What’s Black and White About the Grey Matter?
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In 1873 Camillo Golgi discovered his eponymous stain, which he called la reazione nera. By adding to it the concepts of the Neuron Doctrine and the Law of Dynamic Polarisation, Santiago Ramon y Cajal was able to link the individual Golgi-stained neurons he saw down his microscope into circuits. This was revolutionary and we have all followed Cajal’s winning strategy for over a century. We are now on the verge of a new revolution, which offers the prize of a far more comprehensive description of neural circuits and their operation. The hope is that we will exploit the power of computer vision algorithms and modern molecular biological techniques to acquire rapidly reconstructions of single neurons and synaptic circuits, and to control the function of selected types of neurons. Only one item is now conspicuous by its absence: the 21st century equivalent of the concepts of the Neuron Doctrine and the Law of Dynamic Polarisation. Without their equivalent we will inevitably struggle to make sense of our 21st century observations within the 19th and 20th century conceptual framework we have inherited.
KeywordsNeuron Doctrine Law of Dynamic Polarisation Golgi stain Canonical cortical circuits High-throughput circuit reconstruction
We thank our colleagues in the INI for unrelenting discussions and unsparing debates. This review formed the basis of a lecture given by KACM at the Diadem Grand Challenge final at HHMI Janelia Farm. Supported by EU SECO grant 216593 to both authors and Human Frontiers Science Program grant RG 0123/2000-B to KACM.
- Ananthanarayanan, R., Esser, S. K., Simon, H. D., & Modha, D. S. (2009). The cat is out of the bag: Cortical Simulations with 10^9 neurons and 10^13 synapses. Supercomputing 09: Proceedings of the ACM/IEEE SC2009 Conference on High Performance Networking and Computing, Nov 14–20, 2009, Portland, OR.Google Scholar
- Barlow, H. B. (1977). Performance, perception, dark-light, and gain boxes. In E. Pöppel, R. Held, & J. E. Dowling (Eds.), Neuronal mechanisms in visual perception (pp. 394–397). Cambridge: Neurosciences Research Program Bulletin 15, MIT Press.Google Scholar
- Barlow, H. B. (1980). Cortical function: A tentative theory and preliminary test. In D. McFadden (Ed.), Neural mechanisms in behaviour (pp. 143–171). New York: Springer.Google Scholar
- Barone, P., Batardiere, A., Knoblauch, K., & Kennedy, H. (2000). Laminar distribution of neurons in extrastriate areas projecting to visual areas V1 and V4 correlates with the hierarchical rank and indicates the operation of a distance rule. The Journal of Neuroscience, 20, 3263–3281.PubMedGoogle Scholar
- Bas, E., & Erdogmus, D. (2011). Principal curves as skeletons of tubular objects: locally characterizing the structures of axons. Neuroinformatics, THIS ISSUE.Google Scholar
- Braitenberg, V., & Lauria, F. (1960). Toward a mathematical description of the grey substance of nervous systems. Nuovo Cimento, 18, 1135–1151.Google Scholar
- Braitenberg, V., & Schüz, A. (1991). Peters’ rule and White’s exceptions. In: Anatomy of the cortex (pp. 109–112). Berlin: Springer.Google Scholar
- Cajal, S. R. (1913–1914). Estudios Sobre la Degeneración y Regeneración del Sistema Nervioso, Moya. ‘Cajal’s Degeneration and Regeneration of the Nervous System’, OUP New York. Reprinted and edited with additional translations by J DeFelipe, J. and EG Jones, (1991).Google Scholar
- Cajal, S. R. (1921). Histology of the visual cortex of the cat. Archivos de Neurobiologia, 2, 338–362. In. J. DeFelipe & E. G. Jones (Eds.), Cajal of the cerebral cortex (pp. 495–523). New York: OUP.Google Scholar
- Cajal, S. R. (1937). Recollections of my life. Translated by EH Craigie, J Cano. 1989 Philadephia PA Am Philos. Soc.Google Scholar
- Chothani, P., Mehta, V., & Stepanyants, A. (2011). Automated tracing of neurites from light microscopy stacks of images. Neuroinformatics, THIS ISSUE.Google Scholar
