Amyotrophic lateral sclerosis (ALS) is a devastating neurodegenerative disorder typically characterized by insoluble inclusions of hyperphosphorylated TDP-43. The mechanisms underlying toxic TDP-43 accumulation are not understood. Persistent activation of p38 mitogen-activated protein kinase (MAPK) is implicated in ALS. However, it is unclear how p38 MAPK affects TDP-43 proteinopathy. Here, we show that p38α MAPK inhibition reduces pathological TDP-43 phosphorylation, aggregation, cytoplasmic mislocalization, and neurotoxicity. Remarkably, p38α MAPK inhibition mitigates aberrant TDP-43 phenotypes in diverse ALS patient-derived motor neurons. p38α MAPK phosphorylates TDP-43 at pathological S409/S410 and S292, which reduces TDP-43 liquid-liquid phase separation (LLPS) but allows pathological TDP-43 aggregation. Moreover, we establish that PRMT1 methylates TDP-43 at R293. Importantly, S292 phosphorylation reduces R293 methylation, and R293 methylation reduces S409/S410 phosphorylation. Notably, R293 methylation permits TDP-43 LLPS and reduces pathological TDP-43 aggregation. Thus, strategies to reduce p38α-mediated TDP-43 phosphorylation and promote PRMT1-mediated R293 methylation could have therapeutic utility for ALS and related TDP-43 proteinopathies.

Cell death is a critical process that occurs normally in health and disease. However, its study is limited due to available technologies that only detect very late stages in the process or specific death mechanisms. Here, we report the development of a family of fluorescent biosensors called genetically encoded death indicators (GEDIs). GEDIs specifically detect an intracellular Ca 2+ level that cells achieve early in the cell death process and that marks a stage at which cells are irreversibly committed to die. The time-resolved nature of a GEDI delineates a binary demarcation of cell life and death in real time, reformulating the definition of cell death. We demonstrate that GEDIs acutely and accurately report death of rodent and human neurons in vitro, and show that GEDIs enable an automated imaging platform for single cell detection of neuronal death in vivo in zebrafish larvae. With a quantitative pseudo-ratiometric signal, GEDIs facilitate high-throughput analysis of cell death in time-lapse imaging analysis, providing the necessary resolution and scale to identify early factors leading to cell death in studies of neurodegeneration.

Persistent cytoplasmic aggregates containing RNA binding proteins (RBPs) are central to the pathogenesis of late-onset neurodegenerative disorders such as amyotrophic lateral sclerosis (ALS). These aggregates share components, molecular mechanisms, and cellular protein quality control pathways with stress-induced RNA granules (SGs). Here, we assess the impact of stress on the global mRNA localization landscape of human pluripotent stem cell-derived motor neurons (PSC-MNs) using subcellular fractionation with RNA sequencing and proteomics. Transient stress disrupts subcellular RNA and protein distributions, alters the RNA binding profile of SG- and ALS-relevant RBPs and recapitulates disease-associated molecular changes such as aberrant splicing of STMN2. Although neurotypical PSC-MNs re-establish a normal subcellular localization landscape upon recovery from stress, cells harboring ALS-linked mutations are intransigent and display a delayed-onset increase in neuronal cell death. Our results highlight subcellular molecular distributions as predictive features and underscore the utility of cellular stress as a paradigm to study ALS-relevant mechanisms.

Cellular events underlying neurodegenerative disease may be captured by longitudinal live microscopy of neurons. While the advent of robot-assisted microscopy has helped scale such efforts to high-throughput regimes with the statistical power to detect transient events, time-intensive human annotation is required. We addressed this fundamental limitation with biomarker-optimized convolutional neural networks (BO-CNNs): interpretable computer vision models trained directly on biosensor activity. We demonstrate the ability of BO-CNNs to detect cell death, which is typically measured by trained annotators. BO-CNNs detected cell death with superhuman accuracy and speed by learning to identify subcellular morphology associated with cell vitality, despite receiving no explicit supervision to rely on these features. These models also revealed an intranuclear morphology signal that is difficult to spot by eye and had not previously been linked to cell death, but that reliably indicates death. BO-CNNs are broadly useful for analyzing live microscopy and essential for interpreting high-throughput experiments.

