The cerebral cortex is the source of our most complex cognitive capabilities and a vulnerable target of many neurological and neuropsychiatric disorders. Transcriptomics offers a new approach to understanding the cortex at the level of its underlying genetic code, and rapid technological advances have propelled this field to the high-throughput study of the complete set of transcribed genes at increasingly fine resolution to the level of individual cells. These tools have revealed features of the genetic architecture of adult cortical areas, layers, and cell types, as well as spatiotemporal patterning during development. This has allowed a fresh look at comparative anatomy as well, illustrating surprisingly large differences between mammals while at the same time revealing conservation of some features from avians to mammals. Finally, transcriptomics is fueling progress in understanding the causes of neurodevelopmental diseases such as autism, linking genetic association studies to specific molecular pathways and affected brain regions.


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Literature Cited

  1. Aboitiz F, Montiel J. 2007. Origin and evolution of the vertebrate telencephalon, with special reference to the mammalian neocortex. Advances in Anatomy, Embryology and Cell Biology 193 FF Beck, F Clascá, M Frotscher, DE Haines, HW Korf et al.1–112 Berlin: Springer [Google Scholar]
  2. Amunts K, Armstrong E, Malikovic A, Hömke L, Mohlberg H. et al. 2007a. Gender-specific left-right asymmetries in human visual cortex. J. Neurosci. 27:61356–64 [Google Scholar]
  3. Amunts K, Lepage C, Borgeat L, Mohlberg H, Dickscheid T. et al. 2013. BigBrain: an ultrahigh-resolution 3D human brain model. Science 340:61391472–75 [Google Scholar]
  4. Amunts K, Schleicher A, Zilles K. 2007b. Cytoarchitecture of the cerebral cortex—more than localization. NeuroImage 37:1061–65 [Google Scholar]
  5. Arendt D, Musser JM, Baker CV, Bergman A, Cepko C. et al. 2016. The origin and evolution of cell types. Nat. Rev. Genet. 17:744–57 [Google Scholar]
  6. Arlotta P, Molyneaux BJ, Chen J, Inoue J, Kominami R, Macklis JD. 2005. Neuronal subtype-specific genes that control corticospinal motor neuron development in vivo. Neuron 45:207–21 [Google Scholar]
  7. Audinat E, Lambolez B, Rossier J. 1996. Functional and molecular analysis of glutamate-gated channels by patch-clamp and RT-PCR at the single cell level. Neurochem. Int. 28:119–36 [Google Scholar]
  8. Ayoub AE, Oh S, Xie Y, Leng J, Cotney J. et al. 2011. Transcriptional programs in transient embryonic zones of the cerebral cortex defined by high-resolution mRNA sequencing. PNAS 108:14950–55 [Google Scholar]
  9. Bakken TE, Miller JA, Ding SL, Sunkin SM, Smith KA. et al. 2016. A comprehensive transcriptional map of primate brain development. Nature 535:367–75 [Google Scholar]
  10. Balaram P, Young NA, Kaas JH. 2014. Histological features of layers and sublayers in cortical visual areas V1 and V2 of chimpanzees, macaque monkeys, and humans. Eye Brain 2014:5–18 [Google Scholar]
  11. Belgard TG, Marques AC, Oliver PL, Abaan HO, Sirey TM. et al. 2011. A transcriptomic atlas of mouse neocortical layers. Neuron 71:605–16 [Google Scholar]
  12. Belgard TG, Montiel JF. 2013. Things change: how comparative transcriptomics suggest the pallium has evolved at multiple levels of organization. Brain Behav. Evol. 82:150–52 [Google Scholar]
  13. Belgard TG, Montiel JF, Wang WZ, García-Moreno F, Margulies EH. et al. 2013. Adult pallium transcriptomes surprise in not reflecting predicted homologies across diverse chicken and mouse pallial sectors. PNAS 110:13150–55 [Google Scholar]
