Thursday, November 6, 2025
No menu items!
HomeNatureThe new frontier in understanding human and mammalian brain development

The new frontier in understanding human and mammalian brain development

  • Gidziela, A. et al. A meta-analysis of genetic effects associated with neurodevelopmental disorders and co-occurring conditions. Nat. Hum. Behav. 7, 642–656 (2023).

    PubMed 
    PubMed Central 

    Google Scholar
     

  • Buescher, A. V. S., Cidav, Z., Knapp, M. & Mandell, D. S. Costs of autism spectrum disorders in the United Kingdom and the United States. JAMA Pediatr. 168, 721–728 (2014).

    PubMed 

    Google Scholar
     

  • Leigh, J. P. & Du, J. Brief report: Forecasting the economic burden of autism in 2015 and 2025 in the United States. J. Autism Dev. Disord. 45, 4135–4139 (2015).

    PubMed 

    Google Scholar
     

  • Molnár, Z. et al. New insights into the development of the human cerebral cortex. J. Anat. 235, 432–451 (2019).

    ADS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Wallace, J. L. & Pollen, A. A. Human neuronal maturation comes of age: cellular mechanisms and species differences. Nat. Rev. Neurosci. 25, 7–29 (2024).

    CAS 
    PubMed 

    Google Scholar
     

  • Satterstrom, F. K. et al. Large-scale exome sequencing study implicates both developmental and functional changes in the neurobiology of autism. Cell 180, 568–584.e23 (2020).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Willsey, H. R., Willsey, A. J., Wang, B. & State, M. W. Genomics, convergent neuroscience and progress in understanding autism spectrum disorder. Nat. Rev. Neurosci. 23, 323–341 (2022).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Petilla Interneuron Nomenclature Group. Petilla terminology: nomenclature of features of GABAergic interneurons of the cerebral cortex. Nat. Rev. Neurosci. 9, 557–568 (2008).


    Google Scholar
     

  • Zeng, H. & Sanes, J. R. Neuronal cell-type classification: challenges, opportunities and the path forward. Nat. Rev. Neurosci. 18, 530–546 (2017).

    CAS 
    PubMed 

    Google Scholar
     

  • Colonna, M. et al. Implementation and validation of single-cell genomics experiments in neuroscience. Nat. Neurosci. 27, 2310–2325 (2024).

    CAS 
    PubMed 

    Google Scholar
     

  • Zeng, H. What is a cell type and how to define it? Cell 185, 2739–2755 (2022).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Yao, Z. et al. A high-resolution transcriptomic and spatial atlas of cell types in the whole mouse brain. Nature 624, 317–332 (2023).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Zhang, M. et al. Molecularly defined and spatially resolved cell atlas of the whole mouse brain. Nature 624, 343–354 (2023).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Langlieb, J. et al. The molecular cytoarchitecture of the adult mouse brain. Nature 624, 333–342 (2023).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Liu, H. et al. Single-cell DNA methylome and 3D multi-omic atlas of the adult mouse brain. Nature 624, 366–377 (2023).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Zu, S. et al. Single-cell analysis of chromatin accessibility in the adult mouse brain. Nature 624, 378–389 (2023).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Siletti, K. et al. Transcriptomic diversity of cell types across the adult human brain. Science 382, eadd7046 (2023).

