Neurons can encode information using the rate of their action potentials, making the relation between input rate and output rate a prominent feature of neuronal information processing. This relation, known as I{O function, can rapidly change in response to various factors or neuronal processes. Most noticeably, a neuron can undergo a multiplicative operation, resulting in a change of the slope of its I{O curve, also know as gain change. Gain changes represent multiplicative operations, and they are wide- spread. They have been found to play an important role in the encoding of spatial location and coordinate transformation, to signal amplification, and other neuronal functions. One of the factors found to introduce and control neuronal gain is synaptic Short Term Depression (STD). We use both integrate-and- re and conductance based neuron models to identify the effect of STD in excitatory and inhibitory modulatory input. More specifically, we are interested in the effect of STD at the inhibitory synapse from Purkinje cells to cerebellar nucleus neurons. Using a previously published, biologically realistic model, we find that the presence of STD results in a gain change. Most importantly we identify STD at the inhibitory synapse to enable excitation-mediated gain control. To isolate the mechanism that allows excitation to control gain, even though STD is applied at a different synapse, we first show that the overall effect is mediated by average conductance. Having done this, we find that the effect of STD is based on the non-linearity introduced in the relation between input rate and average conductance. We find this effect to vary, depending on the position of the I{O function on the input rate axis. Modulatory input shifts the I{O curve along the input rate axis, consequently shifting it to a position where STD has a different effect. The gain differences in the STD effects between the two positions enable excitation to perform gain control.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:686144 |
| Date | January 2016 |
| Creators | Bampasakis, Dimitris |
| Publisher | University of Hertfordshire |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://hdl.handle.net/2299/17179 |
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