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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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In the citing paper
“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
“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
The 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
“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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“Such a combinational correspondence illustrates that cell types are conserved across species, although specific features of cell types (e.g. marker genes) are not (Hodge et al., 2019).”
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“Profound differences in animal and human physiology [33] are a critical source of poor translation.”
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Lessons from single cell sequencing in CNS cell specification and function
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“In order to assess the relative contribution of different isoforms to the overall expression of CYP20A1, we used publicly available RNA-seq data from 15928 single nuclei derived from the different layers of the human cerebral cortex (32).”
MethodSelf-citationSingle nucleus sequencing fails to detect microglial activation in human tissuePreprint
Thrupp, N., Frigerio, C. S., Wolfs, L., Skene, N., Poovathingal, S., Fourne, Y., Matthews, P. M., Theys, T., Mancuso, R., Strooper, B. D., et al. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.04.13.035386 · Cited by 11
Glaser, A. K., Chandrashekar, J. V., Vasquez, S., Arshadi, C., Ouellette, N. D., Jiang, X., Baka, J., Kovács, G., Woodard, M., Seshamani, S., et al. (2023) · eLife · doi:10.7554/elife.91979.1 · Cited by 12
Self-citationAAV-mediated interneuron-specific gene replacement for Dravet syndromePreprint
Mich, J. K., Ryu, J., Wei, A. D., Gore, B. B., Guo, R., Bard, A. M., Martinez, R. A., Bishaw, Y. M., Luber, E. M., Oliveira, L. M., et al. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.12.15.571820 · Cited by 12
Self-citationViswanadham, V., Kim, S. N., Caglayan, E., Doan, R. N., Dou, Y., Bizzotto, S., Khoshkhoo, S., Huang, A. Y., Yeh, R. C., Chhouk, B. H., et al. (2025) · Cell Reports · doi:10.1016/j.celrep.2025.116458 · Cited by 40
“After extensive quality control, we retained 71,461 nuclei across 13 snRNA-seq experiments encompassing 37 different cell types based on the Allen Brain Atlas 51 (STAR Methods; Figures 5A and S5A; Table S4.”
InfluentialGe, W., Kan, R. L., Yilgor, C., Fazzari, E., Nano, P. R., Azizad, D. J., Shinglot, H., Li, M. X., Ito, J., Tse, C., et al. (2026) · Cell Reports · doi:10.1016/j.celrep.2025.116848 · Cited by 17
Developmental Programming by Perinatal Glucocorticoids
Hong, J. Y. (2022) · Molecules and Cells · doi:10.14348/molcells.2022.0042 · Cited by 11
“These results along with other single-cell studies show that hippocampal neuronal composition and regulation of GR and MR are generally conserved between mice and humans (Hartmann et al., 2021; Hodge et al., 2019).”
ResultGuerra, K. T. K., Renner, J., Vásquez, C. E., & Rasia‐Filho, A. A. (2022) · The Journal of Comparative Neurology · doi:10.1002/cne.25430 · Cited by 10
Mapping of morpho-electric features to molecular identity of cortical inhibitory neurons
Roussel, Y., Verasztó, C., Rodarie, D., Damart, T., Reimann, M., Ramaswamy, S., Markram, H., & Keller, D. X. (2023) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1010058 · Cited by 11
Saxena, P., Sinha, A., & Singh, S. K. (2024) · Computer Methods in Biomechanics & Biomedical Engineering · doi:10.1080/10255842.2023.2300685 · Cited by 13
Genetic approaches to elucidating cortical and hippocampal GABAergic interneuron diversity
Machold, R. P., & Rudy, B. (2024) · Frontiers in Cellular Neuroscience · doi:10.3389/fncel.2024.1414955 · Cited by 12
ADAR3 modulates neuronal differentiation and regulates mRNA stability and translation
Karlström, V., Sagredo, E. A., Planells, J., Welinder, C., Jungfleisch, J., Barrera-Conde, A., Engfors, L., Daniel, C., Gebauer, F., Visa, N., et al. (2024) · Nucleic Acids Research · doi:10.1093/nar/gkae753 · Cited by 11
A tumorigenicity evaluation platform for cell therapies based on brain organoids
Xue, J., Chu, Y., Huang, Y., Chen, M., Sun, M. J., Fan, Z., Wu, Y., & Chen, L. (2024) · Translational Neurodegeneration · doi:10.1186/s40035-024-00446-5 · Cited by 12
“Significant differences in development, macroscopic architecture, cellular composition, and gene expression between human and rodent brains challenge the validity of these animal models [16, 17].”