    CAS 
    PubMed 

    Google Scholar
     

  • Bhaduri, A. et al. Outer radial glia-like cancer stem cells contribute to heterogeneity of glioblastoma. Cell Stem Cell 26, 48–63.e6 (2020).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Smith, K. S. et al. Unified rhombic lip origins of group 3 and group 4 medulloblastoma. Nature 609, 1012–1020 (2022).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Li, M. et al. Integrative functional genomic analysis of human brain development and neuropsychiatric risks. Science 362, eaat7615 (2018).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Zhu, Y. et al. Spatiotemporal transcriptomic divergence across human and macaque brain development. Science 362, eaat8077 (2018).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Emani, P. S. et al. Single-cell genomics and regulatory networks for 388 human brains. Science 384, eadi5199 (2024).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Bhaduri, A. et al. An atlas of cortical arealization identifies dynamic molecular signatures. Nature 598, 200–204 (2021).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Nowakowski, T. J. et al. Spatiotemporal gene expression trajectories reveal developmental hierarchies of the human cortex. Science 358, 1318–1323 (2017).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Heffel, M. G. et al. Temporally distinct 3D multi-omic dynamics in the developing human brain. Nature 635, 481–489 (2024).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Velmeshev, D. et al. Single-cell analysis of prenatal and postnatal human cortical development. Science 382, eadf0834 (2023).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Zhu, K. et al. Multi-omic profiling of the developing human cerebral cortex at the single-cell level. Sci. Adv. 9, eadg3754 (2023).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Capauto, D. et al. Characterization of enhancer activity in early human neurodevelopment using Massively Parallel Reporter Assay (MPRA) and forebrain organoids. Sci. Rep. 14, 3936 (2024).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Deng, C. et al. Massively parallel characterization of regulatory elements in the developing human cortex. Science 384, eadh0559 (2024).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Ziffra, R. S. et al. Single-cell epigenomics reveals mechanisms of human cortical development. Nature 598, 205–213 (2021).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Trevino, A. E. et al. Chromatin and gene-regulatory dynamics of the developing human cerebral cortex at single-cell resolution. Cell 184, 5053–5069.e23 (2021).

    CAS 
    PubMed 

    Google Scholar
     

  • Lister, R. et al. Global epigenomic reconfiguration during mammalian brain development. Science 341, 1237905 (2013).

    PubMed 
    PubMed Central 

    Google Scholar
     

  • Calo, E. & Wysocka, J. Modification of enhancer chromatin: what, how, and why? Mol. Cell 49, 825–837 (2013).

    CAS 
    PubMed 

    Google Scholar
     

  • Gao, Y. et al. Continuous cell-type diversification in mouse visual cortex development. Nature https://doi.org/10.1038/s41586-025-09644-1 (2025). This study creates a comprehensive and high-resolution transcriptomic and epigenomic cell type atlas of the developing mouse visual cortex, revealing continuous cell-type diversification throughout the embryonic and postnatal periods.

  • Tasic, B. et al. Shared and distinct transcriptomic cell types across neocortical areas. Nature 563, 72–78 (2018).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Di Bella, D. J. et al. Molecular logic of cellular diversification in the mouse cerebral cortex. Nature 595, 554–559 (2021).

    ADS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Chen, X. et al. Whole-cortex in situ sequencing reveals input-dependent area identity. Nature https://doi.org/10.1038/s41586-024-07221-6 (2024). This study utilizes high-throughput in situ sequencing to reveal broad cell-type compositional changes across the cortex caused by developmental perturbation of visual peripheral inputs.

  • Hawrylycz, M. et al. SEA-AD is a multimodal cellular atlas and resource for Alzheimer’s disease. Nat. Aging 4, 1331–1334 (2024).

    PubMed 
    PubMed Central 

    Google Scholar
     

  • Sohal, V. S. & Rubenstein, J. L. R. Excitation–inhibition balance as a framework for investigating mechanisms in neuropsychiatric disorders. Mol. Psychiatry 24, 1248–1257 (2019).

    PubMed 
    PubMed Central 

    Google Scholar
     

  • Bershteyn, M. et al. Human pallial MGE-type GABAergic interneuron cell therapy for chronic focal epilepsy. Cell Stem Cell 30, 1331–1350.e11 (2023).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • van Velthoven, C. T. J. et al. Transcriptomic and spatial organization of telencephalic GABAergic neurons. Nature https://doi.org/10.1038/s41586-025-09296-1 (2025). This study conducts comprehensive mapping of GABAergic neuron types in the adult and developing telencephalon of mice, revealing rules underlying their transcriptomic, spatial and developmental patterns.

  • Krienen, F. M. et al. Innovations present in the primate interneuron repertoire. Nature 586, 262–269 (2020).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Schmitz, M. T. et al. The development and evolution of inhibitory neurons in primate cerebrum. Nature 603, 871–877 (2022).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Corrigan, E. K. et al. Conservation and alteration of mammalian striatal interneurons. Nature https://doi.org/10.1038/s41586-025-09592-w (2025). This study shows the conservation of TAC3 striatal interneurons with modified gene expression and distribution in evolution, suggesting that brain evolution among mammals occurs through fate refinement of initial classes during development rather than through the generation of entirely novel populations.

  • Andrews, M. G. et al. LIF signaling regulates outer radial glial to interneuron fate during human cortical development. Cell Stem Cell 30, 1382–1391.e5 (2023).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Delgado, R. N. et al. Individual human cortical progenitors can produce excitatory and inhibitory neurons. Nature 601, 397–403 (2022).

