The DOI matches its Crossref record; 78 of the 78 references it cites were found in a registry or an index.
Neuronal types in the mouse amygdala and their transcriptional response to fear conditioning
Open accessAbstract
The amygdala is a brain region primarily associated with emotional response. The use of genetic markers and single-cell transcriptomics can provide insights into behavior-associated cell state changes. Here we present a detailed cell-type taxonomy of the adult mouse amygdala during fear learning and memory consolidation. We perform single-cell RNA sequencing on naïve and fear-conditioned mice, identify 130 neuronal cell types and validate their spatial distributions. A subset of all neuronal types is transcriptionally responsive to fear learning and memory retrieval. The activated engram cells upregulate activity-response genes and coordinate the expression of genes associated with neurite outgrowth, synaptic signaling, plasticity and development. We identify known and previously undescribed candidate genes responsive to fear learning. Our molecular atlas may be used to generate hypotheses to unveil the neuron types and neural circuits regulating the emotional component of learning and memory.
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
Figures
















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?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“though VIP+ GABAergic neurons have been identified within the MeA [73].”
From Rapid changes in plasma corticosterone and medial amygdala transcriptome profiles during social status change reveal molecular pathways associated with a major life history transition in mouse dominance hierarchies (2025) · cites this paper as [73]
Experimental — accuracy not yet measured
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
Fast, sensitive and accurate integration of single-cell data with Harmony
Korsunsky, I., Millard, N., Fan, J., Slowikowski, K., Zhang, F., Wei, K., Baglaenko, Y., Brenner, M., Loh, P.-R., & Raychaudhuri, S. (2019) · Nature Methods · doi:10.1038/s41592-019-0619-0 · Cited by 10,488
Genome-wide atlas of gene expression in the adult mouse brain
Lein, E. S., Hawrylycz, M. J., Ao, N., Ayres, M., Bensinger, A., Bernard, A., Boe, A. F., Boguski, M. S., Brockway, K. S., Byrnes, E. J., et al. (2007) · Nature · doi:10.1038/nature05453 · Cited by 5,572
Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq
Zeisel, A., Muñoz-Manchado, A. B., Codeluppi, S., Lönnerberg, P., La Manno, G., Juréus, A., Marques, S., Munguba, H., He, L., Betsholtz, C., et al. (2015) · Science · doi:10.1126/science.aaa1934 · Cited by 3,124
Self-citationMolecular Architecture of the Mouse Nervous System
Zeisel, A., Hochgerner, H., Lönnerberg, P., Johnsson, A., Memic, F., van der Zwan, J., Häring, M., Braun, E., Borm, L. E., La Manno, G., et al. (2018) · Cell · doi:10.1016/j.cell.2018.06.021 · Cited by 2,552
Self-citationShared and distinct transcriptomic cell types across neocortical areas
Tasic, B., Yao, Z., Graybuck, L. T., Smith, K. A., Nguyen, T. N., Bertagnolli, D., Goldy, J., Garren, E., Economo, M. N., Viswanathan, S., et al. (2018) · Nature · doi:10.1038/s41586-018-0654-5 · Cited by 1,746
Molecular diversity and specializations among the cells of the adult mouse brain
Saunders, A., Macosko, E. Z., Wysoker, A., Goldman, M., Krienen, F. M., de Rivera, H., Bien, E., Baum, M., Bortolin, L., Wang, S., et al. (2018) · Cell · doi:10.1016/j.cell.2018.07.028 · Cited by 1,531
Molecular, spatial, and functional single-cell profiling of the hypothalamic preoptic region
Moffitt, J. R., Bambah-Mukku, D., Eichhorn, S. W., Vaughn, E., Shekhar, K., Perez, J. D., Rubinstein, N. D., Hao, J., Regev, A., Dulac, C., et al. (2018) · Science · doi:10.1126/science.aau5324 · Cited by 1,365
The art of using t-SNE for single-cell transcriptomics
Kobak, D., & Berens, P. (2019) · Nature Communications · doi:10.1038/s41467-019-13056-x · Cited by 1,161
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
A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation
Yao, Z., van Velthoven, C. T. J., Nguyen, T. N., Goldy, J., Sedeno-Cortes, A. E., Baftizadeh, F., Bertagnolli, D., Casper, T., Chiang, M., Crichton, K., et al. (2021) · Cell · doi:10.1016/j.cell.2021.04.021 · Cited by 1,065
Pitkänen, A., Savander, V., & LeDoux, J. E. (1997) · Trends in Neurosciences · doi:10.1016/s0166-2236(97)01125-9 · Cited by 980
Genetic dissection of an amygdala microcircuit that gates conditioned fear
Haubensak, W., Kunwar, P. S., Cai, H., Ciocchi, S., Wall, N. R., Ponnusamy, R., Biag, J., Dong, H.-W., Deisseroth, K., Callaway, E. M., et al. (2010) · Nature · doi:10.1038/nature09553 · Cited by 840 · cited 2×
“These neurons likely constitute one or several types described for their involvement in both fear and appetitive behaviors 12,44,45 .”
