Abstract
Despite the explosive growth of bioinformatics, data sharing has not yet become routine in neuroscience, possibly because of several broad-spanning issues, from data heterogeneity to privacy regulations. We present the case of neuronal morphology as an ideal example of shareable data. Drawing from recent experience, we argue that the tremendous research potential of existing (and largely unused) digital reconstructions should diffuse any reticence to sharing this type of data.
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References
Human Brain Project [Online], (2006).
Koslow, S. H. & Hirsch, M. D. Celebrating a decade of neuroscience databases: looking to the future of high-throughput data analysis, data integration, and discovery neuroscience. Neuroinformatics 2, 267–270 (2004).
NIH Blueprint for Neuroscience Research [Online], (2006).
Insel, T. R., Volkow, N. D., Li, T. K., Battey, J. F. Jr & Landis, S. C. Neuroscience networks: data-sharing in an information age. PLoS Biol. 1, e17 (2003).
Koslow, S. H. Should the neuroscience community make a paradigm shift to sharing primary data? Nature Neurosci. 3, 863–865 (2000).
Eckersley, P. et al. Neuroscience data and tool sharing: a legal and policy framework for neuroinformatics. Neuroinformatics 1, 149–165 (2003).
Ascoli, G. A., De Schutter, E. & Kennedy, D. N. An information science infrastructure for neuroscience. Neuroinformatics 1, 1–2 (2003).
The neuroinformatics site [Online], (2006).
Neuroscience Database Gateway [Online], (2006).
Gardner, D. & Shepherd, G. M. A gateway to the future of neuroinformatics. Neuroinformatics 2, 271–274 (2004).
Koslow, S. H. Sharing primary data: a threat or asset to discovery? Nature Rev. Neurosci. 3, 311–313 (2002).
Editorial. A debate over fMRI data sharing. Nature Neurosci. 3, 845–846 (2000).
Van Horn, J. D., Grafton, S. T., Rockmore, D. & Gazzaniga, M. S. Sharing neuroimaging studies of human cognition. Nature Neurosci. 7, 473–481 (2004).
Martone, M. E. et al. The cell-centered database: a database for multiscale structural and protein localization data from light and electron microscopy. Neuroinformatics 1, 379–395 (2003).
Becker, K. G. The sharing of cDNA microarray data. Nature Rev. Neurosci. 2, 438–440 (2001).
Geschwind, D. H. Sharing gene expression data: an array of options. Nature Rev. Neurosci. 2, 435–438 (2001).
Miles, M. F. Microarrays: lost in a storm of data? Nature Rev. Neurosci. 2, 441–443 (2001).
Bowden, D. M. & Dubach, M. F. NeuroNames 2002. Neuroinformatics 1, 43–59 (2003).
Kotter, R. Online retrieval, processing, and visualization of primate connectivity data from the CoCoMac database. Neuroinformatics 2, 127–144 (2004).
Bota, M., Dong, H. W. & Swanson, L. W. Brain architecture management system. Neuroinformatics 3, 15–48 (2005).
Mirsky, J. S., Nadkarni, P. M., Healy, M. D., Miller, P. L. & Shepherd, G. M. Database tools for integrating and searching membrane property data correlated with neuronal morphology. J. Neurosci. Methods 82, 105–121 (1998).
Ascoli, G. A., Krichmar, J. L., Nasuto, S. J. & Senft, S. L. Generation, description and storage of dendritic morphology data. Phil. Trans. R. Soc. Lond. B 356, 1131–1145 (2001).
Capowski, J. J. Computer Techniques in Neuroanatomy (Plenum, New York, 1985).
Glaser, J. R. & Glaser, E. M. Neuron imaging with Neurolucida — a PC-based system for image combining microscopy. Comput. Med. Imaging Graph. 14, 307–317 (1990).
Brown, K. M., Donohue, D. E., D'Alessandro, G. & Ascoli, G. A. A cross-platform freeware tool for digital reconstruction of neuronal arborizations from image stacks. Neuroinformatics 3, 343–360 (2005).
Cannon, R. C., Wheal, H. V. & Turner, D. A. Dendrites of classes of hippocampal neurons differ in structural complexity and branching patterns. J. Comp. Neurol. 413, 619–633 (1999).
Li, Y., Brewer, D., Burke, R. E. & Ascoli, G. A. Developmental changes in spinal motoneuron dendrites in neonatal mice. J. Comp. Neurol. 483, 304–317 (2005).
The NEURON Simulation Environment [Online], (2006).
Senselab ModelDB [Online], (2006).
Mainen, Z. F. & Sejnowski, T. J. Influence of dendritic structure on firing pattern in model neocortical neurons. Nature 382, 363–366 (1996).
