- Poster presentation
- Open Access
Model of hyperpolarization dependent LTD in MVN neurons
© Graham et al; licensee BioMed Central Ltd. 2009
- Published: 13 July 2009
- Calcium Influx
- Tissue Slice
- Deep Cerebellar Nucleus
- Membrane Hyperpolarization
- Cell Patch Clamp
The cell model contained 61 electrical compartments, comprising the cell body and four dendrites. A variety of ionic conductances, including low- and high-voltage-activated calcium conductances, were distributed non-uniformly across the cell membrane. Calcium influx, buffering and extrusion were modeled in every cell compartment. Full details of the model can be found in . For the simulations described here, the model was modified and extended from  as follows. The density of LVA calcium channels and persistent sodium channels were reduced to match the excitability of the cells recorded in slice preparations. An AMPA/NMDA receptor-mediated excitatory synapse was added to the dendrites. The conductance time course, and voltage dependence in the case of the NMDA component, were set to average values determined for deep cerebellar nucleus cells . Hyperpolarization was achieved either by current injection to the soma, or by an IPSP collocated in the dendrite with the afferent EPSP.
The computer simulations clearly demonstrate that rebound from hyperpolarization results in a transiently enhanced LVA calcium current. During this rebound, calcium influx via NMDA and LVA channels may summate to provide a larger change in calcium than seen either during the hyperpolarization or during stimulation without an accompanying hyperpolarization. For single afferent stimuli, the relative timing of the stimulus with respect to the offset of the hyperpolarization determines the magnitude of the calcium influx. The timings that produced LTD in the tissue slice experiments correspond to mid-range peak calcium, which corresponds to a maximal change in calcium from its level immediately prior to the synaptic stimulation. An intermediate calcium level has been hypothesized to produce LTD by a number of proposed synaptic learning rules .
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