BackgroundResultDifferential Control of Learning and Anxiety along the Dorsoventral Axis of the Dentate Gyrus
Kheirbek, M. A., Drew, L. J., Burghardt, N. S., Costantini, D. O., Tannenholz, L., Ahmari, S. E., Zeng, H., Fenton, A. A., & Hen, R. (2013) · Neuron · doi:10.1016/j.neuron.2012.12.038 · Cited by 713
Spatial organization of the somatosensory cortex revealed by osmFISH
Codeluppi, S., Borm, L. E., Zeisel, A., Manno, G. L., van Lunteren, J. A., Svensson, C. I., & Linnarsson, S. (2018) · Nature Methods · doi:10.1038/s41592-018-0175-z · Cited by 635
Self-citationTing, J. T., Daigle, T. L., Chen, Q., & Feng, G. (2014) · Methods in molecular biology · doi:10.1007/978-1-4939-1096-0_14 · Cited by 631
BLA to vHPC inputs modulate anxiety-related behaviors
Felix-Ortiz, A. C., Beyeler, A., Seo, C., Leppla, C. A., Wildes, C. P., & Tye, K. M. (2013) · Neuron · doi:10.1016/j.neuron.2013.06.016 · Cited by 592
Selective Erasure of a Fear Memory
Han, J., Kushner, S. A., Yiu, A. P., Hsiang, H., Buch, T., Waisman, A., Bontempi, B., Neve, R. L., Frankland, P. W., & Josselyn, S. A. (2009) · Science · doi:10.1126/science.1164139 · Cited by 570
Amygdala interneuron subtypes control fear learning through disinhibition
Wolff, S. B. E., Gründemann, J., Tovote, P., Krabbe, S., Jacobson, G. A., Müller, C. R., Herry, C., Ehrlich, I., Friedrich, R. W., Letzkus, J. J., et al. (2014) · Nature · doi:10.1038/nature13258 · Cited by 515
A competitive inhibitory circuit for selection of active and passive fear responses
Fadok, J. P., Krabbe, S., Marković, M., Courtin, J., Xu, C., Massi, L., Botta, P., Bylund, K., Müller, C. R., Kovacevic, A., et al. (2017) · Nature · doi:10.1038/nature21047 · Cited by 499
Single-cell analysis of experience-dependent transcriptomic states in the mouse visual cortex
Hrvatin, S., Hochbaum, D. R., Nagy, M. A., Cicconet, M., Robertson, K., Cheadle, L., Zilionis, R., Ratner, A., Borges-Monroy, R., Klein, A. M., et al. (2018) · Nature Neuroscience · doi:10.1038/s41593-017-0029-5 · Cited by 497
Functional circuit architecture underlying parental behaviour
Kohl, J., Babayan, B. M., Rubinstein, N. D., Autry, A. E., Marin-Rodriguez, B., Kapoor, V., Miyamichi, K., Zweifel, L. S., Luo, L., Uchida, N., et al. (2018) · Nature · doi:10.1038/s41586-018-0027-0 · Cited by 470
Basolateral to Central Amygdala Neural Circuits for Appetitive Behaviors
Kim, J., Zhang, X., Muralidhar, S., LeBlanc, S., & Tonegawa, S. (2017) · Neuron · doi:10.1016/j.neuron.2017.02.034 · Cited by 467
Antagonistic negative and positive neurons of the basolateral amygdala
Kim, J., Pignatelli, M., Xu, S., Itohara, S., & Tonegawa, S. (2016) · Nature Neuroscience · doi:10.1038/nn.4414 · Cited by 464
