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Conserved cell types with divergent features in human versus mouse cortex
Open accessPublished version of a preprint
Abstract
Elucidating the cellular architecture of the human cerebral cortex is central to understanding our cognitive abilities and susceptibility to disease. Here we used single-nucleus RNA-sequencing analysis to perform a comprehensive study of cell types in the middle temporal gyrus of human cortex. We identified a highly diverse set of excitatory and inhibitory neuron types that are mostly sparse, with excitatory types being less layer-restricted than expected. Comparison to similar mouse cortex single-cell RNA-sequencing datasets revealed a surprisingly well-conserved cellular architecture that enables matching of homologous types and predictions of properties of human cell types. Despite this general conservation, we also found extensive differences between homologous human and mouse cell types, including marked alterations in proportions, laminar distributions, gene expression and morphology. These species-specific features emphasize the importance of directly studying human brain.
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“As a third example of the great elaboration and specialization associated with consciousness, the more-advanced animal brains have the largest numbers of neuron types, with highly complex interactions (Strausfeld, 2012; Feinberg and Mallatt, 2016a; Hodge et al., 2019).”
From Phenomenal Consciousness and Emergence: Eliminating the Explanatory Gap (2020) · cites this paper as Hodge et al., 2019
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“nuclei were sorted using a standard gating strategy to exclude multiplets24”
From Integrated multimodal cell atlas of Alzheimer’s disease (2024) · cites this paper as [24]
In the citing paper
“8 out of 14 modules showed greater intra-module correlation than a comparable random gene set in the adult human brain dataset from Hodge et al (30) (Fig. 4B).”
From In vivo Perturb-Seq reveals neuronal and glial abnormalities associated with autism risk genes (2020) · cites this paper as [30]
In the citing paper
“In addition, multiplex FISH is already being used to measure the proportions of transcriptomic types within a given brain tissue (Hodge et al., 2019; Moffitt et al., 2018; Zhang et al., 2020).”
From Integrated Morphoelectric and Transcriptomic Classification of Cortical GABAergic Cells (2020) · cites this paper as Hodge et al., 2019
In the citing paper
“Single-cell RNA-sequencing (scRNA-seq) studies have systematically characterized and classified cell types in individual regions of isocortex and hippocampus”
From A taxonomy of transcriptomic cell types across the isocortex and hippocampal formation (2021) · cites this paper as Hodge et al., 2019
In the citing paper
“The application of single-cell RNA sequencing (scRNA-seq) to the neocortex and other brain regions has revealed a complex but tractable hierarchical organization of transcriptomic cell types that are consistent overall with knowledge from decades of anatomical, physiological and developmental studies but with an unmatched level of granularity7–11.”
From A multimodal cell census and atlas of the mammalian primary motor cortex (2021) · cites this paper as [10]
In the citing paper
“Substantiating previous studies9,10, our multimodal cross-species study of the primary motor cortex suggests that a general principle of cortical cell-type organization is its hierarchical relationship, whereby high-level classes linked by major branches comprise progressively finer subpopulations connected by minor branches.”
From A multimodal cell census and atlas of the mammalian primary motor cortex (2021) · cites this paper as [10]
In the citing paper
“Comparing human with mouse and non-human primates reveals both conserved and distinct cell type signatures, including species-specific differences in the proportions of cell populations and in gene expression within homologous cell classes and types (Bakken et al., 2020; Hodge et al., 2019; Krienen et al., 2020).”
From Single-Cell Sequencing of Brain Cell Transcriptomes and Epigenomes (2021) · cites this paper as Hodge et al., 2019
In the citing paper
“Evolutionary conservation and divergence provide insight into the gene regulatory programs that were selected for their impact on cognitive function (Bakken et al., 2020; Hodge et al., 2019; Krienen et al., 2020).”
