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Distinct behavioural and network correlates of two interneuron types in prefrontal cortex
Open accessAbstract
Neurons in the prefrontal cortex exhibit diverse behavioural correlates, an observation that has been attributed to cell-type diversity. To link identified neuron types with network and behavioural functions, we recorded from the two largest genetically defined inhibitory interneuron classes, the perisomatically targeting parvalbumin (PV) and the dendritically targeting somatostatin (SOM) neurons in anterior cingulate cortex of mice performing a reward foraging task. Here we show that PV and a subtype of SOM neurons form functionally homogeneous populations showing a double dissociation between both their inhibitory effects and behavioural correlates. Out of several events pertaining to behaviour, a subtype of SOM neurons selectively responded at reward approach, whereas PV neurons responded at reward leaving and encoded preceding stay duration. These behavioural correlates of PV and SOM neurons defined a behavioural epoch and a decision variable important for foraging (whether to stay or to leave), a crucial function attributed to the anterior cingulate cortex. Furthermore, PV neurons could fire in millisecond synchrony, exerting fast and powerful inhibition on principal cell firing, whereas the inhibitory effect of SOM neurons on firing output was weak and more variable, consistent with the idea that they respectively control the outputs of, and inputs to, principal neurons. These results suggest a connection between the circuit-level function of different interneuron types in regulating the flow of information and the behavioural functions served by the cortical circuits. Moreover, these observations bolster the hope that functional response diversity during behaviour can in part be explained by cell-type diversity.
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In the citing paper
“Extracellular recordings in the anterior cingulate cortex of mice performing a reward foraging task showed that a subgroup of optogenetically-identified Sst INs with narrow spikes fired preferentially at reward approach, whereas PV INs showed an increase firing when the mouse was leaving the reward location that was correlated with stay duration in the reward zone (Kvitsiani et al., 2013).”
From GABAergic Interneurons in the Neocortex: From Cellular Properties to Circuits (2016) · cites this paper as Kvitsiani et al., 2013
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“PV+ interneurons, which could fire in millisecond synchrony, exert fast and powerful inhibition on principal neuron firing, whereas SST+ interneurons exert weak and more variable inhibitory effects on firing output in behaving mice 29.”
From Mechanisms of synaptic transmission dysregulation in the prefrontal cortex: pathophysiological implications (2022) · cites this paper as [29]
In the citing paper
“In mice performing a reward foraging task, SST+ interneurons in ACC are found to selectively respond at reward approach, whereas PV+ interneurons respond at reward leaving 29.”
From Mechanisms of synaptic transmission dysregulation in the prefrontal cortex: pathophysiological implications (2022) · cites this paper as [29]
In the citing paper
“These elements can be task-dependently recruited into larger brain networks for systems-level information processing and computation, representing their distal behavioural and cognitive functions59,60.”
From The diversity of GABAergic neurons and neural communication elements (2019) · cites this paper as [59]
In the citing paper
“This finding supports the idea that local regions such as dACC can contain multiple, distinct neural population codes25 that encode distinct mental processes.”