Choi, G. B., Dong, H.-W., Murphy, A. J., Valenzuela, D. M., Yancopoulos, G. D., Swanson, L. W., & Anderson, D. J. (2005) · Neuron · doi:10.1016/j.neuron.2005.04.011 · Cited by 462
Neural control of maternal and paternal behaviors
Dulac, C., O’Connell, L. A., & Wu, Z. (2014) · Science · doi:10.1126/science.1253291 · Cited by 457
Detecting Activated Cell Populations Using Single-Cell RNA-Seq
Wu, Y. E., Pan, L., Zuo, Y., Li, X., & Hong, W. (2017) · Neuron · doi:10.1016/j.neuron.2017.09.026 · Cited by 438
Cellular Taxonomy of the Mouse Striatum as Revealed by Single-Cell RNA-Seq
Gokce, O., Stanley, G. M., Treutlein, B., Neff, N. F., Camp, J. G., Malenka, R. C., Rothwell, P. E., Fuccillo, M. V., Südhof, T. C., & Quake, S. R. (2016) · Cell Reports · doi:10.1016/j.celrep.2016.06.059 · Cited by 430
Competition between engrams influences fear memory formation and recall
Rashid, A. J., Chen, Y., Mercaldo, V., Hsiang, H., Park, S., Cole, C. J., Cristofaro, A. D., Yu, J., Ramakrishnan, C., Lee, S. Y., et al. (2016) · Science · doi:10.1126/science.aaf0594 · Cited by 424
Nuclear RNA-seq of single neurons reveals molecular signatures of activation
Lacar, B., Linker, S. B., Jaeger, B. N., Krishnaswami, S. R., Barron, J. J., Kelder, M. J. E., Parylak, S. L., Paquola, A. C. M., Venepally, P., Novotny, M., et al. (2016) · Nature Communications · doi:10.1038/ncomms11022 · Cited by 405
Hall, J., Thomas, K. L., & Everitt, B. J. (2001) · Journal of Neuroscience · doi:10.1523/jneurosci.21-06-02186.2001 · Cited by 398
Central amygdala PKC-δ+ neurons mediate the influence of multiple anorexigenic signals
Cai, H., Haubensak, W. E., Anthony, T. E., & Anderson, D. J. (2014) · Nature Neuroscience · doi:10.1038/nn.3767 · Cited by 388
An Inhibitory Interface Gates Impulse Traffic between the Input and Output Stations of the Amygdala
Royer, S., Martina, M., & Paré, D. (1999) · Journal of Neuroscience · doi:10.1523/jneurosci.19-23-10575.1999 · Cited by 350
Shumyatsky, G. P., Tsvetkov, E., Malleret, G., Vronskaya, S., Hatton, M., Hampton, L. L., Battey, J. F., Dulac, C. G., Kandel, E. R., & Bolshakov, V. Y. (2002) · Cell · doi:10.1016/s0092-8674(02)01116-9 · Cited by 326
Organization of valence-encoding and projection-defined neurons in the basolateral amygdala
Beyeler, A., Chang, C.-J., Silvestre, M., Lévêque, C., Namburi, P., Wildes, C. P., & Tye, K. M. (2018) · Cell Reports · doi:10.1016/j.celrep.2017.12.097 · Cited by 306 · cited 2×
“In addition, their molecular identities correlated with different anterior–posterior distributions, which could link to previous findings that BLA principal cells along the anterior–posterior axis encode opposing valences 5,11,52 .”