    ADS 
    CAS 
    PubMed 

    Google Scholar
     

  • Wang, L. et al. Molecular and cellular dynamics of the developing human neocortex. Nature https://doi.org/10.1038/s41586-024-08351-7 (2025). This study identifies tri-potential intermediate progenitors that generate GABAergic neurons, oligodendrocyte precursors, and astrocytes in the human neocortex, and shows that glioblastoma cells share their transcriptomic features.

  • Wang, R. et al. Adult human glioblastomas harbor radial glia-like cells. Stem Cell Rep. 14, 338–350 (2020).

    ADS 
    CAS 

    Google Scholar
     

  • Keefe, M. G., Steyert, M. R. & Nowakowsk, T. J. Lineage-resolved atlas of the developing human cortex. Nature https://doi.org/10.1038/s41586-025-09033-8 (2025). This study utilizes barcoded lineage tracing to reveal a developmental switch from glutamatergic to GABAergic neurogenesis in the human neocortex.

  • Kostović, I., Judaš, M. & Sedmak, G. Developmental history of the subplate zone, subplate neurons and interstitial white matter neurons: relevance for schizophrenia. Int. J. Dev. Neurosci. 29, 193–205 (2011).

    PubMed 

    Google Scholar
     

  • Kubo, K.-I. Increased densities of white matter neurons as a cross-disease feature of neuropsychiatric disorders. Psychiatry Clin. Neurosci. 74, 166–175 (2020).

    PubMed 

    Google Scholar
     

  • Zhang, D. et al. Spatial dynamics of brain development and neuroinflammation. Nature https://doi.org/10.1038/s41586-025-09663-y (2025). This study applies spatial tri-omics mapping to characterize cellular and regulatory dynamics in the developing mouse brain and in a neuroinflammatory mouse model, revealing a spatiotemporal relationship between axonogenesis and myelination, as well as distal microglia activation in focal demyelination.

  • Mannens, C. C. A. et al. Chromatin accessibility during human first-trimester neurodevelopment. Nature https://doi.org/10.1038/s41586-024-07234-1 (2024). This study details epigenomic characterization of human brain development during the first trimester, using epigenomic signatures to decipher transcriptional modules of regionalization and cell fate specification.

  • Nano, P. R. et al. Integrated analysis of molecular atlases unveils modules driving developmental cell subtype specification in the human cortex. Nat. Neurosci. 28, 949–963 (2025). This study defines a meta-atlas of human brain development using integrative computational analysis of multiple datasets and identifies TSHZ3 as a driver of cortical layer 5 specification.

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Kaplan, H. S. et al. Sensory input, sex and function shape hypothalamic cell type development. Nature https://doi.org/10.1038/s41586-025-08603-0 (2025). This study characterizes the development of cell types in the hypothalamic preoptic area that are involved in the regulation of sex-specific social behaviours, revealing that social experience can shape the development of these cell types.

  • Kronman, F. N. et al. Developmental mouse brain common coordinate framework. Nat. Commun. 15, 9072 (2024). This study creates a comprehensive common coordinate framework for the mouse brain across developmental stages and maps the origin and redistribution of non-neuronal cells across development.

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Jayakumar, J. et al. A three-dimensional histological cell atlas of the developing human brain. Preprint at bioRxiv https://doi.org/10.1101/2024.12.17.628811 (2024). This study reports the first comprehensive histological atlas of human brain development across key developmental stages, using complete intact tissue specimens.

  • Sonthalia, S. et al. A curated compendium of transcriptomic data for the exploration of neocortical development. Preprint at bioRxiv https://doi.org/10.1101/2024.02.26.581612 (2024). This study curates public multi-omics data focused on neocortical development in an open data exploration environment and jointly decomposes these datasets to define the developmental emergence of primate-specific and conserved transcriptomic features, in addition to mapping which of these are recapitulated in organoid models.

  • La Manno, G. et al. Molecular architecture of the developing mouse brain. Nature 596, 92–96 (2021).