BackgroundA temporal cortex cell atlas highlights gene expression dynamics during human brain maturation
Steyn, C., Mishi, R. D., Fillmore, S., Verhoog, M. B., More, J., Rohlwink, U. K., Melvill, R., Butler, J. T., Enslin, N., Jacobs, M., et al. (2024) · Nature Genetics · doi:10.1038/s41588-024-01990-6 · Cited by 13
Fate plasticity of interneuron specification
Mostajo-Radji, M. A., Mancia, W., Breevoort, A., Gonzalez-Ferrer, J., Schweiger, H. E., Lehrer, J., Zhou, L., Schmitz, M. T., Perez, Y., Mukhtar, T., et al. (2025) · iScience · doi:10.1016/j.isci.2025.112295 · Cited by 9
Kim, J. Y., Poddar, A., Sandoval, K., Chu, J. S. F., Horton, E. C., Cui, D., Nakamura, K. C., Lu, I.-L., Mui, M. H., Bartels, T., et al. (2025) · Nature Neuroscience · doi:10.1038/s41593-025-01987-2 · Cited by 13
“To investigate the interneuron subtype composition across Arc–cortical targets, we integrated our snRNA-seq dataset with published snRNA-seq datasets of human developing and adult neocortical interneurons 39 (Supplementary Fig.”
Hu, W., Foord, C., Hsu, J., Fan, L., Corley, M. J., Lanjewar, S. N., Xu, S., Belchikov, N., He, Y., Pang, A. P. S., et al. (2025) · Nature Biotechnology · doi:10.1038/s41587-025-02734-5 · Cited by 14
“Neuronal subtypes are transcriptionally distinct with unique synaptic properties 28–32 .”
The evolution of gene regulation in mammalian cerebellum development
Sarropoulos, I., Sepp, M., Yamada, T., Schäfer, P. S. L., Trost, N., Schmidt, J., Schneider, C., Drummer, C., Mißbach, S., Taskiran, I. I., et al. (2026) · Science · doi:10.1126/science.adw9154 · Cited by 13
Cerebral organoids: emerging ex vivo humanoid models of glioblastoma
Papaioannou, M.-D., Sangster, K. T., Sajid, R. S., Djuric, U., & Diamandis, P. (2020) · Acta Neuropathologica Communications · doi:10.1186/s40478-020-01077-3 · Cited by 11
Bordone, M. C., & Barbosa‐Morais, N. L. (2020) · Frontiers in Neuroscience · doi:10.3389/fnins.2020.607215 · Cited by 9
“Despite the known differences in gene expression between mouse and human brain cells (Hodge et al., 2019), the same trends can be seen using the mouse signature (Supplementary Figures 9A,B).”
BackgroundPhenotyping Neurodegeneration in Human iPSCs
Li, J., & Fraenkel, E. (2021) · Annual Review of Biomedical Data Science · doi:10.1146/annurev-biodatasci-092820-025214 · Cited by 11
Astrocytes, a Promising Opportunity to Control the Progress of Parkinson’s Disease
Sánchez, A., Moráles, I., Rodriguez‐Sabate, C., Solé-Sabater, M., & Rodrı́guez, M. (2021) · Biomedicines · doi:10.3390/biomedicines9101341 · Cited by 12
Roll, L., Lessmann, K., Brüstle, O., & Faissner, A. (2022) · Cells · doi:10.3390/cells11050760 · Cited by 13
Connectome-based biophysics models of Alzheimer’s disease diagnosis and prognosis
Torok, J., Anand, C., Verma, P., & Raj, A. (2022) · Translational research · doi:10.1016/j.trsl.2022.08.008 · Cited by 11
Cai, W., Song, W., Liu, Z., Maharjan, D. T., Liang, J., & Lin, G. N. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms231911581 · Cited by 11
“We downloaded 6468 cell samples of single-cell RNA-seq data [16,17] clustered from 19 neuronal and non-neuronal cell types isolated from middle temporal gyrus (MTG) and anterior cingulate cortex (ACC) tissues from normal adults.”
MethodZhang, W., Han, B. R., Zhang, H., Fu, R., Lu, Y., & Zhang, G. (2023) · Heliyon · doi:10.1016/j.heliyon.2023.e14949 · Cited by 11
Little, P., Liu, S., Zhabotynsky, V., Li, Y., Lin, D. Y., & Sun, W. (2023) · Nature Communications · doi:10.1038/s41467-023-38795-w · Cited by 9
“UsingICeDT 24 ,weestimatedcell type proportions based on TReC and cell type-speci fi c reference data for 5 brain cell types 25 and 22 blood cell types 26 .”