BackgroundDistinct Hippocampal Pathways Mediate Dissociable Roles of Context in Memory Retrieval
Xu, C., Krabbe, S., Gründemann, J., Botta, P., Fadok, J. P., Osakada, F., Saur, D., Grewe, B. F., Schnitzer, M. J., Callaway, E. M., et al. (2016) · Cell · doi:10.1016/j.cell.2016.09.051 · Cited by 297
Amygdala Inhibitory Circuits Regulate Associative Fear Conditioning
Krabbe, S., Gründemann, J., & Lüthi, A. (2017) · Biological Psychiatry · doi:10.1016/j.biopsych.2017.10.006 · Cited by 268
Multimodal analysis of cell types in a hypothalamic node controlling social behavior
Kim, D.-W., Yao, Z., Graybuck, L. T., Kim, T. K., Nguyen, T. N., Smith, K. A., Fong, O., Yi, L., Koulena, N., Pierson, N., et al. (2019) · Cell · doi:10.1016/j.cell.2019.09.020 · Cited by 259
Diversity of Interneurons in the Dorsal Striatum Revealed by Single-Cell RNA Sequencing and PatchSeq
Muñoz-Manchado, A. B., Bengtsson Gonzales, C., Zeisel, A., Munguba, H., Bekkouche, B., Skene, N. G., Lönnerberg, P., Ryge, J., Harris, K. D., Linnarsson, S., et al. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.07.053 · Cited by 229
Self-citationDistinct molecular programs regulate synapse specificity in cortical inhibitory circuits
Favuzzi, E., Deogracias, R., Marques–Smith, A., Maeso, P. A., Jézéquel, J., Exposito-Alonso, D., Balia, M., Kroon, T., Hinojosa, A. J., Maraver, E. F., et al. (2019) · Science · doi:10.1126/science.aau8977 · Cited by 224
Decoding molecular and cellular heterogeneity of mouse nucleus accumbens
Chen, R., Blosser, T. R., Djekidel, M. N., Hao, J., Bhattacherjee, A., Chen, W., Tuesta, L. M., Zhuang, X., & Zhang, Y. (2021) · Nature Neuroscience · doi:10.1038/s41593-021-00938-x · Cited by 191
Prolactin action in the medial preoptic area is necessary for postpartum maternal nursing behavior
Brown, R. S. E., Aoki, M., Ladyman, S. R., Phillipps, H. R., Wyatt, A. K., Boehm, U., & Grattan, D. R. (2017) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1708025114 · Cited by 181
A functional cellular framework for sex and estrous cycle-dependent gene expression and behavior
Knoedler, J. R., Inoue, S., Bayless, D. W., Yang, T., Tantry, A., Davis, C.-H. O., Leung, N. Y., Parthasarathy, S., Wang, G., Alvarado, M., et al. (2022) · Cell · doi:10.1016/j.cell.2021.12.031 · Cited by 168
Continuous and Discrete Neuron Types of the Adult Murine Striatum
Stanley, G., Gokce, O., Malenka, R. C., Südhof, T. C., & Quake, S. R. (2020) · Neuron · doi:10.1016/j.neuron.2019.11.004 · Cited by 158
Zirlinger, M., Kreiman, G., & Anderson, D. J. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.091094698 · Cited by 157
Genetic strategies to access activated neurons
DeNardo, L. A., & Luo, L. (2017) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2017.05.014 · Cited by 148
Engram-specific transcriptome profiling of contextual memory consolidation
Rao‐Ruiz, P., Couey, J. J., Marcelo, I. M., Bouwkamp, C. G., Slump, D. E., Matos, M. R., van der Loo, R. J., Martins, G. J., van den Hout, M. C. G. N., van IJcken, W. F. J., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-09960-x · Cited by 146
A Corticotropin Releasing Factor Network in the Extended Amygdala for Anxiety
Pomrenze, M. B., Tovar-Díaz, J., Blasio, A., Maiya, R., Giovanetti, S. M., Lei, K., Morikawa, H., Hopf, F. W., & Messing, R. O. (2018) · Journal of Neuroscience · doi:10.1523/jneurosci.2143-18.2018 · Cited by 134
A Spatiomolecular Map of the Striatum