  14. Bernard A, Lubbers LS, Tanis KQ, Luo R, Podtelezhnikov AA. et al. 2012. Transcriptional architecture of the primate neocortex. Neuron 73:1083–99 [Google Scholar]
  15. Borges-Monroy R, Ponting CP, Belgard TG. 2015. Elevated gene expression of most microglial markers, and reduced expression of most pyramidal neuron and interneuron markers, in postmortem autism cortex. bioRxiv 032557. https://doi.org/10.1101/032557 [Crossref]
  16. Brodmann K. 1909. Localisation in the Cerebral Cortex London: Smith-Gordon [Google Scholar]
  17. Butler AB, Hodos W. 2005. Comparative Vertebrate Neuroanatomy: Evolution and Adaptation Hoboken, NJ: Wiley-Interscience [Google Scholar]
  18. Cadwell CR, Palasantza A, Jiang X, Berens P, Deng Q. et al. 2016. Electrophysiological, transcriptomic and morphologic profiling of single neurons using Patch-seq. Nat. Biotechnol. 34:199–203 [Google Scholar]
  19. Casagrande VA, Kaas JH. 1994. The afferent, intrinsic, and efferent connections of primary visual cortex in primates. Primary Visual Cortex of Primates A Peters, K Rockland 201–59 New York: Plenum Press [Google Scholar]
  20. Cauli B, Audinat E, Lambolez B, Angulo MC, Ropert N. et al. 1997. Molecular and physiological diversity of cortical nonpyramidal cells. J. Neurosci. 17:3894–906 [Google Scholar]
  21. Chen JC, Alvarez MJ, Talos F, Dhruv H, Rieckhof GE. et al. 2016. Identification of causal genetic drivers of human disease through systems-level analysis of regulatory networks. Cell 155:402–14 [Google Scholar]
  22. Chow ML, Pramparo T, Winn ME, Barnes CC, Li HR. et al. 2012. Age-dependent brain gene expression and copy number anomalies in autism suggest distinct pathological processes at young versus mature ages. PLOS Genet 8:e1002592 [Google Scholar]
  23. Clowry G, Molnár Z, Rakic P. 2010. Renewed focus on the developing human neocortex. J. Anat. 217:276–88 [Google Scholar]
  24. Colantuoni C, Lipska BK, Ye T, Hyde TM, Tao R. et al. 2011. Temporal dynamics and genetic control of transcription in the human prefrontal cortex. Nature 478:519–23 [Google Scholar]
  25. Darmanis S, Sloan SA, Zhang Y, Enge M, Caneda C. et al. 2015. A survey of human brain transcriptome diversity at the single cell level. PNAS 112:7285–90 [Google Scholar]
  26. DeFelipe J. 1993. Neocortical neuronal diversity: chemical heterogeneity revealed by colocalization studies of classic neurotransmitters, neuropeptides, calcium-binding proteins, and cell surface molecules. Cereb. Cortex 3:273–89 [Google Scholar]
  27. Doyle JP, Dougherty JD, Heiman M, Schmidt EF, Stevens TR. et al. 2008. Application of a translational profiling approach for the comparative analysis of CNS cell types. Cell 135:749–62 [Google Scholar]
  28. Dugas-Ford J, Rowell JJ, Ragsdale CW. 2012. Cell-type homologies and the origins of the neocortex. PNAS 109:16974–79 [Google Scholar]
  29. Duque A, Krsnik Z, Kostovic I, Rakic P. 2016. Secondary expansion of the transient subplate zone in the developing cerebrum of human and nonhuman primates. PNAS 113:9892–97 [Google Scholar]
  30. Fan L, Li H, Zhuo J, Zhang Y, Wang J. et al. 2016. The human Brainnetome Atlas: a new brain atlas based on connectional architecture. Cereb. Cortex 26:3508–26 [Google Scholar]
  31. Fietz SA, Lachmann R, Brandl H, Kircher M, Samusik N. et al. 2012. Transcriptomes of germinal zones of human and mouse fetal neocortex suggest a role of extracellular matrix in progenitor self-renewal. PNAS 109:11836–41 [Google Scholar]
  32. French L, Pavlidis P. 2011. Relationships between gene expression and brain wiring in the adult rodent brain. PLOS Comput. Biol. 7:e1001049 [Google Scholar]