Krichmar, J. L., Nasuto, S. J., Scorcioni, R., Washington, S. D. & Ascoli, G. A. Effects of dendritic morphology on CA3 pyramidal cell electrophysiology: a simulation study. Brain Res. 941, 11–28 (2002).
Ascoli, G. A. Neuroanatomical algorithms for dendritic modelling. Network 13, 247–260 (2002).
Stepanyants, A. & Chklovskii, D. B. Neurogeometry and potential synaptic connectivity. Trends Neurosci. 28, 387–394 (2005).
Markram, H. The blue brain project. Nature Rev. Neurosci. 7, 153–160 (2006).
Gardner, D. et al. Towards effective and rewarding data sharing. Neuroinformatics 1, 289–295 (2003).
He, W. et al. Automated three-dimensional tracing of neurons in confocal and brightfield images. Microsc. Microanal. 9, 296–310 (2003).
Rodriguez, A. et al. Automated reconstruction of three-dimensional neuronal morphology from laser scanning microscopy images. Methods 30, 94–105 (2003).
Schmitt, S., Evers, J. F., Duch, C., Scholz, M. & Obermayer, K. New methods for the computer-assisted 3-D reconstruction of neurons from confocal image stacks. Neuroimage 23, 1283–1298 (2004).
The NeuroMorpho.org inventory [Online], (2006).
Turner, D. A., Cannon, R. C. & Ascoli, G. A. in Neuroscience Databases – A Practical Guide (ed. Kotter, R.) 81–98 (Elsevier, Amsterdam, 2002).
Cannon, R. C., Howell, F. W., Goddard, N. H. & De Schutter, E. Non-curated distributed databases for experimental data and models in neuroscience. Network 13, 415–428 (2002).
Scorcioni, R., Lazarewicz, M. T. & Ascoli, G. A. Quantitative morphometry of hippocampal pyramidal cells: differences between anatomical classes and reconstructing laboratories. J. Comp. Neurol. 473, 177–193 (2004).
Samsonovich, A. V. & Ascoli, G. A. Morphological homeostasis in cortical dendrites. Proc. Natl Acad. Sci. USA 103, 1569–1574 (2006).
Kennedy, D. N. The impact of neuroinformatics. Neuroinformatics 3, 287–292 (2005).
Hines, M. L., Morse, T., Migliore, M., Carnevale, N. T. & Shepherd, G. M. ModelDB: A database to support computational neuroscience. J. Comput. Neurosci. 17, 7–11 (2004).
International Consortium for Brain Mapping [Online], (2006).
Mouse Brain Library [Online], (2006).
Allen Brain Atlas [Online], (2006).
BrainInfo [Online], (2006).
The LNI neurophysiology database [Online], (2006).
Synapse Web [Online], (2006).
Cell Centered Database [Online], (2006).
Computational Neurobiology and Imaging Center [Online], (2006).
Computational Neuroscience on the Web [Online], (2006).
Neuron_Morpho Plugin for ImageJ [Online], (2006).
Cvapp: Neuron morphology and conversion tool [Online], (2006).
L-Measure: Morphometric analysis of neuronal reconstructions [Online], (2006).
Scorcioni, R. & Ascoli, G. A. Algorithmic extraction of morphological statistics from electronic archives of neuroanatomy. Lect. Notes Comp. Sci. 2084, 30–37 (2001).
Ascoli, G. A. & Krichmar, J. L. L-Neuron: a modeling tool for the efficient generation and parsimonious description of dendritic morphology. Neurocomputing 32–33, 1003–1011 (2000).
The GENESIS Simulation Environment [Online], (2006).
Migliore, M., Ferrante, M. & Ascoli, G. A. Signal propagation in oblique dendrites of CA1 pyramidal cells. J. Neurophysiol. 94, 4145–4155 (2005).
Samsonovich, A. V. & Ascoli, G. A. Statistical determinants of dendritic morphology in hippocampal pyramidal neurons: a hidden Markov model. Hippocampus 15, 166–183 (2005).
Acknowledgements
I am grateful to all members of my laboratory. In particular, illustration material for this manuscript was contributed by K. Brown, D. Donohue, M. Ferrante, M. Halavi, D. Ropireddy and A. Samsonovich. This work was supported in part by a grant co-funded by the National Institute of Neural Disorders and Stroke, the National Institute of Mental Health and the National Science Foundation (NSF) under the Human Brain Project; by a grant from the National Institute of Aging as part of the NSF/NIH (National Institutes of Health) Collaborative Research in Computational Neuroscience program; and by a contract from the National Institute of Drug Abuse under the Neuroscience Blueprint initiative.
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Ascoli, G. Mobilizing the base of neuroscience data: the case of neuronal morphologies. Nat Rev Neurosci 7, 318–324 (2006). https://doi.org/10.1038/nrn1885
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DOI: https://doi.org/10.1038/nrn1885
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