Mixed-Mode Response of Nigral Dopaminergic Neurons: An in Silico Study on SpiNNaker

We present a work-in-progress on the mixed-mode (burst, non-burst) spiking response of the Substantia-Nigra-pars-compacta (SNc) using a conductance-based Izhikevich's spiking neuron (IZK) model on SpiNNaker. The SNc is a primary source of Dopamine (DA) that is essential for reward-based learning and prediction in the brain and forms a part of the Basal Ganglia (BG). The bursting phases of the mixed-mode facilitate reward-related DA release whereas the non-burst phases maintain the base-levels of DA in the extracellular space. Previously, we have implemented a BG model where the modulatory effects of DA on the network synapses were simulated using static conductances. Recently, we have implemented the time-varying effects of reward-based DA release in a balanced-random-network. However, both these works did not include the SNc population. Here, we present an SNc population simulated on SpiNNaker and parameterised to display mixed-mode response; our goal is to integrate it into the existing BG model. We observe that the IZK model parameter d is crucial for model response transition between the burst and non-burst modes. Furthermore, inhibition play a pivotal role in transition from burst to mixed-mode response as reported in physiological studies. In addition, we have identified the constant current inputs in the model that facilitate mixed-mode response. With appropriate parameterisation of the efferents from the existing BG model to the SNc population, the burst to non-burst ratio in the mixed-mode response conforms to physiological observations. Continuing research is looking into using the SNc population to model reward-based learning and decision-making by the brain.