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder typically characterized by insoluble inclusions of hyperphosphorylated TDP-43. The mechanisms underlying toxic TDP-43 accumulation are not understood. Persistent activation of p38 mitogen-activated protein kinase (MAPK) is implicated in ALS. However, it is unclear how p38 MAPK affects TDP-43 proteinopathy. Here, we demonstrate that inhibition of p38α MAPK reduces pathological TDP-43 phosphorylation, aggregation, cytoplasmic mislocalization, and neurotoxicity. We establish that p38α MAPK phosphorylates TDP-43 at pathological serine 409/410 (S409/S410) and serine 292 (S292), which reduces TDP-43 liquid-liquid phase separation (LLPS) but allows pathological TDP-43 aggregation. Moreover, we show that protein arginine methyltransferase 1 methylates TDP-43 at R293. Importantly, S292 phosphorylation reduces R293 methylation, and R293 methylation reduces S409/S410 phosphorylation. R293 methylation permits TDP-43 LLPS and reduces pathological TDP-43 aggregation. Thus, strategies to reduce p38α-mediated TDP-43 phosphorylation and promote R293 methylation could have therapeutic utility for ALS and related TDP-43 proteinopathies.

Current approaches for dynamic profiling of single cells rely on dissociated cultures, which lack important biological features existing in tissues. Organotypic slice cultures preserve aspects of structural and synaptic organisation within the brain and are amenable to microscopy, but established techniques are not well adapted for high throughput or longitudinal single cell analysis. Here we developed a custom-built, automated confocal imaging platform, with improved organotypic slice culture and maintenance. The approach enables fully automated image acquisition and four-dimensional tracking of morphological changes within individual cells in organotypic cultures from rodent and human primary tissues for at least 3 weeks. To validate this system, we analysed neurons expressing a disease-associated version of huntingtin (HTT586Q138-EGFP), and observed that they displayed hallmarks of Huntington's disease and died sooner than controls. By facilitating longitudinal single-cell analyses of neuronal physiology, our system bridges scales necessary to attain statistical power to detect developmental and disease phenotypes.

Stress granules (SGs) form during cellular stress and are implicated in neurodegenerative diseases such as amyotrophic lateral sclerosis and frontotemporal dementia (ALS/FTD). To yield insights into the role of SGs in pathophysiology, we performed a high-content screen to identify small molecules that alter SG properties in proliferative cells and human iPSC-derived motor neurons (iPS-MNs). One major class of active molecules contained extended planar aromatic moieties, suggesting a potential to intercalate in nucleic acids. Accordingly, we show that several hit compounds can prevent the RNA-dependent recruitment of the ALS-associated RNA-binding proteins (RBPs) TDP-43, FUS, and HNRNPA2B1 into SGs. We further demonstrate that transient SG formation contributes to persistent accumulation of TDP-43 into cytoplasmic puncta and that our hit compounds can reduce this accumulation in iPS-MNs from ALS patients. We propose that compounds with planar moieties represent a promising starting point to develop small-molecule therapeutics for treating ALS/FTD.

Microscopy is a central method in life sciences. Many popular methods, such as antibody labeling, are used to add physical fluorescent labels to specific cellular constituents. However, these approaches have significant drawbacks, including inconsistency; limitations in the number of simultaneous labels because of spectral overlap; and necessary perturbations of the experiment, such as fixing the cells, to generate the measurement. Here, we show that a computational machine- learning approach, which we call "in silico labeling'' (ISL), reliably predicts some fluorescent labels from transmitted- light images of unlabeled fixed or live biological samples. ISL predicts a range of labels, such as those for nuclei, cell type (e.g., neural), and cell state (e.g., cell death). Because prediction happens in silico, the method is consistent, is not limited by spectral overlap, and does not disturb the experiment. ISL generates biological measurements that would otherwise be problematic or impossible to acquire.

HnRNPA2B1 encodes an RNA binding protein associated with neurodegeneration. However, its function in the nervous system is unclear. Transcriptome-wide crosslinking and immunoprecipitation in mouse spinal cord discover UAGG motifs enriched within similar to 2,500 hnRNP A2/B1 binding sites and an unexpected role for hnRNP A2/B1 in alternative polyadenylation. HnRNP A2/B1 loss results in alternative splicing (AS), including skipping of an exon in amyotrophic lateral sclerosis (ALS)-associated D-amino acid oxidase (DAO) that reduces D-serine metabolism. ALS-associated hnRNP A2/B1 D290V mutant patient fibroblasts and motor neurons differentiated from induced pluripotent stem cells (iPSC-MNs) demonstrate abnormal splicing changes, likely due to increased nuclear-insoluble hnRNP A2/B1. Mutant iPSC-MNs display decreased survival in long-term culture and exhibit hnRNP A2/B1 localization to cytoplasmic granules as well as exacerbated changes in gene expression and splicing upon cellular stress. Our findings provide a cellular resource and reveal RNA networks relevant to neurodegeneration, regulated by normal and mutant hnRNP A2/B1.

