Computational analysis of firing regularity and burst firing in midbrain dopamine neurons

Abstract

Dopamine neurons in the substantia nigra pars compacta (SNc) and ventral tegmental area (VTA) regulate day-to-day activities such as reward-related learning, and motor control. Dysfunction of these neurons is implicated in disorders like Schizophrenia, addiction to drugs, and Parkinson’s disease. Dopamine neurons fire action potentials with variability in inter-spike intervals (ISI) interspersed with bursts of spikes, both firing patterns being a result of co-ordinated action of synaptic inputs and ion channels. Pharmacological inhibition of calcium-activated potassium (SK) channels increases the variability in their firing pattern, sometimes also increasing the number of spikes fired in bursts, indicating that SK channels play an important role in maintaining dopamine neuron firing regularity and burst firing. However, the exact mechanisms underlying these effects are still unclear. We hypothesized that the post-spike after hyperpolarisation (AHP) provided by the SK current controls and standardises the availability of other voltage-gated ion channels, thus timing successive action potentials at regular intervals. Here, I develop a biophysical model of a dopamine neuron incorporating ion channel stochasticity that enabled me to analyse availability of ion channels in multiple states during spiking. Decreased firing regularity is primarily due to a significant decrease in the AHP that in turn resulted in a reduction in the fraction of available voltage-gated sodium channels. Insufficient AHP causes a failure of sodium channels to recover from inactivation and, due to ion channel stochasticity, a variable number of sodium channels are available to fire a spike, in the absence of AHP, thus resulting in an irregular spike train. My model further predicts that inhibition of SK channels results in a depolarisation of action potential threshold along with an increase in its variability, thus suggesting that SK channels regulate spike threshold in midbrain dopamine neurons.

Moreover, a quantitative description of action potential features during endogenous burst firing in midbrain dopamine neurons has not been reported, perhaps due to a lack of in vivo whole-cell recordings that can shed light on membrane dynamics. Because we had available in vivo whole-cell recordings from immuno-histochemically identified dopamine neurons in the VTA, I analysed these using mathematical techniques like Principal Components Analysis (PCA) and the stochastic model mentioned above, in order to provide quantitative descriptions of action potential features during the course of endogenous burst firing. I found that the first detectable change in membrane dynamics that perhaps leads to burst firing is a reduction in the AHP mediated by SK channels. This was accompanied by progressive depolarisation of action potential threshold with each spike within the burst due to reduced availability of sodium channels as a result of progressive decrease in recovery from inactivation. This also resulted in a decrease in rate of change of membrane voltage for each successive spike in a burst. Reduction in action potential height that is commonly observed during burst firing can also be explained by the reduced availability of sodium channels. My model predicts that a reduction in A-type potassium channel current during burst firing could facilitate the transient increase in instantaneous firing rate during bursts and the progressive reduction in sodium channel availability results in the cessation of firing, facilitating burst termination in these neurons.