The DOI matches its Crossref record; 125 of the 126 references it cites were found in a registry or an index.
Interneuron cell types are fit to function
Open accessAbstract
Understanding brain circuits begins with an appreciation of their component parts - the cells. Although GABAergic interneurons are a minority population within the brain, they are crucial for the control of inhibition. Determining the diversity of these interneurons has been a central goal of neurobiologists, but this amazing cell type has so far defied a generalized classification system. Interneuron complexity within the telencephalon could be simplified by viewing them as elaborations of a much more finite group of developmentally specified cardinal classes that become further specialized as they mature. Our perspective emphasizes that the ultimate goal is to dispense with classification criteria and directly define interneuron types by function.
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?
The cited source says what the claim attributes to it.
In the citing paper
“IN subtypes differ in their expression of molecules such as calcium-binding proteins and neuropeptides”
From GABAergic Interneurons in the Neocortex: From Cellular Properties to Circuits (2016) · cites this paper as Kepecs and Fishell, 2014
In the citing paper
“Developmental transcriptomic data seems compatible with the hypothesis that that cascades of transcription factors and positive feedback autoregulatory loops predominate early in development, but pass the baton to activity-dependent feedback mechanisms that fine-tune neuronal morphology and synaptic connectivity (see (Fishell and Heintz, 2013; Kepecs and Fishell, 2014) for review).”
From Unifying Views of Autism Spectrum Disorders: A Consideration of Autoregulatory Feedback Loops (2016) · cites this paper as Kepecs and Fishell, 2014
In the citing paper
“This diverse group of neurons is developmentally derived from progenitors residing in embryonic proliferative zones known as the medial, caudal and lateral ganglionic eminences (MGE, CGE, LGE, respectively)1.”
From Developmental diversification of cortical inhibitory interneurons (2018) · cites this paper as [1]
In the citing paper
“For example, decades of developmental studies have established a clear division of transcription programmes between the interneurons derived from the medial and caudal ganglionic eminence (MGE and CGE, respectively)9,31,32,33.”
From The diversity of GABAergic neurons and neural communication elements (2019) · cites this paper as [9]
In the citing paper
“Defining neuronal types on the basis of their ‘function’ seems intuitive and the most relevant to nervous system operation9,51, but neuronal functions manifest at multiple levels that carry different meanings, vary according to behavioural context, and thus seem not to be well suited for use in defining cell types.”
From The diversity of GABAergic neurons and neural communication elements (2019) · cites this paper as [9]
In the citing paper
“The cardinal identity of a cell is probably already instilled at the postmitotic stage during development9,61,62,63,64, and its subsequent phenotypic differentiation and expression are regulated by extrinsic signals such as cell interactions and neural activity.”
From The diversity of GABAergic neurons and neural communication elements (2019) · cites this paper as [9]
In the citing paper
“PVBCs have origin in the MGE with specification driven by the homeodomain transcription factor Nkx2.1 (21% of MGE-derived interneurons, see assumptions above) (147, 575, 1138, 1233).”
From Hippocampal GABAergic Inhibitory Interneurons (2017) · cites this paper as [575]
In the citing paper
“This suggests that interneuron diversity does not emerge in response to activity-dependent mechanisms in the cortex (1, 9), but rather is established early, before these cells reach the cortex, by specific transcriptional programs that then unfold over the course of several weeks.”
From Early emergence of cortical interneuron diversity in the mouse embryo (2018) · cites this paper as [1]
In the citing paper
“(the MGE gives rise to SST and PVALB cortical types; the CGE gives rise to VIP and LAMPS cortical types)”
From Innovations present in the primate interneuron repertoire (2020) · cites this paper as [19]
In the citing paper
“Vip and Tac2 (the mouse homologue of TAC3) are neuropeptide genes associated with a CGE origin in the mouse19”
From Innovations present in the primate interneuron repertoire (2020) · cites this paper as [19]
In the citing paper
“In the mouse, neocortical Lamp5+ interneurons primarily consist of neurogliaform and single-bouquet types, which are the most numerous layer-1 neurons and have distinct morphological, neurochemical and connectivity properties19.”