Märtin, A., Calvigioni, D., Tzortzi, O., Fuzik, J., Wärnberg, E., & Meletis, K. (2019) · Cell Reports · doi:10.1016/j.celrep.2019.11.096 · Cited by 132
Pomrenze, M. B., Millan, E. Z., Hopf, F. W., Keiflin, R., Maiya, R., Blasio, A., Dadgar, J., Kharazia, V., de Guglielmo, G., Crawford, E. F., et al. (2015) · Frontiers in Neuroscience · doi:10.3389/fnins.2015.00487 · Cited by 130
Genetically identified amygdala–striatal circuits for valence-specific behaviors
Zhang, X., Guan, W., Yang, T., Furlan, A., Xiao, X., Yu, K., An, X., Galbavy, W., Ramakrishnan, C., Deisseroth, K., et al. (2021) · Nature Neuroscience · doi:10.1038/s41593-021-00927-0 · Cited by 126
Arc expression identifies the lateral amygdala fear memory trace
Gouty‐Colomer, L., Hosseini, B., Marcelo, I. M., Schreiber, J., Slump, D. E., Yamaguchi, S., Houweling, A. R., Jaarsma, D., Elgersma, Y., & Kushner, S. A. (2015) · Molecular Psychiatry · doi:10.1038/mp.2015.18 · Cited by 121
Intercalated amygdala clusters orchestrate a switch in fear state
Hagihara, K. M., Bukalo, O., Zeller, M., Aksoy‐Aksel, A., Karalis, N., Limoges, A., Rigg, T., Campbell, T. L., Mendez, A., Weinholtz, C. A., et al. (2021) · Nature · doi:10.1038/s41586-021-03593-1 · Cited by 119
Lin, W., Jiang, C. S., Sadahiro, M., Bozdagi, O., Vulchanova, L., Alberini, C. M., & Salton, S. R. (2015) · Journal of Neuroscience · doi:10.1523/jneurosci.0584-15.2015 · Cited by 116
Osseward, P. J., Amin, N. D., Moore, J. D., Temple, B. A., Barriga, B. K., Bachmann, L. C., Beltran, F., Gullo, M., Clark, R. C., Driscoll, S. P., et al. (2021) · Science · doi:10.1126/science.abe0690 · Cited by 115
Persistent transcriptional programmes are associated with remote memory
Chen, M. B., Jiang, X., Quake, S. R., & Südhof, T. C. (2020) · Nature · doi:10.1038/s41586-020-2905-5 · Cited by 111
Ucn3 and CRF-R2 in the medial amygdala regulate complex social dynamics
Shemesh, Y., Forkosh, O., Mahn, M., Anpilov, S., Sztainberg, Y., Manashirov, S., Shlapobersky, T., Elliott, E., Tabouy, L., Ezra, G., et al. (2016) · Nature Neuroscience · doi:10.1038/nn.4346 · Cited by 99
Extensive and spatially variable within-cell-type heterogeneity across the basolateral amygdala
O’Leary, T. P., Sullivan, K. E., Wang, L., Clements, J., Lemire, A. L., & Cembrowski, M. S. (2020) · eLife · doi:10.7554/elife.59003 · Cited by 81
Bakowska, J. C., & Morrell, J. I. (2003) · Molecular Brain Research · doi:10.1016/s0169-328x(03)00213-4 · Cited by 80
Multimodal mapping of cell types and projections in the central nucleus of the amygdala
Wang, Y., Krabbe, S., Eddison, M., Henry, F. E., Fleishman, G. M., Lemire, A. L., Wang, L., Korff, W. L., Tillberg, P. W., Lüthi, A., et al. (2023) · eLife · doi:10.7554/elife.84262 · Cited by 79
Rehfeld, F., Maticzka, D., Grosser, S., Knauff, P., Eravci, M., Vida, I., Backofen, R., & Wulczyn, F. G. (2018) · Nature Communications · doi:10.1038/s41467-018-03681-3 · Cited by 74
Neuronal diversity of the amygdala and the bed nucleus of the stria terminalis
Beyeler, A., & Dabrowska, J. (2020) · Handbook of behavioral neuroscience · doi:10.1016/b978-0-12-815134-1.00003-9 · Cited by 74
Paretkar, T., & Dimitrov, E. L. (2018) · Neuroscience · doi:10.1016/j.neuroscience.2018.08.019 · Cited by 73
Transcriptomic mapping uncovers Purkinje neuron plasticity driving learning