From Single-Cell Sequencing of Brain Cell Transcriptomes and Epigenomes (2021) · cites this paper as Hodge et al., 2019
In the citing paper
“We observed numerous genes with categorical changes in cell-type-specific expression patterns (including NTNG1, IQGAP2 and TRPC3) and, in rare cases, genes that were a specific marker in one cell class in some species but not detected at all in the interneurons of the other species11”
From Innovations present in the primate interneuron repertoire (2020) · cites this paper as [11]
In the citing paper
“which suggests that the genes that encode these markers stably delineate a core repertoire of neocortical interneuron types in these species11,15,18”
From Innovations present in the primate interneuron repertoire (2020) · cites this paper as [11]
In the citing paper
“The expansion of this LAMP5+ LHX6+ cell type throughout the neocortex in diverse primates probably explains a recent observation11 that this cell type is much more abundant in the human temporal lobe than in the mouse V1.”
From Innovations present in the primate interneuron repertoire (2020) · cites this paper as [11]
In the citing paper
“they obtained 45 human interneuron clusters, whereas our marmoset data resolved to 22 clusters”
From Innovations present in the primate interneuron repertoire (2020) · cites this paper as [11]
In the citing paper
“However, in agreement with other reports11, these types were inconsistently observed across individual animals and regions, likely due to laminar location and low abundance, and were not analysed further.”
From Innovations present in the primate interneuron repertoire (2020) · cites this paper as [11]
In the citing paper
“Notably, this approach provides the means to evaluate and compare the circuit contributions and function of PV cINs across species, regardless of their genetic accessibility44,45.”
From Viral manipulation of functionally distinct interneurons in mice, non-human primates and humans (2020) · cites this paper as [44]
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Connecting single-cell transcriptomes to projectomes in the mouse visual cortex
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Self-citationNeural cell diversity in the light of single-cell transcriptomics
Moya, S. M. F., Ganesh, A. J., & Plass, M. (2023) · Transcription · doi:10.1080/21541264.2023.2295044 · Cited by 14
“Up till now we can cover the neuronal diversity in the human brain with several important studies from the cortex [22,33,34], hippocampus [35], striatum [25,36], midbrain [37,38], cerebellum [22], hypothalamus [39], and even retina [40,41] (Figure 1).”
BackgroundIntegrative analysis of epilepsy-associated genes reveals expression-phenotype correlations
Chi, W., & Kiskinis, E. (2024) · Scientific Reports · doi:10.1038/s41598-024-53494-2 · Cited by 15
“Brain cell-type specific transcriptomes were obtained from BrainMap 8 .”
MethodInfluentialLee, C.-Y., Riffle, D., Xiong, Y., Momtaz, N., Lei, Y., Pariser, J. M., Sikdar, D., Hwang, A., Duan, Z., & Zhang, J. (2024) · BMC Neuroscience · doi:10.1186/s12868-024-00867-y · Cited by 17
“0 database [28] such as mitochondrial genes and certain genes highly correlated with RNA sample quality [29].”
BackgroundSIMS: A deep-learning label transfer tool for single-cell RNA sequencing analysis
Gonzalez-Ferrer, J., Lehrer, J., O’Farrell, A., Paten, B., Teodorescu, M., Haussler, D. H., Jönsson, V. D., & Mostajo-Radji, M. A. (2024) · Cell Genomics · doi:10.1016/j.xgen.2024.100581 · Cited by 16
Tian, J., Jia, K., Wang, T., Guo, L., Xuan, Z., Michaelis, E. K., Swerdlow, R. H., Initiative, A. D. N., & Du, H. (2024) · Translational Psychiatry · doi:10.1038/s41398-024-02958-0 · Cited by 17
“[47, 48].”
MethodAbbaspoor, S., & Hoffman, K. L. (2024) · Cell Reports · doi:10.1016/j.celrep.2024.114519 · Cited by 17
“All procedures were conducted in accordance with the approved protocols and authorized procedures under the local animal care authori�es (Ins�tu�onal Animal Care and Use Commitee).”