From Innovations present in the primate interneuron repertoire (2020) · cites this paper as [19]
In the citing paper
“many markers that are widely used to identify specific subtypes of interneurons in mice (such as Calb1, Calb2, Htr3a, Reln, Cck and Nos1)19,33 had different patterns of expression across the corresponding subtypes in primates”
From Innovations present in the primate interneuron repertoire (2020) · cites this paper as [19]
In the citing paper
“Since the diverse sources of inhibition from the various interneuronal types are believed to enable networks to achieve more complex behaviors, including oscillations (Soltesz, 2006; Rotstein et al., 2005; Kepecs and Fishell, 2014)”
From Interneuronal mechanisms of hippocampal theta oscillations in a full-scale model of the rodent CA1 circuit (2016) · cites this paper as Kepecs and Fishell, 2014
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
Neuronal Oscillations in Cortical Networks
Buzsáki, G., & Draguhn, A. (2004) · Science · doi:10.1126/science.1099745 · Cited by 6,576
Millisecond-timescale, genetically targeted optical control of neural activity
Boyden, E. S., Zhang, F., Bamberg, E., Nagel, G., & Deisseroth, K. A. (2005) · Nature Neuroscience · doi:10.1038/nn1525 · Cited by 5,015
Interneurons of the hippocampus
Freund, T. F., & Buzsáki, G. (1998) · Hippocampus · doi:10.1002/(sici)1098-1063(1996)6:4 · Cited by 3,478
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
Neuronal Diversity and Temporal Dynamics: The Unity of Hippocampal Circuit Operations
Klausberger, T., & Somogyi, P. (2008) · Science · doi:10.1126/science.1149381 · Cited by 2,050
Normalization as a canonical neural computation
Carandini, M., & Heeger, D. J. (2012) · Nature Reviews Neuroscience · doi:10.1038/nrn3136 · Cited by 1,906
Chaos in Neuronal Networks with Balanced Excitatory and Inhibitory Activity
van Vreeswijk, C., & Sompolinsky, H. (1996) · Science · doi:10.1126/science.274.5293.1724 · Cited by 1,831
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-citation
Flagged first, then by citations
1 of the 126 references couldn’t be matched to a known paper.
Cited by
Sorted by citations
Items 901–1,000 of 1,004
Su, C., & El-Shamayleh, Y. (2026) · Nature Communications · doi:10.1038/s41467-026-76521-4 · Cited by 1
The regulation of GABAergic nervous system in sleep‑wake states and general anesthesia
Dai, F., Dai, X., Song, W., & Mei, W. (2026) · Brain Research Bulletin · doi:10.1016/j.brainresbull.2026.112041 · Cited by 1
VIP+ interneuron control of the hippocampal cognitive map
Dhanerawala, Z. M., Jiang, B., Molina, G., Bano, E., Pacozzi, L., Wang, H., & Han, E. B. (2026) · Current Biology · doi:10.1016/j.cub.2026.07.050 · Cited by 1
Wilmerding, L. K., Gourianova, F., & Grienberger, C. (2026) · Current Research in Neurobiology · doi:10.1016/j.crneur.2026.100167 · Cited by 1
Internally Organized Cell Assembly Trajectories
Buzsáki, G. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190905385.003.0007 · Cited by 1
Causation and Logic in Neuroscience
Buzsáki, G. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190905385.003.0002 · Cited by 1
Gao, J., Liu, Y., Gong, D., Feng, X., Wan, P., Luo, X.-F., Zhu, W., Hou, J., & Lv, S. (2019) · Neuroreport · doi:10.1097/wnr.0000000000001309 · Cited by 1
Optogenetic and Chemogenetic Tools for Drug Discovery in Schizophrenia
Kätzel, D., & Kullmann, D. M. (2015) · Royal Society of Chemistry eBooks · doi:10.1039/9781782622499-00234 · Cited by 1