Chen, X., Du, Y., Broussard, G. J., Kislin, M., Yuede, C. M., Zhang, S., Dietmann, S., Gabel, H. W., Zhao, G., Wang, S. S. ‐., et al. (2022) · Nature · doi:10.1038/s41586-022-04711-3 · Cited by 70
TrkB Modulates Fear Learning and Amygdalar Synaptic Plasticity by Specific Docking Sites
Musumeci, G., Sciarretta, C., Moreno, A. R., Banchaabouchi, M. A., Negrete‐Díaz, J. V., Costanzi, M., Berno, V., Egorov, A. V., Halbach, O. V. B. U., Cestari, V., et al. (2009) · Journal of Neuroscience · doi:10.1523/jneurosci.1707-09.2009 · Cited by 65
An amygdala circuit that suppresses social engagement
Kwon, J.-T., Ryu, C., Lee, H., Sheffield, A., Fan, J., Cho, D. H., Bigler, S., Sullivan, H. A., Choe, H. K., Wickersham, I. R., et al. (2021) · Nature · doi:10.1038/s41586-021-03413-6 · Cited by 61
Siegmund, A., Langnaese, K., & Wotjak, C. T. (2004) · Behavioural Brain Research · doi:10.1016/j.bbr.2004.07.007 · Cited by 57
Miller, M. A., Kolb, P. E., & Raskind, M. A. (1993) · Journal of Comparative Neurology · doi:10.1002/cne.903290308 · Cited by 56
Gutiérrez-Mariscal, M., de Gortari, P., López‐Rubalcava, C., Martínez, A., & Joseph‐Bravo, P. (2008) · Psychoneuroendocrinology · doi:10.1016/j.psyneuen.2007.11.002 · Cited by 55
O'Connor, V. M., Génin, A., Davis, S., Karishma, K. K., Doyère, V., Zeeuw, C. I. D., Sanger, G. J., Hunt, S. P., Richter‐Levin, G., Mallet, J. J., et al. (2004) · Journal of Biological Chemistry · doi:10.1074/jbc.m312500200 · Cited by 46
Chemosensory Function of the Amygdala
Gutiérrez‐Castellanos, N., Martı́nez-Marcos, A., Martínez‐Garciá, F., & Lanuza, E. (2010) · Vitamins and hormones · doi:10.1016/s0083-6729(10)83007-9 · Cited by 40
The Roles of Basolateral Amygdala Parvalbumin Neurons in Fear Learning
Yau, J. O.-Y., Chaichim, C., Power, J., & McNally, G. P. (2021) · Journal of Neuroscience · doi:10.1523/jneurosci.2461-20.2021 · Cited by 40
Transcriptomics reveals amygdala neuron regulation by fasting and ghrelin thereby promoting feeding
Peters, C., He, S., Fermani, F., Lim, H., Ding, W., Mayer, C., & Klein, R. (2023) · Science Advances · doi:10.1126/sciadv.adf6521 · Cited by 29
Structure and function of the medial amygdala
(2020) · Handbook of Behavioral Neuroscience · doi:10.1016/b978-0-12-815134-1.00002-7 · Cited by 29
Garcı́a-Calero, E., López-González, L., Martı́nez-de-la-Torre, M., Fan, C., & Puelles, L. (2021) · Brain Structure and Function · doi:10.1007/s00429-020-02197-1 · Cited by 28
Kim, H., Kim, D., Kim, J., Lee, H., Park, D., Kang, H., Matsuda, K., Sterky, F. H., Yuzaki, M., Kim, J. Y., et al. (2020) · Journal of Biological Chemistry · doi:10.1074/jbc.ra120.013077 · Cited by 21
Chaperon, F., Fendt, M., Kelly, P. H., Lingenhoehl, K., Mosbacher, J., Olpe, H.-R., Schmid, P., Sturchler, C., McAllister, K. H., van der Putten, P. H., et al. (2012) · PLoS ONE · doi:10.1371/journal.pone.0034963 · Cited by 19
Elucidating memory in the brain via single‐cell transcriptomics
Sullivan, K. E., Kendrick, R. M., & Cembrowski, M. S. (2020) · Journal of Neurochemistry · doi:10.1111/jnc.15250 · Cited by 11
Tanisumi, Y., Shiotani, K., Hirokawa, J., Sakurai, Y., & Manabe, H. (2021) · iScience · doi:10.1016/j.isci.2021.102381 · Cited by 9
Research works printed but not linked: 1
- Ester, M., Kriegel, H.-P., Sander, J. & Xu, X. A density-based algorithm for discovering clusters in large spatial databases with noise. Proceedings of the Second International Conference on Knowledge Discovery and Data Mining (KDD'96) pp. 226–231 (AAAI Press, 1996).