From Separate neural representations for physical pain and social rejection (2014) · cites this paper as [25]
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Cites
Estimating the Number of Clusters in a Data Set Via the Gap Statistic
Tibshirani, R., Walther, G., & Hastie, T. (2001) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/1467-9868.00293 · Cited by 6,205
ASH, R. B. (1966) · Cited by 3,990
Interneurons of the neocortical inhibitory system
Markram, H., Toledo-Rodriguez, M., Wang, Y., Gupta, A., Silberberg, G., & Wu, C. (2004) · Nature Reviews Neuroscience · doi:10.1038/nrn1519 · Cited by 2,954
Parvalbumin neurons and gamma rhythms enhance cortical circuit performance
Sohal, V. S., Zhang, F., Yizhar, O., & Deisseroth, K. (2009) · Nature · doi:10.1038/nature07991 · Cited by 2,606
Driving fast-spiking cells induces gamma rhythm and controls sensory responses
Cardin, J. A., Carlén, M., Meletis, K., Knoblich, U., Zhang, F., Deisseroth, K., Tsai, L.-H., & Moore, C. I. (2009) · Nature · doi:10.1038/nature08002 · Cited by 2,603
A resource of Cre driver lines for genetic targeting of GABAergic neurons in cerebral cortex
Taniguchi, H., He, M., Wu, P., Kim, S., Paik, R., Sugino, K., Kvitsani, D., Fu, Y., Lu, J., Lin, Y., et al. (2011) · Neuron · doi:10.1016/j.neuron.2011.07.026 · Cited by 1,828
Self-citationNeural correlations, population coding and computation
Averbeck, B. B., Latham, P. E., & Pouget, A. (2006) · Nature reviews. Neuroscience · doi:10.1038/nrn1888 · Cited by 1,743
How Inhibition Shapes Cortical Activity
Isaacson, J. S., & Scanziani, M. (2011) · Neuron · doi:10.1016/j.neuron.2011.09.027 · Cited by 1,678
Petilla terminology: nomenclature of features of GABAergic interneurons of the cerebral cortex
The Petilla Interneuron Nomenclature Group (PING) (2008) · Nature Reviews Neuroscience · doi:10.1038/nrn2402 · Cited by 1,491
Brain-state- and cell-type-specific firing of hippocampal interneurons in vivo
Klausberger, T., Magill, P. J., Márton, L. F., Roberts, J. D. B., Cobden, P. M., Buzsáki, G., & Somogyi, P. (2003) · Nature · doi:10.1038/nature01374 · Cited by 1,345
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Urrutia-Piñones, J., Morales-Moraga, C., Sanguinetti, N. K., Escobar, A. P., & Chiu, C. Q. (2022) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2022.841869 · Cited by 36
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Mohan, H., An, X., Xu, X. H., Kondo, H., Zhao, S., Matho, K. S., Wang, B., Musall, S., Mitra, P. P., & Huang, Z. J. (2023) · Nature Neuroscience · doi:10.1038/s41593-022-01244-w · Cited by 38
Gaykema, R. P. A., Nguyen, X.-M. T., Boehret, J. M., Lambeth, P. S., Joy-Gaba, J., Warthen, D. M., & Scott, M. M. (2014) · Frontiers in Neuroanatomy · doi:10.3389/fnana.2014.00060 · Cited by 36
Chen, Y.-W., Wable, G. S., Chowdhury, T. G., & Aoki, C. J. (2015) · Cerebral Cortex · doi:10.1093/cercor/bhv087 · Cited by 32
Large-scale neurophysiology and single-cell profiling in human neuroscience
Lee, A. T., Chang, E. F., Paredes, M. F., & Nowakowski, T. J. (2024) · Nature · doi:10.1038/s41586-024-07405-0 · Cited by 35
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Onorato, I., Τζάνου, Α., Schneider, M., Uran, C., Broggini, A. C., & Vinck, M. A. (2025) · Cell Reports · doi:10.1016/j.celrep.2025.115385 · Cited by 37
Nawreen, N., Cotella, E. M., Morano, R. L., Mahbod, P., Dalal, K. S., Fitzgerald, M. E., Martelle, S. E., Packard, B. A., Franco, A. C. G., Moloney, R. D., et al. (2020) · eNeuro · doi:10.1523/eneuro.0423-19.2020 · Cited by 35
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Miczán, V., Kelemen, K., Glavinics, J. R., László, Z. I., Barti, B., Kenesei, K., Kisfali, M., & Katona, I. (2020) · Cerebral Cortex · doi:10.1093/cercor/bhaa326 · Cited by 30