The transcriptional profiles of radial glia are compared between humans and mice during neurogenesis, implicating the growth factor PDGFD and its receptor, PDGFRβ, in human but not mouse neocortical development. The unique intellectual capabilities of humans are widely attributed to the expansion of the human neocortex in comparison to primates and other mammals. Recent reports implicated the elevated proliferative potential of radial glia, a type of neuronal precursor cell than spans the developing cerebral cortex, as a driver for neocortical expansion. Arnold Kriegstein and colleagues take this concept further by identifying evolutionary changes in radial glia gene expression that may have contributed to human neocortical expansion. They find that humans and mice exhibit highly conserved gene expression patterns amongst radial glia except for a few specific signalling pathways. PDGFD and its receptor, PDGFRβ, show distinct expression patterns and profiles in human cortex development that are absent in mice. Disrupting these paths in human brain slice cultures prevents normal cell cycle progression, whereas ectopic activation of these paths in mice enhances radial glia proliferation and dispersion, revealing one critical mechanism specific to human cortical development. Evolutionary expansion of the human neocortex underlies many of our unique mental abilities. This expansion has been attributed to the increased proliferative potential1,2 of radial glia (RG; neural stem cells) and their subventricular dispersion from the periventricular niche3,4,5 during neocortical development. Such adaptations may have evolved through gene expression changes in RG. However, whether or how RG gene expression varies between humans and other species is unknown. Here we show that the transcriptional profiles of human and mouse neocortical RG are broadly conserved during neurogenesis, yet diverge for specific signalling pathways. By analysing differential gene co-expression relationships between the species, we demonstrate that the growth factor PDGFD is specifically expressed by RG in human, but not mouse, corticogenesis. We also show that the expression domain of PDGFRβ, the cognate receptor6,7 for PDGFD, is evolutionarily divergent, with high expression in the germinal region of dorsal human neocortex but not in the mouse. Pharmacological inhibition of PDGFD–PDGFRβ signalling in slice culture prevents normal cell cycle progression of neocortical RG in human, but not mouse. Conversely, injection of recombinant PDGFD or ectopic expression of constitutively active PDGFRβ in developing mouse neocortex increases the proportion of RG and their subventricular dispersion. These findings highlight the requirement of PDGFD–PDGFRβ signalling for human neocortical development and suggest that local production of growth factors by RG supports the expanded germinal region and progenitor heterogeneity of species with large brains.

There has been a growing interest in using next-generation sequencing (NGS) to profile extracellular small RNAs from the blood and cerebrospinal fluid (CSF) of patients with neurological diseases, CNS tumors, or traumatic brain injury for biomarker discovery. Small sample volumes and samples with low RNA abundance create challenges for downstream small RNA sequencing assays. Plasma, serum, and CSF contain low amounts of total RNA, of which small RNAs make up a fraction. The purpose of this study was to maximize RNA isolation from RNA-limited samples and apply these methods to profile the miRNA in human CSF by small RNA deep sequencing. We systematically tested RNA isolation efficiency using ten commercially available kits and compared their performance on human plasma samples. We used RiboGreen to quantify total RNA yield and custom TaqMan assays to determine the efficiency of small RNA isolation for each of the kits. We significantly increased the recovery of small RNA by repeating the aqueous extraction during the phenol-chloroform purification in the top performing kits. We subsequently used the methods with the highest small RNA yield to purify RNA from CSF and serum samples from the same individual. We then prepared small RNA sequencing libraries using Illumina's TruSeq sample preparation kit and sequenced the samples on the HiSeq 2000. Not surprisingly, we found that the miRNA expression profile of CSF is substantially different from that of serum. To our knowledge, this is the first time that the small RNA fraction from CSF has been profiled using next-generation sequencing.