Homochronic Transplantation of Interneuron Precursors into Early Postnatal Mouse Brains
Quattrocolo, G., Isaac, M., Zhang, Y., & Petros, T. J. (2018) · Journal of Visualized Experiments · doi:10.3791/57723 · Cited by 1
A leech brain in the dish: a method for detailed analysis of specifically labeled single cells
Cohen, S., Baranes, K., & Shefi, O. (2019) · Neural Imaging and Sensing · doi:10.1117/12.2507250 · Cited by 1
Differential coupling of parvalbumin and somatostatin interneurons with adult-born granule cells
Yang, S. M., Groisman, A. I., & Schinder, A. F. (2019) · Greater South Information System · doi:10.60692/bp6f4-r9e67 · Cited by 1
Modulation of adult-born neuron excitability by coupling to GABAergic networks
Yang, S. M., Groisman, A. I., & Schinder, A. F. (2019) · Greater South Information System · doi:10.60692/4a93a-ddm52 · Cited by 1
Zelenka, O., Novák, O., BRUNOVA, A., & Syka, J. (2021) · Physiological Research · doi:10.33549/physiolres.934559 · Cited by 1
GABAergic Axosomatic Synapses of Rat Brain Cortex
Razenkova, V. A., & Korzhevsky, D. E. (2021) · Cell and Tissue Biology · doi:10.1134/s1990519x21030093 · Cited by 1
Buzsáki, G. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190905385.003.0010 · Cited by 1
[Auditory response patterns of mouse primary auditory cortex to sound stimuli].
Zheng, Q., Song, C., & Liang, F. (2022) · PubMed · doi:10.12122/j.issn.1673-4254.2022.08.14 · Cited by 1
Biocytin Recovery and 3D Reconstructions of Filled Hippocampal CA2 Interneurons
Economides, G., Falk, S., & Mercer, A. (2018) · Journal of Visualized Experiments · doi:10.3791/58592-v · Cited by 1
Electrophysiological Recordings from Identified Cell Types in the Olfactory Cortex of Awake Mice
Bolding, K. A., & Franks, K. M. (2023) · Methods in molecular biology · doi:10.1007/978-1-0716-3425-7_16 · Cited by 1
Koo, J. M., Yoo, S., Kim, J. H., Park, J. E., Baek, S., & Jeon, T. Y. (2024) · ULTRASONOGRAPHY · doi:10.14366/usg.24110 · Cited by 1
Szabó, F., Sigutova, V., Schneider, A. M., Hoerder‐Suabedissen, A., & Molnár, Z. (2024) · Journal of Anatomy · doi:10.1111/joa.14181 · Cited by 1
Disinhibitory signaling enables flexible coding of top-down information in cortical networks
Aquino, T. G., Kim, R., & Rungratsameetaweemana, N. (2026) · PLoS Biology · doi:10.1371/journal.pbio.3003831 · Cited by 1
The Role of Perineuronal Nets in Regulating Barrel Cortex Physiology
Chu, P. (2015) · CUNY Academic Works (City University of New York) · Cited by 1
Petros, T. J. (2018) · Journal of Experimental Neuroscience · doi:10.1177/1179069518758656 · Cited by 1
Nguyen, R. (2018) · TSpace (University of Toronto) · Cited by 1
La-Vu, M. Q., Sethi, E., Maesta‐Pereira, S., Schuette, P. J., Tobias, B. C., Reis, F. M., Wang, W., Leonard, S. J., Lin, L., & Adhikari, A. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.01.19.476981 · Cited by 1
Electrophysiological monitoring of inhibition in mammalian species, from rodents to humansPreprint
Peyrache, A., & Alain Destexhe, A. (2019) · Frenxiv (OSF Preprints) · doi:10.31226/osf.io/a69dt · Cited by 1
Chatzikalymniou, A. P., Sengupta, S., Lefebvre, J., & Skinner, F. K. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.06.01.494440 · Cited by 1
Hippocampus, Model Inhibitory Cells
Skinner, F. K., & Ferguson, K. (2018) · Springer eBooks · doi:10.1007/978-1-4614-7320-6_29-2 · Cited by 1