Jones, E. A. A., Rao, A. T., Zilberter, M. Y., Djukic, B., Bant, J. S., Gillespie, A. K., Koutsodendris, N., Nelson, M. R., Yoon, S. Y., Huang, K., et al. (2021) · Cell Reports · doi:10.1016/j.celrep.2021.110159 · Cited by 36
A mismatch between striatal cholinergic pauses and dopaminergic reward prediction errors
Duhne, M., Mohebi, A., Kim, K., Pelattini, L., & Berke, J. D. (2024) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2410828121 · Cited by 37
Filippo, R. D., Rost, B. R., Stumpf, A., Cooper, C., Tukker, J. J., Harms, C., Beed, P. S., & Schmitz, D. (2021) · eLife · doi:10.7554/elife.66960 · Cited by 34
Bush, N. E., & Ramirez, J. (2024) · Nature Neuroscience · doi:10.1038/s41593-023-01520-3 · Cited by 32
Activity of ventral hippocampal parvalbumin interneurons during anxiety
Volitaki, E., Forro, T., Li, K., Nevian, T., & Ciocchi, S. (2024) · Cell Reports · doi:10.1016/j.celrep.2024.114295 · Cited by 32
Sallet, J., Camille, N., & Procyk, E. (2013) · Frontiers in Neuroscience · doi:10.3389/fnins.2013.00209 · Cited by 36
The convergence of aversion and reward signals in individual neurons of the mice lateral habenula
Li, J., Fan, R., Liu, X., Shen, X., Liu, X., & Zhao, H. (2021) · Experimental Neurology · doi:10.1016/j.expneurol.2021.113637 · Cited by 33
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He, L. S., Shi, H., Zhang, G., Peng, Y., Ghosh, A., Zhang, M., Hu, X., Liu, C., Shao, Y., Wang, S., et al. (2023) · Journal of Neuroscience · doi:10.1523/jneurosci.2035-22.2023 · Cited by 32
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He, H., Shen, W., Hiramoto, M., & Cline, H. T. (2016) · Neuron · doi:10.1016/j.neuron.2016.04.044 · Cited by 32
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Maffei, A., Charrier, C., Caiati, M. D., Barberis, A., Mahadevan, V., Woodin, M. A., & Tyagarajan, S. K. (2017) · Journal of Neuroscience · doi:10.1523/jneurosci.1824-17.2017 · Cited by 35
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Nocon, J. C., Gritton, H. J., James, N. M., Mount, R. A., Qu, Z., Han, X., & Sen, K. (2023) · Communications Biology · doi:10.1038/s42003-023-05126-0 · Cited by 30
Casas-Torremocha, D., Clascá, F., & Núñez, Á. (2017) · Frontiers in Neural Circuits · doi:10.3389/fncir.2017.00069 · Cited by 33
Robinson, J. E., & Gradinaru, V. (2017) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2017.08.003 · Cited by 34
Brain Computation Is Organized via Power-of-Two-Based Permutation Logic
Xie, K., Fox, G. E., Liu, J., Lyu, C., Lee, J. C., Kuang, H., Jacobs, S., Li, M., Liu, T., Song, S., et al. (2016) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2016.00095 · Cited by 30
Sullivan, J. M., Bagnell, A. M., Alevy, J., Avila, E. M., Mihaljević, L., Saavedra-Rivera, P. C., Kong, L., Huh, J. S., McCray, B. A., Aisenberg, W. H., et al. (2024) · Science Translational Medicine · doi:10.1126/scitranslmed.adk1358 · Cited by 29
Boroujeni, K. B., Tiesinga, P. H. E., & Womelsdorf, T. (2021) · eLife · doi:10.7554/elife.69111 · Cited by 35
Dynamic control of visually guided locomotion through corticosubthalamic projections
Adam, E. M., Johns, T., & Sur, M. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.111139 · Cited by 28
Cognition and the single neuron: How cell types construct the dynamic computations of frontal cortex
Christensen, A. J., Ott, T., & Kepecs, Á. (2022) · Current Opinion in Neurobiology · doi:10.1016/j.conb.2022.102630 · Cited by 24
An introduction and guidance for neurodynamics
Ma, J., & Xu, J. (2015) · 中国科学通报:英文版 · doi:10.1007/s11434-015-0945-2 · Cited by 28
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Han, Y., Xia, G., He, Y., He, Y., Farías, M., Xu, Y., & Wu, Q. (2021) · Science Advances · doi:10.1126/sciadv.abf8719 · Cited by 30
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Urien, L., Xiao, Z., Dale, J., Bauer, E. P., Chen, Z. S., & Wang, J. (2018) · Scientific Reports · doi:10.1038/s41598-018-26518-x · Cited by 28
