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12 - Electrical structures in 3D dendritic space

Published online by Cambridge University Press:  03 May 2010

Sergiy Mikhailovich Korogod
Affiliation:
Dniepropetrovsk National University, Ukraine
Suzanne Tyč-Dumont
Affiliation:
CNRS, Marseille
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Summary

For the biologist, the gap between results of model computation and live neurons is filled when an electrical structure is mapped on the static anatomy of the dendritic field of neurons. The speaking likeness of these 3D images opens a new way of thinking by providing a functional image of 3D dendritic space. Indeed it is new because the question of the electrical state of the whole dendritic space is rarely addressed, although critical for understanding how the neuron processes its inputs.

The three types of neurons investigated here have their own idiosyncratic 3D dendritic pattern so well described in morphological words. In Chapters 10 and 11, we explore the arborizations as determinants of their spatial electrical properties without referring to the dendritic geometry as an object inserted in physical 3D space. The restriction of this view can be explained with a simple analogy. This is a view of the dendrites ‘from the inside’.

We can imagine the dendritic arborization as a ‘cave maze’ in the brain's depths. When we are inside the maze, we do not perceive its 3D shape. We can wander inside, uncoiling ‘Ariadne's thread’ on our path from the entry (the soma) to the deadlocks (the distal tips) and then measure the length of the threads between those points to find the path lengths. Another spatial information available from the interior view is the diameter of the ‘cave’ at each site along the path. Knowing the lengths and diameters of all the paths in such a labyrinth is sufficient for computing the spatial electrical structures.

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Chapter
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Publisher: Cambridge University Press
Print publication year: 2009

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References

Bras, H., Gogan, P. and Tyč-Dumont, S. (1987). The dendrites of single brain-stem motoneurons intracellularly labelled with horseradish peroxidase in the cat. Morphological and electrical differences. Neuroscience, 22:947–970.CrossRef
Bras, H., Korogod, S., Driencourt, Y., Gogan, P. and Tyč-Dumont, S. (1993). Stochastic geometry and electrotonic architecture of dendritic arborization of a brain-stem motoneuron. Eur. J. Neurosci., 5:1405–1493.CrossRef
Korogod, S. M., Bras, H., Sarana, V. N., Gogan, P. and Tyč-Dumont, S. (1994). Electrotonic clusters in the dendritic arborisation of abducens motoneurons in the rat. Eur. J. Neurosci., 6:1517–1527.CrossRef
Korogod, S. M., Kulagina, I. B., Horcholle-Bossavit, G., Gogan, P. and Tyč-Dumont, S. (2000). Activity-dependent reconfiguration of the effective dendritic field of motoneurons. J. Comp. Neurol., 422:18–34.3.0.CO;2-A>CrossRef
Korogod, S. M., Kulagina, I. B., Kukushka, V. I., Gogan, P. and Tyč-Dumont, S. (2002). Spatial reconfiguration of charge transfer effectiveness in active bistable dendritic arborizations. Eur. J. Neurosci., 16:2260–2270.CrossRef
Kulagina, I. B., Korogod, S. M., Horcholle-Bossavit, G., Batini, C. and Tyč-Dumont, S. (2007). The electro-dynamics of the dendritic space in Purkinje cells of the cerebellum. Arch. Ital. Biol., 145:211–233.

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