MethodTranscriptomic pathology of neocortical microcircuit cell types across psychiatric disorders
Arbabi, K., Newton, D. F., Oh, H., Davie, M., Lewis, D. A., Wainberg, M., Tripathy, S. J., & Sibille, E. L. (2024) · Molecular Psychiatry · doi:10.1038/s41380-024-02707-1 · Cited by 18
Dolganova, I. N., Aleksandrova, P. V., Nikitin, P. V., Алексеева, А. И., Chernomyrdin, N. V., Musina, G. R., Beshplav, S.-I. T., Reshetov, I. V., Aa, P., Курлов, В. Н., et al. (2020) · Biomedical Optics Express · doi:10.1364/boe.409692 · Cited by 15
Gomes, A. R., Fernandes, T. G., Cabral, J. M. S., & Diogo, M. M. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms22073751 · Cited by 15
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Ettema, L., Lochocki, B., Hoozemans, J. J. M., de Boer, J. F., & Ariese, F. (2022) · Journal of Optics · doi:10.1088/2040-8986/ac5b51 · Cited by 15
Lukacs, I. P., Francavilla, R., Field, M., Hunter, E., Howarth, M., Horie, S., Plaha, P., Stacey, R. J., Livermore, L. J., Ansorge, O., et al. (2022) · Cerebral Cortex · doi:10.1093/cercor/bhac195 · Cited by 14
“Basket cells, including some parvalbuminexpressing (PV+) cells, show great diversity in molecular expression (Tasic et al. 2018; Hodge et al. 2019; Gouwens et al. 2020; Bakken et al. 2021), lateral spread and interlaminar specificity of their axons (Somogyi et al.”
BackgroundMethodInfluentialGarcía, F., & Heiman, M. (2025) · Molecular Neurodegeneration · doi:10.1186/s13024-025-00799-z · Cited by 14
Molecular Signatures in Cortical Development
Steyert, M. R., Li, T., Piao, X., & Nowakowski, T. J. (2025) · Annual Review of Neuroscience · doi:10.1146/annurev-neuro-091823-014001 · Cited by 15
Human iPSC-Derived Neurons as A Platform for Deciphering the Mechanisms behind Brain Aging
Chao, C., Shen, P.-W., Tzeng, T., Kung, H., Tsai, T., & Wong, Y. (2021) · Biomedicines · doi:10.3390/biomedicines9111635 · Cited by 13
BRN2 as a key gene drives the early primate telencephalon development
Zhu, X., Guo, Y., Chu, C., Liu, D., Duan, K., Yin, Y., Si, C., Kang, Y., Yao, J., Du, X., et al. (2022) · Science Advances · doi:10.1126/sciadv.abl7263 · Cited by 15
Winkler, E. A., Pacult, M. A., Catapano, J. S., Scherschinski, L., Srinivasan, V. M., Graffeo, C. S., Oh, S. P., & Lawton, M. T. (2022) · Neurosurgical FOCUS · doi:10.3171/2022.4.focus2291 · Cited by 15
Achieving a Deeper Understanding of Drug Metabolism and Responses Using Single-Cell Technologies
Wheeler, A. M., Eberhard, C. D., Mosher, E. P., Yuan, Y., Wilkins, H. N., Seneviratne, H. K., Orsburn, B. C., & Bumpus, N. N. (2023) · Drug Metabolism and Disposition · doi:10.1124/dmd.122.001043 · Cited by 14
“In the cortex alone, there have been 180 perceptible areas (Glasser et al., 2016) and 75 cell types identified (Hodge et al., 2019).”
BackgroundHicks, A. R., Reynolds, R. H., O’Callaghan, B., García-Ruiz, S., Gil-Martínez, A. L., Botía, J. A., Plun‐Favreau, H., & Ryten, M. (2023) · Brain · doi:10.1093/brain/awad246 · Cited by 17
“31,32 Consistent with expectation, the NSL complex genes displayed no overt differences in cell type-specific gene expression when considered collectively (Supplementary Fig.”
BackgroundGalvão, I. C., Kandratavicius, L., Messias, L. A., Athié, M. C. P., Assis‐Mendonça, G. R., Alvim, M. K. M., Ghizoni, E., Tedeschi, H., Yasuda, C. L., Cendes, F., et al. (2023) · Scientific Reports · doi:10.1038/s41598-023-40240-3 · Cited by 14
“S2A): Hodge et al. 26 (Cell Atlas or “CA” signature), Lake et al. 27 (“LK” signature), Nagy et al. 28 (“NG” signature), and Velmeshev et al. 29 (“VL” signature).”