  33. Fuzik J, Zeisel A, Mate Z, Calvigioni D, Yanagawa Y. et al. 2016. Integration of electrophysiological recordings with single-cell RNA-seq data identifies neuronal subtypes. Nat. Biotechnol. 34:175–83 [Google Scholar]
  34. García-Moreno F, Vasistha NA, Trevia N, Bourne JA, Molnár Z. 2012. Compartmentalization of cerebral cortical germinal zones in a lissencephalic primate and gyrencephalic rodent. Cereb. Cortex 22:482–92 [Google Scholar]
  35. Geschwind DH, Rakic P. 2013. Cortical evolution: Judge the brain by its cover. Neuron 80:633–47 [Google Scholar]
  36. Glasser MF, Coalson TS, Robinson EC, Hacker CD, Harwell J. et al. 2016. A multi-modal parcellation of human cerebral cortex. Nature 536:171–78 [Google Scholar]
  37. Grange P, Bohland JW, Okaty BW, Sugino K, Bokil H. et al. 2014. Cell-type-based model explaining coexpression patterns of genes in the brain. PNAS 111:5397–402 [Google Scholar]
  38. Gupta S, Ellis SE, Ashar FN, Moes A, Bader JS. et al. 2014. Transcriptome analysis reveals dysregulation of innate immune response genes and neuronal activity-dependent genes in autism. Nat. Commun. 5:5748 [Google Scholar]
  39. Han X, Chen M, Wang F, Windrem M, Wang S. et al. 2013. Forebrain engraftment by human glial progenitor cells enhances synaptic plasticity and learning in adult mice. Cell Stem Cell 12:342–53 [Google Scholar]
  40. Hansen DV, Lui JH, Parker PR, Kriegstein AR. 2010. Neurogenic radial glia in the outer subventricular zone of human neocortex. Nature 464:554–61 [Google Scholar]
  41. Hassler RG, Stephan H. 1966. Evolution of the Forebrain: Phylogenesis and Ontogenesis of the Forebrain Stuttgart, Ger.: Thieme Verlag [Google Scholar]
  42. Hawrylycz MJ, Lein ES, Guillozet-Bongaarts AL, Shen EH, Ng L. et al. 2012. An anatomically comprehensive atlas of the adult human brain transcriptome. Nature 489:391–99 [Google Scholar]
  43. Hawrylycz MJ, Miller JA, Menon V, Feng D, Dolbeare T. et al. 2015. Canonical genetic signatures of the adult human brain. Nat. Neurosci. 18:1832–44 [Google Scholar]
  44. Hoerder-Suabedissen A, Molnár Z. 2015. Development, evolution and pathology of neocortical subplate neurons. Nat. Rev. Neurosci. 16:133–46 [Google Scholar]
  45. Hoerder-Suabedissen A, Oeschger FM, Krishnan ML, Belgard TG, Wang WZ. et al. 2013. Expression profiling of mouse subplate reveals a dynamic gene network and disease association with autism and schizophrenia. PNAS 110:3555–60 [Google Scholar]
  46. Hoerder-Suabedissen A, Wang WZ, Lee S, Davies KE, Goffinet AM. et al. 2009. Novel markers reveal subpopulations of subplate neurons in the murine cerebral cortex. Cereb. Cortex 19:1738–50 [Google Scholar]
  47. Holmgren N. 1922. Points of view concerning forebrain morphology in lower vertebrates. J. Comp. Neurol. 34:391–459 [Google Scholar]
  48. Irimia M, Weatheritt RJ, Ellis JD, Parikshak NN, Gonatopoulos-Pournatzis T. et al. 2014. A highly conserved program of neuronal microexons is misregulated in autistic brains. Cell 159:1511–23 [Google Scholar]
  49. Jarvis ED, Gunturkun O, Bruce L, Csillag A, Karten H. et al. 2005. Avian brains and a new understanding of vertebrate brain evolution. Nat. Rev. Neurosci. 6:151–59 [Google Scholar]
  50. Jarvis ED, Yu J, Rivas MV, Horita H, Feenders G. et al. 2013. Global view of the functional molecular organization of the avian cerebrum: mirror images and functional columns. J. Comp. Neurol. 521:3614–65 [Google Scholar]
  51. Jockwitz C, Caspers S, Lux S, Jütten K, Schleicher A. et al. 2016. Age- and function-related regional changes in cortical folding of the default mode network in older adults. Brain Struct. Funct. 222:83–99 [Google Scholar]
