Neurons of the central nervous system rely on finely tuned integrative properties to perform the computations that allow transformation of sensory input into an output. It has long been a goal of neuroscience to understand this computation, in order to grasp the fundamental function of neuronal circuits. In my thesis, I have focused on cerebellar granule cells to dissect the input-output transformation that takes place within a single neuron. The small size of the granule cell together with its limited number of inputs make it an ideal cell in which to study integration of synaptic input. Using whole-cell patch clamp recordings in awake, head-fixed mice I have characterised the input-output transformations that underlie the flow of sensory information through the cerebellar cortex. I found that in the awake state the cerebellum receives a greatly increased amount of synaptic input compared to the anesthetised state. This high frequency input appears to contribute to distinct integrative properties in granule cells, such as a considerably lower input resistance. Surprisingly, despite the dramatically higher rate of excitatory input, output spiking rates in the resting awake state remain similar to the anesthetised state. However, the onset of locomotion was correlated with an increase in spiking, associated with a further increase in excitatory synaptic input. This suggests that these cells may be ‘primed’ to fire explicitly during motor function, allowing transmission of highly filtered sensory information with a very high signal-to-noise ratio. My experiments suggest that glutamatergic spillover may contribute to synaptic transmission during locomotion. Furthermore, spatial segregation of inhibitory inputs or their modulation may also play a role in this function-related firing, but this remains an open question. Together these results represent the first example of relating synaptic input of single cells with the behavioural state of an awake animal.
|Publisher||University College London (University of London)|
|Source Sets||Ethos UK|
|Type||Electronic Thesis or Dissertation|
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