Evolutionary conservation of hippocampal mossy fiber synapse properties
Pelkey, K. A., Vargish, G. A., Pellegrini, L. V., Calvigioni, D., Chapeton, J. I., Yuan, X. Q., Hunt, S., Cummins, A. C., Eldridge, M. A. G., Pickel, J. M., et al. (2023) · Neuron · doi:10.1016/j.neuron.2023.09.005 · Cited by 16
STAB2: an updated spatio-temporal cell atlas of the human and mouse brain
Yang, Y., Gan, Z., Zhang, J., Zhao, X., Yang, Y., Han, S., Wu, W., & Zhao, X. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad955 · Cited by 15
Morphological Features of Human Dendritic Spines
Renner, J., & Rasia‐Filho, A. A. (2023) · Advances in neurobiology · doi:10.1007/978-3-031-36159-3_9 · Cited by 18
Functional subtypes of synaptic dynamics in mouse and human
Beninger, J., Rossbroich, J., Tóth, K., & Naud, R. (2024) · Cell Reports · doi:10.1016/j.celrep.2024.113785 · Cited by 15
Obesity and the cerebral cortex: Underlying neurobiology in mice and humans
Patel, Y., Woo, A., Shi, S. S. W., Ayoub, R., Shin, J., Botta, A. M., Ketela, T., Sung, H., Lerch, J. P., Nieman, B. J., et al. (2024) · Brain Behavior and Immunity · doi:10.1016/j.bbi.2024.04.033 · Cited by 14
“Broadly speaking, there is striking conservation of cell types (Hodge, 2019), canonical circuit motifs (Kim, 2023), and neuroanatomical transcriptomics (Beauchamp, 2022) between the mouse and human cortex.”
Lee, E. J., Bae, S., Suh, M., Choi, Y., Choi, Y., Hwang, D. W., & Lee, D. S. (2024) · BMC Genomics · doi:10.1186/s12864-024-10434-8 · Cited by 15
“…resource reports in the literature up to the date of this investigation run by trial-and-evaluation and then the choice; for example, for neurons and neuronal sub-types, Hodge et al.’s report [75] was adopted as is or after NS Forest [59] to define 20 GABAergic neurons and 12 glutamatergic neurons.”
MethodInfluentialCharacterization of reduced astrocyte creatine kinase levels in Alzheimer's disease
Zheng, T., Kotol, D., Sjöberg, R., Mitsios, N., Uhlén, M., Zhong, W., Edfors, F., & Mulder, J. (2024) · Glia · doi:10.1002/glia.24569 · Cited by 14
“However, our results cannot completely rule out expression of CKB in neurons, as previous single nuclei transcriptomic (Hodge et al., 2019) and single cell mass spectrometry (Sandebring-Matton et al., 2021) studies have identified CKB in neurons.”
Regional brain iron correlates with transcriptional and cellular signatures in Alzheimer's disease
Yang, A., Luan, J., Xu, M., Du, L., Lv, K., Hu, P., Shu, N., Yuan, Z., Shmuel, A., & Ma, G. (2025) · Alzheimer s & Dementia · doi:10.1002/alz.14459 · Cited by 14
“45 It was shown in previous study 46 that correspondence can be made between the labels in the two datasets, namely between the respective labels for astrocytes (ASC), microglia (MG), endothelial cells (END), oligo-dendrocytes (ODCs), oligodendrocyte precursor cells (OPCs), and gamma-aminobutyric…”
PRC1 catalytic unit RING1B regulates early neural differentiation of human pluripotent stem cells
Desai, D., Khanna, A., & Pethe, P. S. (2020) · Experimental Cell Research · doi:10.1016/j.yexcr.2020.112294 · Cited by 14
Gambardella, I., Ascione, R., D’Agostino, D. P., Ari, C., Worku, B., Tranbaugh, R. F., Ivascu, N. S., Villena‐Vargas, J., & Girardi, L. N. (2021) · Journal of Neurochemistry · doi:10.1111/jnc.15341 · Cited by 14
“Although the murine was proven to be a satisfactory translational model in neuroscience (Holmes, 2008), speciesspecific differences exist in the CNS of the two mammalian models among many similarities (Hodge et al., 2019).”