  52. Johnson MB, Kawasawa YI, Mason CE, Krsnik Z, Coppola G. et al. 2009. Functional and evolutionary insights into human brain development through global transcriptome analysis. Neuron 62:494–509 [Google Scholar]
  53. Johnson MR, Shkura K, Langley SR, Delahaye-Duriez A, Srivastava P. et al. 2016. Systems genetics identifies a convergent gene network for cognition and neurodevelopmental disease. Nat. Neurosci. 19:223–32 [Google Scholar]
  54. Johnston JB. 1923. Further contributions to the study of the evolution of the forebrain. J. Comp. Neurol. 35:337–481 [Google Scholar]
  55. Kaas JH. 2007. Evolution of Nervous Systems: A Comprehensive Reference Amsterdam/Boston: Elsevier Acad. [Google Scholar]
  56. Kang HJ, Kawasawa YI, Cheng F, Zhu Y, Xu X. et al. 2011. Spatio-temporal transcriptome of the human brain. Nature 478:483–89 [Google Scholar]
  57. Karten HJ. 1997. Evolutionary developmental biology meets the brain: the origins of mammalian cortex. PNAS 94:2800–4 [Google Scholar]
  58. Karten HJ. 2013. Neocortical evolution: Neuronal circuits arise independently of lamination. Curr. Biol. 23:R12–15 [Google Scholar]
  59. Karten HJ. 2015. Vertebrate brains and evolutionary connectomics: on the origins of the mammalian ‘neocortex’. Philos. Trans. R. Soc. B 370:20150060 [Google Scholar]
  60. Kelava I, Reillo I, Murayama AY, Kalinka AT, Stenzel D. et al. 2012. Abundant occurrence of basal radial glia in the subventricular zone of embryonic neocortex of a lissencephalic primate, the common marmoset Callithrix jacchus. Cereb. Cortex 22:469–81 [Google Scholar]
  61. Khaladkar M, Buckley PT, Lee MT, Francis C, Eghbal MM. et al. 2013. Subcellular RNA sequencing reveals broad presence of cytoplasmic intron-sequence retaining transcripts in mouse and rat neurons. PLOS ONE 8:e76194 [Google Scholar]
  62. Konopka G, Friedrich T, Davis-Turak J, Winden K, Oldham MC. et al. 2012. Human-specific transcriptional networks in the brain. Neuron 75:601–17 [Google Scholar]
  63. Kostovic I, Rakic P. 1990. Developmental history of the transient subplate zone in the visual and somatosensory cortex of the macaque monkey and human brain. J. Comp. Neurol. 297:441–70 [Google Scholar]
  64. Kriegstein A, Noctor S, Martínez-Cerdeño V. 2006. Patterns of neural stem and progenitor cell division may underlie evolutionary cortical expansion. Nat. Rev. Neurosci. 7:883–90 [Google Scholar]
  65. Krishnan A, Zhang R, Yao V, Theesfeld CL, Wong AK. et al. 2016. Genome-wide prediction and functional characterization of the genetic basis of autism spectrum disorder. Nat. Neurosci. 19:1454–62 [Google Scholar]
  66. Krishnaswami SR, Grindberg RV, Novotny M, Venepally P, Lacar B. et al. 2016. Using single nuclei for RNA-seq to capture the transcriptome of postmortem neurons. Nat. Protoc. 11:499–524 [Google Scholar]
  67. Lacar B, Linker SB, Jaeger BN, Krishnaswami S, Barron J. et al. 2016. Nuclear RNA-seq of single neurons reveals molecular signatures of activation. Nat. Commun. 7:11022 [Google Scholar]
  68. Lake BB, Ai R, Kaeser GE, Salathia NS, Yung YC. et al. 2016. Neuronal subtypes and diversity revealed by single-nucleus RNA sequencing of the human brain. Science 352:1586–90 [Google Scholar]
  69. Lee JH, Daugharthy ER, Scheiman J, Kalhor R, Yang JL. et al. 2014. Highly multiplexed subcellular RNA sequencing in situ. Science 343:1360–63 [Google Scholar]
  70. Lein ES, Hawrylycz MJ, Ao N, Ayres M, Bensinger A. et al. 2007. Genome-wide atlas of gene expression in the adult mouse brain. Nature 445:168–76 [Google Scholar]