- Crick, F. H. C. In V. S. Ramachandran (1985). The neurobiology of perception. Perception 14, 97–103.Google Scholar
- da Costa, N. M., & Martin, K. A. C. (2010). Whose cortical column would that be? Frontiers Neuroanat, 4, 16.Google Scholar
- Eccles, J. C., Ito, M., & Szentágothai, J. (1967). The Cerebellum as a Neuronal Machine. New York: Springer. 343 pp.Google Scholar
- Elston, G. N., Benavides-Piccione, R., & DeFelipe, J. (2001). The pyramidal cell in cognition: a comparative study in human and monkey. Journal of Neuroscience, 21, RC163, 1–5.Google Scholar
- Fulton, J. F. (1949). Physiology of the nervous system (pp. 288–312). New York: OUP.Google Scholar
- Gilbert, C.D. (1983). Microcircuitry of the visual cortex. Annu Rev Neurosci. 6, 217–247.Google Scholar
- Gilbert, C. D., & Wiesel, T. N. (1981). Laminar specialization and intracortical connections in cat primary visual cortex. In F. O. Schmitt, F. G. Worden, G. Adelman, & S. G. Dennis (Eds.), The organization of the cerebral cortex (pp. 163–191). Cambridge: MIT.Google Scholar
- Hubel, D. H., & Wiesel, T. N. (1962). Receptive fields, binocular interaction and functional architecture in the cat's visual cortex. J. Physiol, 160, 106–154.Google Scholar
- Lorente de Nó, R. (1949). “Cerebral cortex: architecture, intracortical connections, motor projections,” in Physiology of the Nervous System, ed. J. F. Fulton (New York: Oxford University Press), 288–312.Google Scholar
- Lorente de Nó, R. (1992). The cerebral cortex of the mouse, a first contribution—the acoustic cortex. Somatosensory and Motor Research. 9, 3–36, translated by A. Fairen, J. Regidor, L. Kruger, from the original, La corteza cerebral raton, primera contribucion- la corteza acustica, Trabajos del Laboratorio de Investigaciones Biologicas de la Universidad de Madrid, 20 (1922) 41–78.Google Scholar
- Markov, N. T., Misery, P., Falchier, A., Lamy, C., Vezoli, J., Quilodran, R., et al. (2010). Weight consistency specifies regularities of Macaque Cortical Networks. Cerebral Cortex, (in press).Google Scholar
- Markram, H. (2010). http://www.ted.com/talks/henry_markram_supercomputing_the_brain_s_secrets.html.
- Narayanaswamy, A., Wang, Y., & Roysam, B. (2011). A preprocessing pipeline to enhance 3-D images of neuronal arbors. Neuroinformatics, THIS ISSUE.Google Scholar
- Rockland, K. S. (1997). Elements of cortical architecture. Hierarchy revisited. In K. S. Rockland, J. H. Kaas, & A. Peters (Eds.), Cerebral cortex, vol. 12 (pp. 243–293). New York: Plenum.Google Scholar
- Rockland, K. S. (2010). Five points on columns. Frontiers in Neuroanatomy, 4, 1–10.Google Scholar
- Rushton, W. A. H. (1977). Some memories of visual research in the past 50 years. In The pursuit of nature (pp. 85–104.). Cambridge: CUP.Google Scholar
- Seung, H. S. (2010). http://www.ted.com/talks/sebastian_seung.html.
- Shepherd, G. M. (1991). Foundations of the neuron doctrine. New York: Oxford University Press.Google Scholar
- Sherrington, C. (1940). Man on his Nature. Cambridge. CUP. p. 277.Google Scholar
- Sholl, D. (1956). The organisation of the cerebral cortex. London: Methuen.Google Scholar
- Sullivan, L. (1896). The tall office building artistically considered. Lippincotts Magazine (March). In I. Athey (Ed.), Kindergarten chats and other writings. New York: Dover Publications. 1979.Google Scholar
- Thompson, D. W. (1971). On growth and form. Abridged Edition. Cambridge: CUP.Google Scholar
- Turetken, E., Gonzalez, G., Blum, C., Fua, P. (2011). Automated reconstruction of dendritic and axonal trees by global optimization with geometric priors. Neuroinformatics, THIS ISSUE.Google Scholar
- Wang, Y., Narayanaswamy, A., Tsai, C., Roysam, B. (2011). Generally Applicable 3D >Neuron Tracing Approach and System based on Open-Curve Snake. Neuroinformatics, THIS ISSUE.Google Scholar
- Zhao, T., Xie, J., Amat, F., Clack, N., Ahammad, P., Peng, H., Long, F., Myers, E. (2011). Automated reconstruction of neuronal morphology based on local geometrical and global structural models. Neuroinformatics, THIS ISSUE.Google Scholar