BackgroundHuang, B., Peng, J., Huang, X., Liang, F., Wang, L., Shi, J., Yamada, A., & Chen, Y. (2021) · ACS Applied Materials & Interfaces · doi:10.1021/acsami.1c18465 · Cited by 14
Francistiová, L., Vörös, K., Lovász, Z., Dinnyés, A., & Kobolák, J. (2022) · Frontiers in Molecular Neuroscience · doi:10.3389/fnmol.2021.793769 · Cited by 14
Sheardown, E., Mech, A. M., Petrazzini, M. E. M., Leggieri, A., Gidziela, A., Hosseinian, S., Sealy, I. M., Torres-Pérez, J. V., Busch‐Nentwich, E. M., Malanchini, M., et al. (2022) · Neuroscience & Biobehavioral Reviews · doi:10.1016/j.neubiorev.2022.104559 · Cited by 13
Xing, Y., Zan, C., & Liu, L. (2023) · Frontiers in Neural Circuits · doi:10.3389/fncir.2023.1007755 · Cited by 14
Graffunder, A. S., Bresser, A. A. J., Vallone, V. B. F., Megges, M., Stachelscheid, H., Kühnen, P., & Opitz, R. (2024) · Scientific Reports · doi:10.1038/s41598-024-59533-2 · Cited by 18
“However, fundamental inter-species differences in tissue cytoarchitecture, neuronal cell types, developmental features and molecular pathways are complicating human disease modelling in many rodent models 6,7,29,30 .”
Gaps and Doubts in Search to Recognize Glioblastoma Cellular Origin and Tumor Initiating Cells
Włodarczyk, A., Grot, D., Stoczyńska-Fidelus, E., & Rieske, P. (2020) · Journal of Oncology · doi:10.1155/2020/6783627 · Cited by 14
Mounting evidence suggests human adult neurogenesis is unlikely
Nano, P. R., & Bhaduri, A. (2022) · Neuron · doi:10.1016/j.neuron.2022.01.004 · Cited by 16
The Neuron Phenotype Ontology: A FAIR Approach to Proposing and Classifying Neuronal Types
Gillespie, T., Tripathy, S. J., Sy, M. F., Martone, M. E., & Hill, S. (2022) · Neuroinformatics · doi:10.1007/s12021-022-09566-7 · Cited by 14
Recent ultra-rare inherited mutations identify novel autism candidate risk genesPreprint
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Satellite glial cells: Shaping peripheral input into the brain-body axis?
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ApoE-calypse tau: ApoE–tau synergy in Alzheimer’s disease
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Sex effects on gene expression across the human cerebral cortex at cell type resolution
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“Sophisticated experimental techniques continue to uncover the rich diversity and distinctness of neuron types (Harris et al., 2018; Hodge et al., 2019; Kepecs & Fishell, 2014; Sugino et al., 2019).”
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Gallo, C. M., Labadorf, A. T., Ho, A., & Beffert, U. (2022) · Genomics · doi:10.1016/j.ygeno.2022.110318 · Cited by 11
“types between mouse and human cortex despite overall conserved cell types [59].”
Background
Metadata
- Authors
- Hodge, R. D., Bakken, T. E., Miller, J. A., Smith, K. A., Barkan, E. R., Graybuck, L. T., Close, J. L., Long, B., Johansen, N., Penn, O., Yao, Z., Eggermont, J., Höllt, T., Levi, B. P., Shehata, S. I., Aevermann, B., Beller, A., Bertagnolli, D., Brouner, K., Casper, T., Cobbs, C., Dalley, R., Dee, N., Ding, S.-L., Ellenbogen, R. G., Fong, O., Garren, E., Goldy, J., Gwinn, R. P., Hirschstein, D., Keene, C. D., Keshk, M., Ko, A. L., Lathia, K., Mahfouz, A., Maltzer, Z., McGraw, M., Nguyen, T. N., Nyhus, J., Ojemann, J. G., Oldre, A., Parry, S., Reynolds, S., Rimorin, C., Shapovalova, N. V., Somasundaram, S., Szafer, A., Thomsen, E. R., Tieu, M., Quon, G., Scheuermann, R. H., Yuste, R., Sunkin, S. M., Lelieveldt, B., Feng, D., Ng, L., Bernard, A., Hawrylycz, M., Phillips, J. W., Tasic, B., Zeng, H., Jones, A. R., Koch, C., & Lein, E. S.