  71. Lent R, Azevedo FAC, Andrade-Moraes CH, Pinto AVO. 2012. How many neurons do you have? Some dogmas of quantitative neuroscience under revision. Eur. J. Neurosci. 35:1–9 [Google Scholar]
  72. Liu X, Han D, Somel M, Jiang X, Hu H. et al. 2016. Disruption of an evolutionarily novel synaptic expression pattern in autism. PLOS Biol 14:e1002558 [Google Scholar]
  73. Louveau A, Smirnov I, Keyes TJ, Eccles JD, Rouhani SJ. et al. 2015. Structural and functional features of central nervous system lymphatic vessels. Nature 523:337–41 [Google Scholar]
  74. Macosko EZ, Basu A, Satija R, Nemesh J, Shekhar K. et al. 2015. Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Cell 161:1202–14 [Google Scholar]
  75. Markram H, Toledo-Rodriguez M, Wang Y, Gupta A, Silberberg G, Wu C. 2004. Interneurons of the neocortical inhibitory system. Nat. Rev. 5:793–807 [Google Scholar]
  76. Marques S, Zeisel A, Codeluppi S, van Bruggen D, Mendanha Falcão A. et al. 2016. Oligodendrocyte heterogeneity in the mouse juvenile and adult central nervous system. Science 352:1326–29 [Google Scholar]
  77. Medina L, Reiner A. 2000. Do birds possess homologues of mammalian primary visual, somatosensory and motor cortices?. Trends Neurosci 23:1–12 [Google Scholar]
  78. Miller JA, Ding SL, Sunkin SM, Smith KA, Ng L. et al. 2014. Transcriptional landscape of the prenatal human brain. Nature 508:199–206 [Google Scholar]
  79. Molnár Z. 2013. Cortical columns. Comprehensive Developmental Neuroscience: Neural Circuit Development and Function in the Healthy and Diseased Brain 3 JLR Rubenstein, P Rakic 109–29 San Diego: Elsevier [Google Scholar]
  80. Molnár Z, Butler AB. 2002. The corticostriatal junction: a crucial region for forebrain development and evolution. BioEssays 24:530–41 [Google Scholar]
  81. Molyneaux BJ, Arlotta P, Hirata T, Hibi M, Macklis JD. 2005. Fezl is required for the birth and specification of corticospinal motor neurons. Neuron 47:817–31 [Google Scholar]
  82. Montiel JF, Molnár Z. 2013. The impact of gene expression analysis on evolving views of avian brain organization. J. Comp. Neurol. 521:3604–13 [Google Scholar]
  83. Montiel JF, Wang WZ, Oeschger FM, Hoerder-Suabedissen A, Tung WL. et al. 2011. Hypothesis on the dual origin of the mammalian subplate. Front. Neuroanat. 5:25 [Google Scholar]
  84. Montiel JF, Vasistha NA, García-Moreno F, Molnár Z. 2016. From sauropsids to mammals and back: new approaches to comparative cortical development. J. Comp. Neurol. 524:3630–45 [Google Scholar]
  85. Mountcastle VB. 1997. The columnar organization of the neocortex. Brain 120:Pt. 4701–22 [Google Scholar]
  86. Northcutt RG, Kaas JH. 1995. The emergence and evolution of mammalian neocortex. Trends Neurosci 18:373–79 [Google Scholar]
  87. Oberheim NA, Takano T, Han X, He W, Lin JH. et al. 2009. Uniquely hominid features of adult human astrocytes. J. Neurosci. 29:3276–87 [Google Scholar]
  88. Oeschger FM, Wang WZ, Lee S, García-Moreno F, Goffinet AM. et al. 2012. Gene expression analysis of the embryonic subplate. Cereb. Cortex 22:1343–59 [Google Scholar]
  89. Oldham MC, Konopka G, Iwamoto K, Langfelder P, Kato T. et al. 2008. Functional organization of the transcriptome in human brain. Nat. Neurosci. 11:1271–82 [Google Scholar]
  90. Parikshak NN, Luo R, Zhang A, Won H, Lowe JK. et al. 2013. Integrative functional genomic analyses implicate specific molecular pathways and circuits in autism. Cell 155:1008–21 [Google Scholar]
  91. Parikshak NN, Swarup V, Belgard TG, Irimia M, Ramaswami G. et al. 2016. Genome-wide changes in lncRNA, splicing, and regional gene expression patterns in autism. Nature 540:423–27 [Google Scholar]