Regulation of critical brain dynamics and its functional implications
Avrămiea, A.-E. (2023) · doi:10.5463/thesis.144 · Cited by 1
Kirchner, J. H., Euler, L., & Gjorgjieva, J. (2023) · eLife · doi:10.7554/elife.87527.1 · Cited by 1
Synaptic Proteomes of Cortical Interneuron Classes Revealed by Antibody Directed Proximity LabelingPreprint
Battison, A. S., Liddle, J. C., Sumsky, S. L., O’Connell, C. B., Balsbaugh, J. L., & LoTurco, J. J. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.01.03.574066 · Cited by 1
Hayano, Y., Miyoshi, G., Paul, A., & Taniguchi, H. (2025) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2025.1568845 · Cited by 1
Arenivar, M. A., Ross, N. S., Flores, R. J., Zakariya, S., Wang, Z., Yarur, H. E., Kore, R., Richiez-Mateo, W. V., Limoges, A., Wang, H., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.05.13.653840 · Cited by 1
Silverstein, S. E., Clarity, T. T., Deshpande, M. S., Vaughan, E., Novik, S., Yarur, H. E., Zhang, S., Tsai, V. S., Ye, R., Mikofsky, R. M., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.07.21.665987 · Cited by 1
Cortical GABAergic inhibition dynamics around hippocampal sharp-wave ripplesPreprint
Rezaei, E., Tohidi, S., Nazari, M., McNaughton, B. L., & Mohajerani, M. H. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.08.17.670701 · Cited by 1
Factors determining competence for in vivo glia-to-neuron conversion
Galante, C. (2019) · Gutenberg Open Science · doi:10.25358/openscience-2366 · Cited by 1
Yáñez, F., Messore, F., Qi, G., Dehghani, N., Meyer, H., Feldmeyer, D., Sakmann, B. J., & Oberlaender, M. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.03.05.709819 · Cited by 1
GABAergic signaling in cortical feedback to the olfactory bulb
Mazo, C. (2017) · theses.fr (ABES) · doi:10.70675/2ebf44fdz7471z4669zbc58zdbe2e8e66849 · Cited by 1
Adrenomedullin restores the human cortical interneurons migration defects induced by hypoxiaPreprint
Puno, A., Michno, W., Li, L., Everitt, A., McCluskey, K., Htun, S., Nagar, D., Choi, J. B., Dai, Y., Park, S., et al. (2026) · eLife · doi:10.7554/elife.108134.2 · Cited by 1
Neurodevelopmental alterations in a mouse model of maternal immune activation
Fernandez, A. (2018) · theses.fr (ABES) · doi:10.70675/502cd79bzfc73z4f21z8675z5dea9ddf93e0 · Cited by 1
Papetti, A. V., Ma, Z., Ng, M., Jin, M., Levison, S. W., & Jiang, P. (2026) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.64898/2026.05.26.728058 · Cited by 1
Double Trouble: Impairment of Two Interneuron Types in a Dravet Mouse Model
Kearney, J. A. (2015) · Epiliepsy currents/Epilepsy currents · doi:10.5698/1535-7597-15.1.47
Hippocampus, Model Inhibitory Cells
Skinner, F. K., & Ferguson, K. (2015) · Springer eBooks · doi:10.1007/978-1-4614-6675-8_29
Reverse engineering inhibitory circuits in hippocampal CA3
Wester, J. C. (2016) · The Journal of Physiology · doi:10.1113/jp272620
Cholinergic transmission in the cerebral cortex of a conditional murine model of ADNFLE
Meneghini, S. (2016) · BOA (University of Milano-Bicocca)
Human brains teach us a surprising lesson
McKenzie, M. G., & Fishell, G. (2016) · Science · doi:10.1126/science.aai9379
Self-citationBlood on the Tracks: Two Pathways for Predation
Rozeske, R. R., & Herry, C. (2017) · Cell · doi:10.1016/j.cell.2016.12.042
Kapadia, F. (2016) · TSpace (University of Toronto)
Visual function in human and experimental glaucoma
Vasalauskaite, A. (2016) · ORCA Online Research @Cardiff (Cardiff University)