Cited by
Sorted by citations
Chromatin plasticity predetermines neuronal eligibility for memory trace formation
Santoni, G., Astori, S., Leleu, M., Glauser, L., Zamora, S. A., Schioppa, M., Tarulli, I., Sandi, C., & Gräff, J. (2024) · Science · doi:10.1126/science.adg9982 · Cited by 81
Chiaruttini, N., Castoldi, C., Requie, L. M., Camarena-Delgado, C., Bianco, B. D., Gräff, J., Seitz, A., & Silva, B. A. (2025) · Cell Reports · doi:10.1016/j.celrep.2025.115876 · Cited by 77
Stress disrupts engram ensembles in lateral amygdala to generalize threat memory in mice
Lesuis, S. L., Park, S., Hoorn, A., Rashid, A. J., Mocle, A. J., Salter, E. W., Vislavski, S., Gray, M. T., Torelli, A. M., Cristofaro, A. D., et al. (2024) · Cell · doi:10.1016/j.cell.2024.10.034 · Cited by 82
A spatially-resolved transcriptional atlas of the murine dorsal pons at single-cell resolution
Nardone, S., Luca, R. D., Zito, A., Klymko, N., Nicoloutsopoulos, D., Amsalem, O., Brannigan, C., Resch, J. M., Jacobs, C. L., Pant, D. B., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-45907-7 · Cited by 66
Developmental origins and evolution of pallial cell types and structures in birds
Zaremba, B., Fallahshahroudi, A., Schneider, C., Schmidt, J., Sarropoulos, I., Leushkin, E. V., Berki, B., Poucke, E. V., Jensen, P., Senovilla-Ganzo, R., et al. (2025) · Science · doi:10.1126/science.adp5182 · Cited by 55
Metadata
- Authors
- Hochgerner, H., Singh, S., Tibi, M., Lin, Z., Skarbianskis, N., Admati, I., Ophir, O., Reinhardt, N., Netser, S., Wagner, S., & Zeisel, A.
- Affiliations
- Technion – Israel Institute of Technology (IL)
- University of Haifa (IL)
- Corresponding author
- Zeisel, Amit
- Venue
- Nature Neuroscience
- Published
- 2023-10-26
- Volume
- 26
- Issue
- 12
- Pages
- 2237-2249
- ISSN
- 1097-6256 (ISSN-L)
- 1546-1726
- PMC
- PMC10689239
- OpenAlex
- W4387965083
- Cited by
- 110
- References
- 78
- Citations by year
- 2026: 34 · 2025: 48 · 2024: 27 · 2023: 1
- FWCI
- 16.47
- Type
- journal article
- Language
- en
- Update notices
- correction (2024-01-19)
- Open access
- hybrid
- doi.org
- Locations
- Nature Neuroscience (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- Israel Science Foundation (2028912)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Keywords
- amygdala, neuronal cell types, fear conditioning, fear memory consolidation, memory retrieval, engram cells, single-cell transcriptomics, molecular atlas, synaptic plasticity, neurite outgrowth
- MeSH terms
- Amygdala, Animals, Fear, Memory, Neuronal Plasticity, Neurons, 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