- Affiliations
- Allen Institute for Brain Science (US)
- University of California, Davis (US)
- Leiden University Medical Center (NL)
- J. Craig Venter Institute (US)
- University of Washington (US)
- Swedish Medical Center (US)
- Columbia University (US)
- Corresponding author
- Lein, Ed S.
- ORCID
- Hodge, Rebecca D.
- Bakken, Trygve E.
- Miller, Jeremy A.
- Smith, Kimberly A.
- Barkan, Eliza R.
- Graybuck, Lucas T.
- Close, Jennie L.
- Long, Brian
- Johansen, Nelson
- Yao, Zizhen
- Eggermont, Jeroen
- Höllt, Thomas
- Levi, Boaz P.
- Shehata, Soraya I.
- Aevermann, Brian
- Beller, Allison
- Bertagnolli, Darren
- Brouner, Krissy
- Casper, Tamara
- Cobbs, Charles
- Dalley, Rachel
- Dee, Nick
- Ding, Song-Lin
- Ellenbogen, Richard G.
- Fong, Olivia
- Goldy, Jeff
- Gwinn, Ryder P.
- Hirschstein, Daniel
- Keene, C. Dirk
- Ko, Andrew L.
- Lathia, Kanan
- Mahfouz, Ahmed
- Maltzer, Zoe
- Nguyen, Thuc Nghi
- Nyhus, Julie
- Ojemann, Jeffrey G.
- Oldre, Aaron
- Rimorin, Christine
- Shapovalova, Nadiya V.
- Somasundaram, Saroja
- Szafer, Aaron
- Thomsen, Elliot R.
- Tieu, Michael
- Quon, Gerald
- Scheuermann, Richard H.
- Yuste, Rafael
- Sunkin, Susan M.
- Lelieveldt, Boudewijn
- Feng, David
- Ng, Lydia
- Bernard, Amy
- Hawrylycz, Michael
- Phillips, John W.
- Tasic, Bosiljka
- Zeng, Hongkui
- Lein, Ed S.
- Venue
- Nature
- Published
- 2019-08-21
- Volume
- 573
- Issue
- 7772
- Pages
- 61-68
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- PMC
- PMC6919571
- OpenAlex
- W2969948459
- Cited by
- 1,775
- References
- 89
- Citations by year
- 2026: 199 · 2025: 242 · 2024: 275 · 2023: 269 · 2022: 235 · 2021: 289 · 2020: 212 · 2019: 43
- FWCI
- 64.09
- Type
- journal article
- Language
- en
- Open access
- green
- doi.org
- Licence
- Locations
- Nature (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Leiden Repository (Leiden University) (submittedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- University of Washington
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek (12720, 12721)
- National Institutes of Health (5u01mh114812-03, MH114812-02)
- National Institute of Mental Health (U01MH105982, U01MH114812, U19MH114830)
- National Institute of General Medical Sciences (T32GM008497)
- Topics
- 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
- Life Sciences › Neuroscience › Developmental Neuroscience › Neurogenesis and neuroplasticity mechanisms
- Keywords
- human cerebral cortex, middle temporal gyrus, cortical cell types, excitatory neurons, inhibitory neurons, single-nucleus RNA sequencing, human-mouse comparison, cortical laminar organization, species differences, neuronal morphology, gene expression
- MeSH terms
- RNA-Seq, Adolescent, Adult, Aged, Animals, Astrocytes, Cerebral Cortex, Biological Evolution, Female, Humans, Male, Middle Aged, Neural Inhibition, Neurons, Species Specificity, Principal Component Analysis, Mice, Young Adult, Single-Cell Analysis, Transcriptome
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