Ye, Z., Shelton, A. M., Shaker, J. R., Boussard, J., Colonell, J. I., Birman, D., Manavi, S., Chen, S., Windolf, C., Hurwitz, C., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.08.23.554527 · Cited by 28
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Ye, Z., Shelton, A. M., Shaker, J. R., Boussard, J., Colonell, J. I., Birman, D., Manavi, S., Chen, S., Windolf, C., Hurwitz, C., et al. (2025) · Neuron · doi:10.1016/j.neuron.2025.08.030 · Cited by 69
New approaches to manipulating the epigenome
Day, J. J. (2014) · Dialogues in Clinical Neuroscience · doi:10.31887/dcns.2014.16.3/jday · Cited by 27
Pan, G., Yang, J.-M., Hu, X.-Y., & Li, X.-M. (2016) · Scientific Reports · doi:10.1038/srep28137 · Cited by 30
Stress and prefrontal cortical plasticity in the developing brain
Kolb, B. E., Harker, A., Mychasiuk, R., de Melo, S. R., & Gibb, R. L. (2017) · Cognitive Development · doi:10.1016/j.cogdev.2017.01.001 · Cited by 30
Solari, N., Sviatkó, K., Laszlovszky, T., Hegedüs, P., & Hangya, B. (2018) · Frontiers in Systems Neuroscience · doi:10.3389/fnsys.2018.00018 · Cited by 23
Self-citationIn vivo localization of chronically implanted electrodes and optic fibers in mice
Király, B., Balázsfi, D., Horváth, I., Solari, N., Sviatkó, K., Lengyel, K., Birtalan, E., Babos, M., Bagaméry, G., Máthé, D., et al. (2020) · Nature Communications · doi:10.1038/s41467-020-18472-y · Cited by 27
Self-citationCholinergic activity reflects reward expectations and predicts behavioral responses
Hegedüs, P., Sviatkó, K., Király, B., Martínez‐Bellver, S., & Hangya, B. (2022) · iScience · doi:10.1016/j.isci.2022.105814 · Cited by 28
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Jun, H., Lee, J. Y., Bleza, N. R., Ichii, A., Donohue, J. D., & Igarashi, K. M. (2024) · Nature · doi:10.1038/s41586-024-07868-1 · Cited by 26
Cooperative actions of interneuron families support the hippocampal spatial code
Valero, M., Abad-Perez, P., Gallardo, A., Picco, M., García-Hernandez, R., Brotons‐Mas, J. R., Martínez-Félix, A., Machold, R. P., Rudy, B., & Buzsáki, G. (2025) · Science · doi:10.1126/science.adv5638 · Cited by 37
High-resolution optogenetics in space and time
Fernández‐Ruiz, A., Oliva, A., & Chang, H. (2022) · Trends in Neurosciences · doi:10.1016/j.tins.2022.09.002 · Cited by 28
Kanigowski, D., Bogaj, K., Barth, A. L., & Urban‐Ciećko, J. (2023) · Scientific Reports · doi:10.1038/s41598-023-35890-2 · Cited by 26
Postnatal TrkB ablation in corticolimbic interneurons induces social dominance in male mice
Tan, S., Xiao, Y., Yin, H. H., Chen, A. I., Soong, T. W., & Je, H. S. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1812083115 · Cited by 27
A non-canonical retina-ipRGCs-SCN-PVT visual pathway for mediating contagious itch behavior
Gao, F., Ma, J., Yu, Y., Gao, X.-F., Bai, Y., Sun, Y., Liu, J., Liu, X., Barry, D. M., Wilhelm, S. J., et al. (2022) · Cell Reports · doi:10.1016/j.celrep.2022.111444 · Cited by 25
Rankin, G., Chirila, A. M., Emanuel, A. J., Zhang, Z., Woolf, C. J., Drugowitsch, J., & Ginty, D. D. (2024) · Cell Reports · doi:10.1016/j.celrep.2024.113718 · Cited by 24
Li, M., Cabrera-García, D., Salling, M. C., Au, E., Yang, G., & Harrison, N. L. (2021) · Neuropharmacology · doi:10.1016/j.neuropharm.2021.108501 · Cited by 25
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Nelson, A. C., Kapoor, V., Vaughn, E., Gnanasegaram, J. A., Rubinstein, N. D., Murthy, V. N., & Dulac, C. G. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/838664 · Cited by 24
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Bugeon, S., Duffield, J. A. M., Dipoppa, M., Ritoux, A., Prankerd, I., Nicoloutsopoulos, D., Orme, D., Shinn, M., Peng, H., Forrest, H., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.10.24.465600 · Cited by 24