Noncoding transcripts are linked to brain resting-state activity in non-human primates
Wang, W., Bo, T., Zhang, G., Li, J., Ma, J., Ma, L., Hu, G., Tong, H., Lv, Q., Araujo, D. J., et al. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.112652 · Cited by 12
Yin, P., Cai, Y., Cui, T., Berg, A. J., Wang, T., Morency, D. T., Paganelli, P. M., Lok, C., Yang, X., Vicini, S., et al. (2023) · Journal of Neuroscience · doi:10.1523/jneurosci.0515-23.2023 · Cited by 11
Application of Computational Biology to Decode Brain Transcriptomes
Li, J., & Wang, G. (2019) · Genomics Proteomics & Bioinformatics · doi:10.1016/j.gpb.2019.03.003 · Cited by 11
Roberts, K., & Bayraktar, O. A. (2020) · Methods in molecular biology · doi:10.1007/978-1-0716-0623-0_15 · Cited by 10
Ramos-Vicente, D., & Bayés, À. (2020) · Open Biology · doi:10.1098/rsob.200234 · Cited by 11
“We argued that the high diversity of neuronal types [3] or the wide array of glutamate receptor functionalities [4] found in vertebrates is unlikely to be the result of an increased repertoire of genes coding for them.”
BackgroundCell type innovation at the tips of the animal tree
Kishi, Y., & Parker, J. (2021) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2021.01.009 · Cited by 10
“scRNAseq has already been used to address questions related to cell type evolution [5 ,7,8,39,40], and has the potential to illuminate how cell type novelties, such as secretory cells, are assembled.”
MethodTranscriptomic expression of AMPA receptor subunits and their auxiliary proteins in the human brain
Shen, K., & Limón, A. (2021) · Neuroscience Letters · doi:10.1016/j.neulet.2021.135938 · Cited by 13
Neuronal Cell-type Engineering by Transcriptional Activation
Liu, S., Striebel, J., Pasquini, G., Ng, A. H. M., Khoshakhlagh, P., Church, G. M., & Busskamp, V. (2021) · Frontiers in Genome Editing · doi:10.3389/fgeed.2021.715697 · Cited by 11
“Single cell reference atlases of human brain cell types represent an outstanding resource for in vitro cell fate studies (Hodge et al., 2019).”
BackgroundPech, U., Janssens, J., Schoovaerts, N., Kuenen, S., Calatayud, C., Gallego, S. F., Makhzami, S., Hulselmans, G. J., Poovathingal, S. K., Davie, K., et al. (2024) · eLife · doi:10.1101/2023.03.11.532176 · Cited by 18
“Nuclei of human samples were prepared as described in (Hodge et al., 2019; Slyper et al., 2020).”
MethodTranscriptomic and genetic analysis suggests a role for mitochondrial dysregulation in schizophreniaPreprint
Bast, L., Yao, S., Martínez‐López, J. A., Memic, F., French, H., Valiukonyte, M., Karlsson, R., Wen, J., Song, J., Zhang, R., et al. (2025) · medRxiv · doi:10.1101/2025.03.14.25323827 · Cited by 12
Co-clustering of spatially resolved transcriptomic data
Sottosanti, A., & Risso, D. (2023) · The Annals of Applied Statistics · doi:10.1214/22-aoas1677 · Cited by 9
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“Recent snRNA-seq has enabled large-scale characterization of human brain transcriptomic profiles at the individual cell level [39,40].”
BackgroundA single-cell trajectory atlas of striatal development
Anderson, A. G., Kulkarni, A., & Konopka, G. (2023) · Scientific Reports · doi:10.1038/s41598-023-36255-5 · Cited by 9
Huang, L., Mut-Arbona, P., Varga, B., Török, B., Brunner, J., Arszovszki, A., Iring, A., Kisfali, M., Vizi, E. S., & Sperlágh, B. (2023) · iScience · doi:10.1016/j.isci.2023.107560 · Cited by 10
Shen, Y., Shao, M., Hao, Z.-Z., Huang, M., Xu, N., & Liu, S. (2024) · Neuroscience Bulletin · doi:10.1007/s12264-023-01160-4 · Cited by 11
“1 3 primates, and humans, particularly in genes related to neuronal structure and function [2, 13–15].”
BackgroundInfluentialCHRNA5 links chandelier cells to severity of amyloid pathology in aging and Alzheimer’s disease
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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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