Activity-dependent reconfiguration of the effective dendritic field of motoneurons
โ Scribed by Korogod, Sergey M.; Kulagina, Irina B.; Horcholle-Bossavit, Ginette; Gogan, Paul; Tyc-Dumont, Suzanne
- Publisher
- John Wiley and Sons
- Year
- 2000
- Tongue
- English
- Weight
- 513 KB
- Volume
- 422
- Category
- Article
- ISSN
- 0021-9967
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โฆ Synopsis
A neuron in vivo receives a continuous bombardment of synaptic inputs that modify the integrative properties of dendritic arborizations by changing the specific membrane resistance (R m ). To address the mechanisms by which the synaptic background activity transforms the charge transfer effectiveness (T x ) of a dendritic arborization, the authors simulated a neuron at rest and a highly excited neuron. After in vivo identification of the motoneurons recorded and stained intracellularly, the motoneuron arborizations were reconstructed at high spatial resolution. The neuronal model was constrained by the geometric data describing the numerized arborization. The electrotonic structure and T x were computed under different R m values to mimic a highly excited neuron (1 kOhm.cm 2 ) and a neuron at rest (100 kOhm.cm 2 ). The authors found that the shape and the size of the effective dendritic fields varied in the function of R m . In the highly excited neuron, the effective dendritic field was reduced spatially by switching off most of the distal dendritic branches, which were disconnected functionally from the somata. At rest, the entire dendritic field was highly efficient in transferring current to the somata, but there was a lack of spatial discrimination. Because the large motoneurons are more sensitive to variations in the upper range of R m , they switch off their distal dendrites before the small motoneurons. Thus, the same anatomic structure that shrinks or expands according to the background synaptic activity can select the types of its synaptic inputs. The results of this study demonstrate that these reconfigurations of the effective dendritic field of the motoneurons are activity-dependent and geometry-dependent.
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