    ADS 
    PubMed 

    Google Scholar
     

  • Micali, N. et al. Molecular programs of regional specification and neural stem cell fate progression in macaque telencephalon. Science 382, eadf3786 (2023).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Bakken, T. E. et al. Comparative cellular analysis of motor cortex in human, marmoset and mouse. Nature 598, 111–119 (2021).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Jorstad, N. L. et al. Transcriptomic cytoarchitecture reveals principles of human neocortex organization. Science 382, eadf6812 (2023).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Shibata, M. et al. Regulation of prefrontal patterning and connectivity by retinoic acid. Nature 598, 483–488 (2021).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Shibata, M. et al. Hominini-specific regulation of CBLN2 increases prefrontal spinogenesis. Nature 598, 489–494 (2021).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Ma, S. et al. Molecular and cellular evolution of the primate dorsolateral prefrontal cortex. Science 377, eabo7257 (2022).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Franjic, D. et al. Transcriptomic taxonomy and neurogenic trajectories of adult human, macaque, and pig hippocampal and entorhinal cells. Neuron 110, 452–469.e14 (2022).

    CAS 
    PubMed 

    Google Scholar
     

  • Liu, Y. et al. Comparative single-cell multiome identifies evolutionary changes in neural progenitor cells during primate brain development. Dev. Cell 60, 414–428.e8 (2025).

    CAS 
    PubMed 

    Google Scholar
     

  • Zhao, Z. et al. Evolutionarily conservative and non-conservative regulatory networks during primate interneuron development revealed by single-cell RNA and ATAC sequencing. Cell Res. 32, 425–436 (2022).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Adameyko, I. et al. Applying single-cell and single-nucleus genomics to studies of cellular heterogeneity and cell fate transitions in the nervous system. Nat. Neurosci. 27, 2278–2291 (2024).

    CAS 
    PubMed 

    Google Scholar
     

  • Schlegel, P. et al. Whole-brain annotation and multi-connectome cell typing of Drosophila. Nature 634, 139–152 (2024).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Schneider-Mizell, C. M. et al. Inhibitory specificity from a connectomic census of mouse visual cortex. Nature 640, 448–458 (2025).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Gamlin, C. R. et al. Connectomics of predicted Sst transcriptomic types in mouse visual cortex. Nature 640, 497–505 (2025).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Zhou, J. et al. Brain-wide correspondence of neuronal epigenomics and distant projections. Nature 624, 355–365 (2023).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Peng, H. et al. Morphological diversity of single neurons in molecularly defined cell types. Nature 598, 174–181 (2021).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Foster, N. N. et al. The mouse cortico-basal ganglia-thalamic network. Nature 598, 188–194 (2021).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Nagy, C. et al. Single-nucleus transcriptomics of the prefrontal cortex in major depressive disorder implicates oligodendrocyte precursor cells and excitatory neurons. Nat. Neurosci. 23, 771–781 (2020).

    CAS 
    PubMed 

    Google Scholar
     

  • Pfisterer, U. et al. Identification of epilepsy-associated neuronal subtypes and gene expression underlying epileptogenesis. Nat. Commun. 11, 5038 (2020).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Gandal, M. J. et al. Broad transcriptomic dysregulation occurs across the cerebral cortex in ASD. Nature 611, 532–539 (2022).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Bhaduri, A. et al. Cell stress in cortical organoids impairs molecular subtype specification. Nature 578, 142–148 (2020).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Velasco, S. et al. Individual brain organoids reproducibly form cell diversity of the human cerebral cortex. Nature 570, 523–527 (2019).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • López-Tobón, A. et al. Human cortical organoids expose a differential function of GSK3 on cortical neurogenesis. Stem Cell Rep. 13, 847–861 (2019).


    Google Scholar
     

  • Mansour, A. A. et al. An in vivo model of functional and vascularized human brain organoids. Nat. Biotechnol. 36, 432–441 (2018).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Giandomenico, S. L. et al. Cerebral organoids at the air-liquid interface generate diverse nerve tracts with functional output. Nat. Neurosci. 22, 669–679 (2019).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Cakir, B. et al. Engineering of human brain organoids with a functional vascular-like system. Nat. Methods 16, 1169–1175 (2019).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Pașca, S. P. et al. A framework for neural organoids, assembloids and transplantation studies. Nature 639, 315–320 (2025).

    ADS 
    PubMed 

    Google Scholar
     

  • Werner, J. M. & Gillis, J. Meta-analysis of single-cell RNA sequencing co-expression in human neural organoids reveals their high variability in recapitulating primary tissue. PLoS Biol. 22, e3002912 (2024). This study presents a comprehensive data framework for evaluating the fidelity of in vitroderived brain organoids benchmarked against the ground truth of primary developing brain tissue.

