in TNR -/- global knockout mice [113] (Fig. 2C).”
From The extracellular matrix and perineuronal nets in memory (2022) · cites this paper as [113]
Cites
Cortical inhibitory neurons and schizophrenia
Lewis, D. A., Hashimoto, T., & Volk, D. W. (2005) · Nature Reviews Neuroscience · doi:10.1038/nrn1648 · Cited by 2,297 · see citing works
Weber, P., Bartsch, U., Rasband, M. N., Czaniera, R., Lang, Y., Bluethmann, H., Margolis, R. U., Levinson, S. R., Shrager, P., Montag, D., et al. (1999) · The Journal of Neuroscience · doi:10.1523/jneurosci.19-11-04245.1999 · Cited by 247 · see citing works
Self-citationNormal spatial learning despite regional inhibition of LTP in mice lacking Thy-1
Nosten-Bertrand, M., Errington, M. L., Murphy, K. P. S. J., Tokugawa, Y., Barboni, E., Kozlova, E., Michalovich, D., Morris, R. G. M., Silver, J., Stewart, C. L., et al. (1996) · Nature · doi:10.1038/379826a0 · Cited by 232 · see citing works
Abdul-Monim, Z., Neill, J. C., & Reynolds, G. P. (2007) · Journal of Psychopharmacology · doi:10.1177/0269881107067097 · Cited by 206 · see citing works
Structural and Functional Aberrations in the Cerebral Cortex of Tenascin-C Deficient Mice
Irintchev, A., Rollenhagen, A., Troncoso, E., Kiss, J. Z., & Schachner, M. (2005) · Cerebral Cortex · doi:10.1093/cercor/bhh195 · Cited by 137 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
The roles of perineuronal nets and the perinodal extracellular matrix in neuronal function
Fawcett, J. W., Oohashi, T., & Pizzorusso, T. (2019) · Nature Reviews Neuroscience · doi:10.1038/s41583-019-0196-3 · Cited by 589 · see citing works
The dual role of the extracellular matrix in synaptic plasticity and homeostasis
Dityatev, A., Schachner, M., & Sonderegger, P. (2010) · Nature Reviews Neuroscience · doi:10.1038/nrn2898 · Cited by 559 · see citing works
Self-citationSala, M., Braida, D., Lentini, D., Busnelli, M., Bulgheroni, E., Capurro, V., Finardi, A., Donzelli, A., Pattini, L., Rubino, T., et al. (2011) · Biological Psychiatry · doi:10.1016/j.biopsych.2010.12.022 · Cited by 375 · see citing works
Romberg, C., Yang, S., Melani, R., Andrews, M. R., Horner, A. E., Spillantini, M. G., Bussey, T. J., Fawcett, J. W., Pizzorusso, T., & Saksida, L. M. (2013) · The Journal of Neuroscience · doi:10.1523/jneurosci.6267-11.2013 · Cited by 231 · see citing works
Kochlamazashvili, G., Henneberger, C., Bukalo, O., Dvoretskova, E., Senkov, O., Lievens, P. M.-J., Westenbroek, R., Engel, A. K., Catterall, W. A., Rusakov, D. A., et al. (2010) · Neuron · doi:10.1016/j.neuron.2010.05.030 · Cited by 215 · see citing works
Self-citationThe extracellular matrix and perineuronal nets in memory
Fawcett, J. W., Fyhn, M., Jendelova, P., Kwok, J. C. F., Ruzicka, J., & Sorg, B. A. (2022) · Molecular Psychiatry · doi:10.1038/s41380-022-01634-3 · Cited by 169 · see citing works
Geissler, M., Gottschling, C., Aguado, A., Rauch, U., Wetzel, C. H., Hatt, H., & Faissner, A. (2013) · The Journal of Neuroscience · doi:10.1523/jneurosci.3275-12.2013 · Cited by 140 · see citing works
Tong, L. M., Djukic, B., Arnold, C., Gillespie, A. K., Yoon, S. Y., Wang, M. M., Zhang, O., Knoferle, J., Rubenstein, J. L. R., Alvarez-Buylla, A., et al. (2014) · The Journal of Neuroscience · doi:10.1523/jneurosci.0693-14.2014 · Cited by 123 · see citing works
Releasing Addiction Memories Trapped in Perineuronal Nets
Lasek, A. W., Chen, H., & Chen, W.-Y. (2018) · Trends in Genetics · doi:10.1016/j.tig.2017.12.004 · Cited by 71 · see citing works
Chondroitin Sulfate Proteoglycan Tenascin-R Regulates Glutamate Uptake by Adult Brain Astrocytes
Okuda, H., Tatsumi, K., Morita, S., Shibukawa, Y., Korekane, H., Horii-Hayashi, N., Wada, Y., Taniguchi, N., & Wanaka, A. (2014) · Journal of Biological Chemistry · doi:10.1074/jbc.m113.504787 · Cited by 33 · see citing works
Anderson, M. D., Paylor, J. W., Scott, G. A., Greba, Q., Winship, I. R., & Howland, J. G. (2020) · Learning & Memory · doi:10.1101/lm.050245.119 · Cited by 16 · see citing works
Zhang, Y., Wang, Z., Ju, J., Liao, J., & Zhou, Q. (2021) · Journal of Psychiatry and Neuroscience · doi:10.1503/jpn.200151 · Cited by 14 · see citing works
- Authors
- Morellini, F., Sivukhina, E., Stoenica, L., Oulianova, E., Bukalo, O., Jakovcevski, I., Dityatev, A., Irintchev, A., & Schachner, M.
- Affiliations
- University Medical Center Hamburg-Eppendorf (DE)
- Italian Institute of Technology (IT)
- Rutgers, The State University of New Jersey (US)
- Venue
- Cerebral Cortex
- Publisher
- Oxford University Press (OUP)
- Published
- 2010-03-01
- Volume
- 20
- Issue
- 11
- Pages
- 2712-2727
- ISSN
- 1047-3211 (ISSN-L)
- 1460-2199
- OpenAlex
- W2123320547
- Cited by
- 104
- References
- 5
- Citations by year
- 2026: 6 · 2025: 4 · 2024: 5 · 2023: 4 · 2022: 4 · 2021: 5 · 2020: 5 · 2019: 3 · 2018: 7 · 2017: 10 · 2016: 5 · 2015: 3 · 2014: 9 · 2013: 13 · 2012: 9
- FWCI
- 4.38
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Cerebral Cortex (publishedVersion)
- PubMed (publishedVersion)
- Rutgers University Community Repository (Rutgers University) (submittedVersion)
- INFM-OAR (INFN Catania) (submittedVersion, other-oa)
- Zenodo (CERN European Organization for Nuclear Research) (other-oa)
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Life Sciences › Neuroscience › Developmental Neuroscience › Neurogenesis and neuroplasticity mechanisms
- Keywords
- reversal learning, working memory, novelty reactivity, dentate gyrus, GABAergic innervation, tenascin-R, extracellular matrix, parvalbumin interneurons, granule cells, synaptic plasticity, hippocampus, excitation-inhibition balance, GABAA receptor
- MeSH terms
- Animals, Cognition, gamma-Aminobutyric Acid, Interneurons, Learning, Male, Memory, Mice, Inbred C57BL, Neural Inhibition, Mice, Knockout, Dentate Gyrus, Tenascin, 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