Qi, C., Sima, W., Mao, H., Hu, E., Ge, J., Deng, M., Chen, A., Ye, W., Xue, Q., Wang, W., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-59473-z · Cited by 30
Wyss, C., Tse, D. H. Y., Kometer, M., Dammers, J., Achermann, R., Shah, N. J., Kawohl, W., & Neuner, I. (2017) · Human Brain Mapping · doi:10.1002/hbm.23642 · Cited by 26
Jeong, H., Kim, D., Song, M. J., Paik, S., & Jung, M. W. (2019) · Progress in Neurobiology · doi:10.1016/j.pneurobio.2020.101773 · Cited by 24
Dissociable encoding of motivated behavior by parallel thalamo-striatal projections
Beas, B. S., Khan, I., Gao, C., Loewinger, G. C., Macdonald, E., Bashford, A., Rodriguez-Gonzalez, S., Pereira, F., & Penzo, M. A. (2024) · Current Biology · doi:10.1016/j.cub.2024.02.037 · Cited by 24
Serotonergic Suppression of Mouse Prefrontal Circuits Implicated in Task Attention
Tian, M. K., Schmidt, E. F., & Lambe, E. K. (2016) · eNeuro · doi:10.1523/eneuro.0269-16.2016 · Cited by 26
Havenith, M. N., Zijderveld, P. M., van Heukelum, S., Abghari, S., Glennon, J. C., & Tiesinga, P. H. E. (2018) · Scientific Reports · doi:10.1038/s41598-018-34966-8 · Cited by 22
Pinto, S. R., & Uchida, N. (2025) · Nature Communications · doi:10.1038/s41467-025-62280-1 · Cited by 24
Electrophysiological monitoring of inhibition in mammalian species, from rodents to humans
Peyrache, A., & Alain Destexhe, A. (2019) · Neurobiology of Disease · doi:10.1016/j.nbd.2019.104500 · Cited by 24
Dynamic corticothalamic modulation of the somatosensory thalamocortical circuit during wakefulness
Dimwamwa, E., Pala, A., Chundru, V., Wright, N. C., & Stanley, G. B. (2024) · Nature Communications · doi:10.1038/s41467-024-47863-8 · Cited by 21
Sekulić, V., Lawrence, J. J., & Skinner, F. K. (2014) · PLoS ONE · doi:10.1371/journal.pone.0106567 · Cited by 20
Clarke, R. E., Verdejo‐García, A., & Andrews, Z. B. (2018) · Journal of Neurochemistry · doi:10.1111/jnc.14455 · Cited by 21
Neocortical somatostatin neuron diversity in cognition and learning
Park, E., Mosso, M. B., & Barth, A. L. (2025) · Trends in Neurosciences · doi:10.1016/j.tins.2024.12.004 · Cited by 24
Semantic priming and neurobiology in schizophrenia: A theoretical review
Almeida, V. N., & Radanovic, M. (2021) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2021.108058 · Cited by 23
Prelimbic area to lateral hypothalamus circuit drives social aggression
Bai, F., Huang, L., Deng, J., Long, Z., Hao, X., Chen, P., Wu, G., Wen, H., Deng, Q., Bao, X., et al. (2023) · iScience · doi:10.1016/j.isci.2023.107718 · Cited by 19
Self-citationKang, S. J., Kim, S., Lee, J., Kwak, C., Lee, K., Zhuo, M., & Kaang, B. (2017) · Korean Journal of Physiology and Pharmacology · doi:10.4196/kjpp.2017.21.5.487 · Cited by 20
Targeting prefrontal cortex GABAergic microcircuits for the treatment of alcohol use disorder
Fish, K. N., & Joffe, M. E. (2022) · Frontiers in Synaptic Neuroscience · doi:10.3389/fnsyn.2022.936911 · Cited by 20
Graham, D. L., Durai, H. H., Garden, J. D., Cohen, E. L., Echevarría, F. D., & Stanwood, G. D. (2014) · ACS Chemical Neuroscience · doi:10.1021/cn500235m · Cited by 22
Esmaeili, V., Oryshchuk, A., Asri, R., Tamura, K., Foustoukos, G., Liu, Y., Guiet, R., Crochet, S., & Petersen, C. C. H. (2022) · PLoS Biology · doi:10.1371/journal.pbio.3001667 · Cited by 18
Associations between in vitro, in vivo and in silico cell classes in mouse primary visual cortex
Wei, Y., Nandi, A., Jia, X., Siegle, J. H., Denman, D. J., Lee, S. Y., Buchin, A., Geit, W. A. H. V., Mosher, C. P., Olsen, S. R., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-37844-8 · Cited by 18
An adaptive behavioral control motif mediated by cortical axo-axonic inhibition
Jung, K., Chang, M., Steinecke, A., Burke, B., Choi, Y., Oisi, Y., Fitzpatrick, D., Taniguchi, H., & Kwon, H. (2023) · Nature Neuroscience · doi:10.1038/s41593-023-01380-x · Cited by 18