Development of therapeutics for genetically complex neurodegenerative diseases such as sporadic amyotrophic lateral sclerosis (ALS) has largely been hampered by lack of relevant disease models. Reprogramming of sporadic ALS patients' fibroblasts into induced pluripotent stem cells (iPSC) and differentiation into affected neurons that show a disease phenotype could provide a cellular model for disease mechanism studies and drug discovery. Here we report the reprogramming to pluripotency of fibroblasts from a large cohort of healthy controls and ALS patients and their differentiation into motor neurons. We demonstrate that motor neurons derived from three sALS patients show de novo TDP-43 aggregation and that the aggregates recapitulate pathology in postmortem tissue from one of the same patients from which the iPSC were derived. We configured a high-content chemical screen using the TDP-43 aggregate endpoint both in lower motor neurons and upper motor neuron like cells and identified FDA-approved small molecule modulators including Digoxin demonstrating the feasibility of patient-derived iPSC-based disease modeling for drug screening.

Key Points Induced pluripotent stem cells (iPSCs) that are derived from patients and differentiated in vitro can provide disease-relevant cell types for drug screening. Directed differentiation of iPSCs has yielded many disease-relevant cells — chiefly neurons, hepatocytes, blood cells and cardiomyocytes — but often the cells reflect embryonic stages of development, and may not faithfully reflect disease phenotypes of adult tissues. Methods for deriving iPSCs are evolving, and much remains to be learned about the genetic and epigenetic stability of iPSCs and their relationships to embryonic stem cells, and how this affects the fidelity of drug screening. Notwithstanding a few exceptions, disease modelling so far has focused on Mendelian disorders of high clinical penetrance and with a recognized cellular pathophysiology, such as spinal muscular atrophy, familial dysautonomia, Rett syndrome, Hutchinson–Gilford progeria syndrome and long QT syndrome. Whether more complex, sporadically occurring disease entities can be modelled with iPSCs remains uncertain. Cell-based assays enable the discovery of novel pathways and the identification of compounds with favourable cell permeability and toxicity profiles, but such assays are less amenable to defining the structure–activity relationships that are important for optimizing drug properties. iPSCs offer important advantages for drug toxicity screening against relevant human cells and tissues, and may facilitate the development of ' in vitro clinical trials' to test the efficacy of drugs or gene correction vectors against various distinct patient genotypes.

The excitatory neurons of the mammalian cerebral cortex arise from asymmetric divisions of radial glial cells in the ventricular zone and symmetric division of intermediate progenitor cells (IPCs) in the subventricular zone (SVZ) of the embryonic cortex. Little is known about the microenvironment in which IPCs divide or whether a stem cell niche exists in the SVZ of the embryonic cortex. Recent evidence suggests that vasculature may provide a niche for adult stem cells but its role in development is less clear. We have investigated the vasculature in the embryonic cortex during neurogenesis and find that IPCs are spatially and temporally associated with blood vessels during cortical development. Intermediate progenitors mimic the pattern of capillaries suggesting patterns of angiogenesis and neurogenesis are coordinated during development. More importantly, we find that IPCs divide near blood vessel branch points suggesting that cerebral vasculature establishes a stem cell niche for intermediate progenitors in the SVZ. These data provide novel evidence for the presence of a neurogenic niche for intermediate progenitors in the embryonic SVZ and suggest blood vessels are important for proper patterning of neurogenesis.

We have used in vivo time-lapse two-photon imaging of single motor neuron axons labeled with GFP combined with labeling of presynaptic vesicle clusters and postsynaptic acetylcholine receptors in Xenopus laevis tadpoles to determine the dynamic rearrangement of individual axon branches and synaptogenesis during motor axon arbor development. Control GFP-labeled axons are highly dynamic during the period when axon arbors are elaborating. Axon branches emerge from sites of synaptic vesicle clusters. These data indicate that motor neuron axon elaboration and synaptogenesis are concurrent and iterative. We tested the role of Candidate Plasticity Gene 15 (CPG15, also known as Neuritin), an activity-regulated gene that is expressed in the developing motor neurons in this process. CPG15 expression enhances the development of motor neuron axon arbors by promoting neuromuscular synaptogenesis and by increasing the addition of new axon branches.