Re-expression of MeCP2 in early adulthood recovers cortical function in Rett syndrome
Simon, A. J. (2016) · Digital Access to Scholarship at Harvard (DASH) (Harvard University)
Libé‐Philippot, B. (2017) · theses.fr (ABES) · doi:10.70675/d55d00d1z9a58z4436zb726zf903ff3c2d0a
Pardillo-Díaz, R. (2017) · LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas)
LAPORTA, A. (2018) · Archivio Istituzionale della Ricerca (Universita Degli Studi Di Milano) · doi:10.13130/laporta-angela_phd2018-03-23
Rózsa, M. (2018) · SZTE Repository of Dissertations (University of Szeged) · doi:10.14232/phd.9755
The connectivity logic of cannabinoid type-1 expressing interneurones in the mouse visual cortex
Montmerle, M. (2017) · theses.fr (ABES) · doi:10.70675/c0579af5z9002z4a6dz85bfz85f3bee027e8
Neuronal circuits of experience-dependent plasticity in the primary visual cortex
Dylda, E. (2018) · ERA
Exploring the Interneuron Canopy Atop the ‘Impenetrable Jungle’
Chittajallu, R., Gonzales, C. B., & McBain, C. J. (2019) · Trends in Neurosciences · doi:10.1016/j.tins.2019.01.001
The Role of Synaptic Inhibition in the Primary Motor Cortex of an ALS Mouse Model
Place, K. M. (2018) · TSpace (University of Toronto)
Buzsáki, G. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190905385.003.0011
Buzsáki, G. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190905385.003.0012
Buzsáki, G. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190905385.003.0005
Buzsáki, G. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190905385.003.0013
Enhancing Brain Performance by Externalizing Thought
Buzsáki, G. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190905385.003.0009
Internally Organized Activity During Offline Brain States
Buzsáki, G. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190905385.003.0008
Buzsáki, G. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190905385.003.0004
The integration of extrinsic and intrinsic neuromodulators in the olfactory system
Lizbinski, K. M. (2018) · The Research Repository @ WVU (West Virginia University) · doi:10.33915/etd.3753
How Low Can You Go? Calling Robust ATAC-Seq Peaks Through Read Down-SamplingPreprint
Lihm, J., Ahrens, S., Ballouz, S., Lee, H., Crow, M., Tollkühn, J., McCarthy, S., Li, B., McCombie, W. R., & Gillis, J. (2018) · SSRN Electronic Journal · doi:10.2139/ssrn.3266868
Ca²+ mechanisms of synaptic integration and plasticity in inhibitory interneurons
Camiré, O. (2019) · Corpus Université Laval (Université Laval)
Tactile discrimination learning in mice
Pacchiarini, N. (2019) · ORCA Online Research @Cardiff (Cardiff University)
Shimell, J. J. (2019) · cIRcle (University of British Columbia) · doi:10.14288/1.0384822
Inhibitory mechanisms for visual learning in the human brain
Frangou, P. (2018) · Apollo (University of Cambridge) · doi:10.17863/cam.28130
Stimulation électrique transcranienne multisite dans l'épilepsie pharmaco-résistante
Denoyer, Y. (2019) · ORI-OAI warehouse (University of Rennes)
Lateralized role of prefrontal cortex in guiding orienting behaviorPreprint
Mohebi, A., & Oweiss, K. G. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.04.12.038356
Exciting inhibition: Local regulation of synapse formation and plasticity
Kruijssen, D. L. H. (2020) · Utrecht University Repository (Utrecht University) · doi:10.33540/296
Slow Inhibition and Inhibitory Recruitment in the Hippocampal Dentate Gyrus