  92. Pollen AA, Nowakowski TJ, Chen J, Retallack H, Sandoval-Espinosa C. et al. 2015. Molecular identity of human outer radial glia during cortical development. Cell 163:55–67 [Google Scholar]
  93. Pollen AA, Nowakowski TJ, Shuga J, Wang X, Leyrat AA. et al. 2014. Low-coverage single-cell mRNA sequencing reveals cellular heterogeneity and activated signaling pathways in developing cerebral cortex. Nat. Biotechnol. 32:1053–58 [Google Scholar]
  94. Pouchelon G, Gambino F, Bellone C, Telley L, Vitali I. et al. 2014. Modality-specific thalamocortical inputs instruct the identity of postsynaptic L4 neurons. Nature 511:471–74 [Google Scholar]
  95. Prabhakar S, Noonan JP, Pääbo S, Rubin EM. 2006. Accelerated evolution of conserved noncoding sequences in humans. Science 314:786 [Google Scholar]
  96. Prufer K, Racimo F, Patterson N, Jay F, Sankararaman S. et al. 2014. The complete genome sequence of a Neanderthal from the Altai Mountains. Nature 505:43–49 [Google Scholar]
  97. Puelles L. 2001. Thoughts on the development, structure and evolution of the mammalian and avian telencephalic pallium. Philos. Trans. R. Soc. B 356:1583–98 [Google Scholar]
  98. Rakic P, Bourgeois JP, Eckenhoff MF, Zecevic N, Goldman-Rakic PS. 1986. Concurrent overproduction of synapses in diverse regions of the primate cerebral cortex. Science 232:232–35 [Google Scholar]
  99. Reillo I, de Juan Romero C, García-Cabezas MA, Borrell V. 2011. A role for intermediate radial glia in the tangential expansion of the mammalian cerebral cortex. Cereb. Cortex 21:1674–94 [Google Scholar]
  100. Richiardi J, Altmann A, Milazzo AC, Chang C, Chakravarty MM. et al. 2015. Correlated gene expression supports synchronous activity in brain networks. Science 348:1241–44 [Google Scholar]
  101. Rubenstein JLR, Rakic P. 2013. Comprehensive Developmental Neuroscience: Patterning and Cell Type Specification in the Developing CNS and PNS San Diego: Elsevier [Google Scholar]
  102. Sankararaman S, Patterson N, Li H, Pääbo S, Reich D. 2012. The date of interbreeding between Neandertals and modern humans. PLOS Genet 8:e1002947 [Google Scholar]
  103. Sansom SN, Livesey FJ. 2009. Gradients in the brain: the control of the development of form and function in the cerebral cortex. Cold Spring Harb. Perspect. Biol. 1:a002519 [Google Scholar]
  104. Smart IH, Dehay C, Giroud P, Berland M, Kennedy H. 2002. Unique morphological features of the proliferative zones and postmitotic compartments of the neural epithelium giving rise to striate and extrastriate cortex in the monkey. Cereb. Cortex 12:37–53 [Google Scholar]
  105. Smith GE. 1919. A preliminary note on the morphology of the corpus striatum and the origin of the neopallium. J. Anat. 53:271–91 [Google Scholar]
  106. Sugino K, Hempel CM, Miller MN, Hattox AM, Shapiro P. et al. 2006. Molecular taxonomy of major neuronal classes in the adult mouse forebrain. Nat. Neurosci. 9:99–107 [Google Scholar]
  107. Sun W, Poschmann J, Cruz-Herrera Del Rosario R, Parikshak NN, Hajan HS. et al. 2016. Histone acetylome-wide association study of autism spectrum disorder. Cell 167:1385–97.e11 [Google Scholar]
  108. Suzuki IK, Kawasaki T, Gojobori T, Hirata T. 2012. The temporal sequence of the mammalian neocortical neurogenetic program drives mediolateral pattern in the chick pallium. Dev. Cell 22:863–70 [Google Scholar]
  109. Tasic B, Menon V, Nguyen TN, Kim TK, Jarsky T. et al. 2016. Adult mouse cortical cell taxonomy revealed by single cell transcriptomics. Nat. Neurosci. 19:335–46 [Google Scholar]