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Ament, S. A. et al. A single-cell genomic atlas for maturation of the human cerebellum during early childhood. Sci. Transl. Med. 15, eade1283 (2023).

    CAS 
    PubMed 

    Google Scholar
     

  • Kamimoto, K. et al. Dissecting cell identity via network inference and in silico gene perturbation. Nature 614, 742–751 (2023).

    ADS 
    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Roohani, Y., Huang, K. & Leskovec, J. Predicting transcriptional outcomes of novel multigene perturbations with GEARS. Nat. Biotechnol. 42, 927–935 (2024).

    CAS 
    PubMed 

    Google Scholar
     

  • Bock, C. et al. High-content CRISPR screening. Nat. Rev. Methods Primers 2, 9 (2022).

    PubMed 
    PubMed Central 

    Google Scholar
     

  • Dixit, A. et al. Perturb-seq: dissecting molecular circuits with scalable single-cell RNA profiling of pooled genetic screens. Cell 167, 1853–1866.e17 (2016).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Adamson, B. et al. A multiplexed single-cell CRISPR screening platform enables systematic dissection of the unfolded protein response. Cell 167, 1867–1882.e21 (2016).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Jaitin, D. A. et al. Dissecting immune circuits by linking CRISPR-pooled screens with single-cell RNA-seq. Cell 167, 1883–1896.e15 (2016).

    CAS 
    PubMed 

    Google Scholar
     

  • Fleck, J. S. et al. Resolving organoid brain region identities by mapping single-cell genomic data to reference atlases. Cell Stem Cell 28, 1148–1159.e8 (2021).

    CAS 
    PubMed 

    Google Scholar
     

  • Jin, X. et al. In vivo Perturb-Seq reveals neuronal and glial abnormalities associated with autism risk genes. Science 370, eaaz6063 (2020).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Tasic, B. & Fishell, G. Exploring brain circuits, one cell type-or more- at a time. Neuron 113, 1469–1473 (2025).

    CAS 
    PubMed 

    Google Scholar
     

  • Bashor, C. J., Hilton, I. B., Bandukwala, H., Smith, D. M. & Veiseh, O. Engineering the next generation of cell-based therapeutics. Nat. Rev. Drug Discov. 21, 655–675 (2022).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Bose, A., Petsko, G. A. & Studer, L. Induced pluripotent stem cells: a tool for modeling Parkinson’s disease. Trends Neurosci. 45, 608–620 (2022).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Lin, H.-C. et al. Human neuron subtype programming via single-cell transcriptome-coupled patterning screens. Science 389, eadn6121 (2025).

    ADS 
    CAS 
    PubMed 

    Google Scholar
     

  • Rood, J. E. et al. The Human Cell Atlas from a cell census to a unified foundation model. Nature 637, 1065–1071 (2025).

    ADS 
    CAS 
    PubMed 

    Google Scholar
     

  • Brust, V., Schindler, P. M. & Lewejohann, L. Lifetime development of behavioural phenotype in the house mouse (Mus musculus). Front. Zool. 12, S17 (2015).

    PubMed 
    PubMed Central 

    Google Scholar
     

  • de Castro Leão, A., Duarte Dória Neto, A. & de Sousa, M. B. C. New developmental stages for common marmosets (Callithrix jacchus) using mass and age variables obtained by K-means algorithm and self-organizing maps (SOM). Comput. Biol. Med. 39, 853–859 (2009).

    PubMed 

    Google Scholar
     

  • Walker, M. L. & Herndon, J. G. Menopause in nonhuman primates? Biol. Reprod. 79, 398–406 (2008).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • Clancy, B., Darlington, R. B. & Finlay, B. L. Translating developmental time across mammalian species. Neuroscience 105, 7–17 (2001).

    CAS 
    PubMed 

    Google Scholar
     

  • Workman, A. D., Charvet, C. J., Clancy, B., Darlington, R. B. & Finlay, B. L. Modeling transformations of neurodevelopmental sequences across mammalian species. J. Neurosci. 33, 7368–7383 (2013).

    CAS 
    PubMed 
    PubMed Central 

    Google Scholar
     

  • RELATED ARTICLES

    Most Popular

    Recent Comments