References and Notes 1. H. Van der Loos, T. A. Woolsey, Science 179, 395 (1973). 2. D. J. Simons, P. W. Land, Nature 326, 694 (1987). 3. D. V. Buonomano, M. M. Merzenich, Annu. Rev. Neurosci. 21, 149 (1998). 4. T. A. Woolsey, H. Van der Loos, Brain Res. 17, 205 (1970). 5. G. T. Finnerty, L. S. Roberts, B. W. Connors, Nature 400, 367 (1999). 6. K. Fox, Neuroscience 111, 799 (2002). 7. M. Brecht et al., J. Neurosci. 24, 9223 (2004). 8. C. C. Petersen, Pflugers Arch. 447, 126 (2003). 9. D. Feldmeyer, V. Egger, J. Lubke, B. Sakmann, J. Physiol. 521, 169 (1999). 10. R. A. Silver, J. Lubke, B. Sakmann, D. Feldmeyer, Science 302, 1981 (2003). 11. D. Feldmeyer, J. Lubke, R. A. Silver, B. Sakmann, J. Physiol. 538, 803 (2002). 12. T. Shimogori, V. Banuchi, H. Y. Ng, J. B. Strauss, E. A. Grove, Development 131, 5639 (2004). 13. T. Fukuchi-Shimogori, E. A. Grove, Science 294, 1071 (2001). 14. R. S. Erzurumlu, P. C. Kind, Trends Neurosci. 24, 589 (2001). 15. S. Glazewski, K. Fox, J. Neurophysiol. 75, 1714 (1996). 16. M. E. Diamond, W. Huang, F. F. Ebner, Science 265, 1885 (1994). 17. E. A. Stern, M. Maravall, K. Svoboda, Neuron 31, 305 (2001). 18. D. B. Polley, E. Kvasnak, R. D. Frostig, Nature 429, 67 (2004). 19. G. W. Knott, C. Quairiaux, C. Genoud, E. Welker, Neuron 34, 265 (2002). 20. D. O. Hebb, Organization of Behavior (Wiley, New York, 1949). 21. H. Wallace, K. Fox, J. Neurobiol. 41, 58 (1999). 22. E. Siucinska, M. Kossut, Cereb. Cortex 6, 506 (1996). 23. A. Skibinska, S. Glazewski, K. Fox, M. Kossut, Exp. Brain Res. 132, 134 (2000). 24. C. B. Allen, T. Celikel, D. E. Feldman, Nat. Neurosci. 6, 291 (2003). 25. G. M. Shepherd, T. A. Pologruto, K. Svoboda, Neuron 38, 277 (2003). 26. S. Glazewski, K. P. Giese, A. Silva, K. Fox, Nat. Neurosci. 3, 911 (2000). 27. M. Kossut, Exp. Brain Res. 123, 110 (1998). 28. D. L. Maier, G. M. Grieb, D. J. Stelzner, J. S. McCasland, Exp. Neurol. 184, 737 (2003). 29. X. Wang, M. M. Merzenich, K. Sameshima, W. M. Jenkins, Nature 378, 71 (1995). 30. M. A. Lebedev, G. Mirabella, I. Erchova, M. E. Diamond, Cereb. Cortex 10, 23 (2000). 31. A. Schierloh, M. Eder, W. Zieglgansberger, H. U. Dodt, Eur. J. Neurosci. 20, 1118 (2004). 32. E. Welker, S. B. Rao, J. Dorfl, P. Melzer, H. van der Loos, J. Neurosci. 12, 153 (1992). 33. M. A. Castro-Alamancos, Prog. Neurobiol. 74, 213 (2004). 34. D. B. Polley, C. H. Chen-Bee, R. D. Frostig, Neuron 24, 623 (1999). 35. E. L. Bienenstock, L. N. Cooper, P. W. Munro, J. Neurosci. 2, 32 (1982). 36. G. G. Turrigiano, S. B. Nelson, Curr. Opin. Neurobiol. 10, 358 (2000). 37. D. E. Feldman, R. A. Nicoll, R. C. Malenka, J. Neurobiol. 41, 92 (1999). 38. K. Fox, B. L. Schlaggar, S. Glazewski, D. D. O’Leary, Proc. Natl. Acad. Sci. U.S.A. 93, 5584 (1996). 39. V. Rema, M. Armstrong-James, F. F. Ebner, J. Neurosci. 18, 10196 (1998). 40. W. A. Myers, J. D. Churchill, N. Muja, P. E. Garraghty, J. Comp. Neurol. 418, 373 (2000). 41. H. T. Cline, Curr. Opin. Neurobiol. 11, 118 (2001). 42. K. J. Bender, J. Rangel, D. E. Feldman, J. Neurosci. 23, 8759 (2003). 43. K. J. Bender, S. Deshmukh, D. E. Feldman, in Development and Plasticity in Sensory Thalamus and Cortex, W. Guido, Ed. (Academic Press, in press). 