  110. Thompson CL, Ng L, Menon V, Martinez S, Lee CK. et al. 2014. A high-resolution spatiotemporal atlas of gene expression of the developing mouse brain. Neuron 83:309–23 [Google Scholar]
  111. Thompson CL, Pathak SD, Jeromin A, Ng LL, MacPherson CR. et al. 2008. Genomic anatomy of the hippocampus. Neuron 60:1010–21 [Google Scholar]
  112. Thomsen ER, Mich JK, Yao Z, Hodge RD, Doyle AM. et al. 2016. Fixed single-cell transcriptomic characterization of human radial glial diversity. Nat. Methods 13:87–93 [Google Scholar]
  113. Toledo-Rodriguez M, Blumenfeld B, Wu C, Luo J, Attali B. et al. 2004. Correlation maps allow neuronal electrical properties to be predicted from single-cell gene expression profiles in rat neocortex. Cereb. Cortex 14:1310–27 [Google Scholar]
  114. Voineagu I, Wang X, Johnston P, Lowe JK, Tian Y. et al. 2011. Transcriptomic analysis of autistic brain reveals convergent molecular pathology. Nature 474:380–84 [Google Scholar]
  115. Wang GZ, Belgard TG, Mao D, Chen L, Berto S. et al. 2015. Correspondence between resting-state activity and brain gene expression. Neuron 88:659–66 [Google Scholar]
  116. Wang WZ, Oeschger FM, Montiel JF, García-Moreno F, Hoerder-Suabedissen A. et al. 2011. Comparative aspects of subplate zone studied with gene expression in sauropsids and mammals. Cereb. Cortex 21:2187–203 [Google Scholar]
  117. Washington SD, Gordon EM, Brar J, Warburton S, Sawyer AT. et al. 2014. Dysmaturation of the default mode network in autism. Hum. Brain Mapp. 35:1284–96 [Google Scholar]
  118. Willsey AJ, Sanders SJ, Li M, Dong S, Tebbenkamp AT. et al. 2013. Coexpression networks implicate human midfetal deep cortical projection neurons in the pathogenesis of autism. Cell 155:997–1007 [Google Scholar]
  119. Wu YE, Parikshak NN, Belgard TG, Geschwind DH. 2016. Genome-wide, integrative analysis implicates microRNA dysregulation in autism spectrum disorder. Nat. Neurosci. 19:111463–76 [Google Scholar]
  120. Zeisel A, Muñoz-Manchado AB, Codeluppi S, Lönnerberg P, La Manno G. et al. 2015. Brain structure. Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq. Science 347:1138–42 [Google Scholar]
  121. Zeng H, Shen EH, Hohmann JG, Oh SW, Bernard A. et al. 2012. Large-scale cellular-resolution gene profiling in human neocortex reveals species-specific molecular signatures. Cell 149:483–96 [Google Scholar]
  122. Zhang B, Gaiteri C, Bodea LG, Wang Z, McElwee J. et al. 2013. Integrated systems approach identifies genetic nodes and networks in late-onset Alzheimer's disease. Cell 153:707–20 [Google Scholar]
  123. Zhang B, Horvath S. 2005. A general framework for weighted gene co-expression network analysis. Stat. Appl. Genet. Mol. Biol. 4:17 [Google Scholar]
  124. Zhang Y, Barres BA. 2010. Astrocyte heterogeneity: an underappreciated topic in neurobiology. Curr. Opin. Neurobiol. 20:588–94 [Google Scholar]
  125. Zhang Y, Chen K, Sloan SA, Bennett ML, Scholze AR. et al. 2014. An RNA-sequencing transcriptome and splicing database of glia, neurons, and vascular cells of the cerebral cortex. J. Neurosci. 34:11929–47 [Google Scholar]
  126. Zhang Y, Sloan SA, Clarke LE, Caneda C, Plaza CA. et al. 2016. Purification and characterization of progenitor and mature human astrocytes reveals transcriptional and functional differences with mouse. Neuron 89:37–53 [Google Scholar]
  127. Zilles K, Amunts K. 2009. Receptor mapping: architecture of the human cerebral cortex. Curr. Opin. Neurol. 22:331–39 [Google Scholar]
  128. Zilles K, Amunts K. 2013. Individual variability is not noise. Trends Cogn. Sci. 17:4153–55 [Google Scholar]

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