Self-citationCho, K. K. A., & Sohal, V. S. (2014) · Human Molecular Genetics · doi:10.1093/hmg/ddu225 · Cited by 19
Kecskés, M., Henn-Mike, N., Agócs-Laboda, Á., Szőcs, S., Petykó, Z., & Varga, C. (2020) · Communications Biology · doi:10.1038/s42003-020-01496-x · Cited by 18
Lateral inhibition in V1 controls neural and perceptual contrast sensitivity
Rosario, J. D., Coletta, S., Kim, S. H., Mobille, Z., Peelman, K., Williams, B., Otsuki, A. J., Valerio, A. D. C., Worden, K., Blanpain, L. T., et al. (2025) · Nature Neuroscience · doi:10.1038/s41593-025-01888-4 · Cited by 23
Streaming of Repeated Noise in Primary and Secondary Fields of Auditory Cortex
Saderi, D., Buran, B. N., & David, S. V. (2020) · Journal of Neuroscience · doi:10.1523/jneurosci.2105-19.2020 · Cited by 19
Tseng, H.-A., & Han, X. (2021) · Frontiers in Physiology · doi:10.3389/fphys.2021.618307 · Cited by 17
Computational Classification Approach to Profile Neuron Subtypes from Brain Activity Mapping Data
Li, M., Zhao, F., Lee, J., Wang, D., Kuang, H., & Tsien, J. Z. (2015) · Scientific Reports · doi:10.1038/srep12474 · Cited by 19
Lewin, A. E., Vicini, S., Richardson, J. R., Dretchen, K. L., Gillis, R. A., & Sahibzada, N. (2016) · The Journal of Physiology · doi:10.1113/jp272069 · Cited by 18
Wang, X., Song, X., Wu, L., Nadler, J. V., & Zhan, R. (2016) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2016.00094 · Cited by 18
Adams, N., Sherfey, J. S., Kopell, N., Whittington, M. A., & LeBeau, F. E. N. (2017) · eNeuro · doi:10.1523/eneuro.0313-16.2017 · Cited by 19
Vibrissa Sensory Neurons: Linking Distinct Morphology to Specific Physiology and Function
Takatoh, J., Prevosto, V., & Wang, F. (2017) · Neuroscience · doi:10.1016/j.neuroscience.2017.06.033 · Cited by 19
Understanding the circuit basis of cognitive functions using mouse models
Nakajima, M., & Schmitt, L. I. (2019) · Neuroscience Research · doi:10.1016/j.neures.2019.12.009 · Cited by 19
Reward Timing and Its Expression by Inhibitory Interneurons in the Mouse Primary Visual Cortex
Monk, K. J., Allard, S., & Shuler, M. G. H. (2020) · Cerebral Cortex · doi:10.1093/cercor/bhaa068 · Cited by 18
Zhang, B., Chen, K., Dai, Y., Luo, X., Xiong, Z., Zhang, W., Huang, X., So, K., & Zhang, L. (2024) · Communications Biology · doi:10.1038/s42003-024-06896-x · Cited by 17
Kim, H., Brünner, H., & Carlén, M. (2020) · Scientific Reports · doi:10.1038/s41598-020-68783-9 · Cited by 15
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Self-citation
Metadata
- Authors
- Kvitsiani, D., Ranade, S., Hangya, B., Taniguchi, H., Huang, J. Z., & Kepecs, A.
- Affiliations
- Cold Spring Harbor Laboratory (US)
- Venue
- Nature
- Published
- 2013-05-26
- Volume
- 498
- Issue
- 7454
- Pages
- 363-366
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC4349584
- OpenAlex
- W2012509205
- Cited by
- 516
- References
- 49
- Citations by year
- 2026: 20 · 2025: 49 · 2024: 45 · 2023: 39 · 2022: 36 · 2021: 36 · 2020: 43 · 2019: 48 · 2018: 34 · 2017: 39 · 2016: 41 · 2015: 35 · 2014: 37 · 2013: 14
- FWCI
- 23.13
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Cold Spring Harbor Laboratory Institutional Repository (Cold Spring Harbor Laboratory) (acceptedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- National Institute of Neurological Disorders and Stroke (R01NS075531)
- Topics
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
- Keywords
- parvalbumin interneurons, somatostatin interneurons, inhibitory interneurons, anterior cingulate cortex, prefrontal cortex, neuronal synchronization, decision variables, stay duration, cortical circuits
- MeSH terms
- Animals, Feeding Behavior, Interneurons, Male, Neural Pathways, Parvalbumins, Reward, Somatostatin, Prefrontal Cortex, Mice, Single-Cell Analysis, Optogenetics
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