44. K. J. Bender, C. B. Allen, D. E. Feldman, Soc. Neurosci. Abstr. 26.3 (2005). 45. T. Takahashi, K. Svoboda, R. Malinow, Science 299, 1585 (2003). 46. E. Foeller, D. E. Feldman, Curr. Opin. Neurobiol. 14, 89 (2004). 47. T. W. Margrie, M. Brecht, B. Sakmann, Pfleugers Arch. 444, 491 (2002). 48. M. Brecht, M. Schneider, I. Manns, The Plasticity of the Sensory-Motor Cortices, F. Ebner, Ed. (CRC Press, in press). 49. Y. Dan, M. M. Poo, Neuron 44, 23 (2004). 50. D. E. Feldman, Neuron 27, 45 (2000). 51. T. Celikel, V. A. Szostak, D. E. Feldman, Nat. Neurosci. 7, 534 (2004). 52. D. E. Shulz, V. Ego-Stengel, E. Ahissar, J. Physiol. (Paris) 97, 431 (2003). 53. G. Feng et al., Neuron 28, 41 (2000). 54. W. Denk, J. H. Strickler, W. W. Webb, Science 248, 73 (1990). 55. B. Lendvai, E. A. Stern, B. Chen, K. Svoboda, Nature 404, 876 (2000). 56. D. B. Chklovskii, B. W. Mel, K. Svoboda, Nature 431, 782 (2004). 57. F. Engert, T. Bonhoeffer, Nature 399, 66 (1999). 58. Q. Zhou, K. J. Homma, M. M. Poo, Neuron 44, 749 (2004). 59. E. S. Ruthazer, H. T. Cline, J. Neurobiol. 59, 134 (2004). 60. M. Maravall, I. Y. Koh, W. B. Lindquist, K. Svoboda, Cereb. Cortex 14, 655 (2004). 61. F. R. Volkmar, W. T. Greenough, Science 176, 1445 (1972). 62. J. T. Trachtenberg et al., Nature 420, 788 (2002). 63. J. Grutzendler, N. Kasthuri, W. B. Gan, Nature 420, 812 (2002). 64. E. J. Green, W. T. Greenough, B. E. Schlumpf, Brain Res. 264, 233 (1983). 65. P. W. Hickmott, P. A. Steen, Nat. Neurosci. 8, 140 (2005). 66. A. K. McAllister, L. C. Katz, D. C. Lo, Annu. Rev. Neurosci. 22, 295 (1999). 67. L. C. Katz, C. J. Shatz, Science 274, 1133 (1996). 68. I. Bureau, G. M. Shepherd, K. Svoboda, Neuron 42, 789 (2004). 69. C. Darian-Smith, C. D. Gilbert, Nature 368, 737 (1994). 70. R. Yuste, T. Bonhoeffer, Annu. Rev. Neurosci. 24, 1071 (2001). 71. A. J. Holtmaat et al., Neuron 45, 279 (2005). 72. Y. Zuo, A. Lin, P. Chang, W. B. Gan, Neuron 46, 181 (2005). 73. M. Matsuzaki, N. Honkura, G. C. Ellis-Davies, H. Kasai, Nature 429, 761 (2004). 74. H. Markram, J. Lubke, M. Frotscher, A. Roth, B. Sakmann, J. Physiol. (London) 500 (part 2), 409 (1997). 75. V. Braitenberg, A. Schuz, Anatomy of the Cortex (Springer-Verlag, Berlin, 1991). 76. G. W. Davis, C. M. Schuster, C. S. Goodman, Neuron 17, 669 (1996). 77. S. Ramón y Cajal, Nuevo concepto de la Histologı́a de los Centros nerviosos (Barcelona, 1893). 78. T. Dittgen et al., Proc. Natl. Acad. Sci. U.S.A. 101, 18206 (2004). 79. K. Haas, W. C. Sin, A. Javaherian, Z. Li, H. T. Cline, Neuron 29, 583 (2001). 80. T. W. Margrie et al., Neuron 39, 911 (2003). 81. D. J. Simons, The Barrel Cortex of Rodents, E. G. Jones, I. T. Diamond, Eds. (Plenum, New York, 1995), pp. 262–298. 82. Y. Zuo, G. Yang, E. Kwon, W.-B. Gan, Nature 436, 261 (2005). 83. We thank C. Hansel and A. Lee for manuscript comments. This work was supported by NIH R01 NS046652 and the McKnight Foundation (D.F.) and the Erasmus University Rotterdam, a Vidi grant from Netherlands Organization for Scientific Research, and Human Frontier Science Program grants (M.B.).