Mircheva, Y. (2020) · Corpus Université Laval (Université Laval)
Inhibitory Dysfunction in the SOD1-ALS Motor Cortex
Khademullah, C. S. (2018) · TSpace (University of Toronto)
Adolf, A., Turko, P., Rohrbeck, A., Just, I., Vida, I., Ahnert‐Hilger, G., & Höltje, M. (2020) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2020.596072
McKenzie, M. G., Cobbs, L., Petros, T. J., Halford, M. M., Stacker, S. A., Zou, Y., Fishell, G., & Au, E. (2018) · SSRN Electronic Journal · doi:10.2139/ssrn.3155597
Self-citationYiannakas, A., Chandran, S. K., Kayyal, H., Gould, N. L., Khamaisy, M., & Rosenblum, K. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.03.01.433377
Lai, T. K. Y. (2019) · TSpace (University of Toronto)
Large-scale dendritic spine extraction and analysis through petascale computingPreprint
Wildenberg, G. A., Li, H., Badalamente, G. S., Uram, T. D., Ferrier, N., & Kasthuri, N. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.07.29.454371
The construction of 3D cognitive networks from iPSCs through precise spatiotemporal specification
Miu, K.-K., Cao, D., Wang, Z., Hao, S., & Chan, W. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-823809-7.00012-8
Coltogirone, R. A. (2021) · The Research Repository @ WVU (West Virginia University) · doi:10.33915/etd.8280
Vroman, R., & McKay, L. S. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.11.17.468122
Neuronal cell-type and circuit basis for visual predictive processingPreprint
Zou, J., Huang, L., Wang, L., Xu, Y., Li, C., Peng, Q., Zeng, H., Zhang, S., & Li, L. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.12.31.474667
Engelhardt, K.-A. (2021) · eDiss (Georg-August-Universität Göttingen) · doi:10.53846/goediss-8824
Milton, A. L. (2019) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.734996995.793567218
Sajikumar, S., & Raghuraman, R. (2019) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.734996995.793556932
Muotri, A. R. (2019) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.733994888.793560520
Sala, C. (2018) · Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature · doi:10.3410/f.732860113.793545803
Buzsáki, G. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780190905385.003.0014
Metadata
- Authors
- Kepecs, A., & Fishell, G.
- Venue
- Nature
- Published
- 2014-01
- Volume
- 505
- Issue
- 7483
- Pages
- 318-326
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC4349583
- OpenAlex
- W1970789949
- Cited by
- 1,110
- References
- 126
- Citations by year
- 2026: 46 · 2025: 95 · 2024: 85 · 2023: 77 · 2022: 92 · 2021: 114 · 2020: 92 · 2019: 118 · 2018: 105 · 2017: 107 · 2016: 82 · 2015: 71 · 2014: 26
- FWCI
- 10.89
- 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 Mental Health (R01MH071679, MH095147, R01MH095147, MH071679, R37MH071679)
- National Institute of Neurological Disorders and Stroke (NS 081297, P01NS074972, R01NS075531, NS074972, R01NS081297)
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Life Sciences › Neuroscience › Developmental Neuroscience › Neurogenesis and neuroplasticity mechanisms
- Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
- Keywords
- GABAergic interneurons, interneuron classification, brain circuits, inhibition, telencephalon, interneuron development
- MeSH terms
- Animals, Behavior, Humans, Interneurons, Mental Processes, Models, Neurological, Neural Pathways, Cell Lineage, Cell Proliferation
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