A computational model of a midbrain dopamine neuron was extended in this study to include a response to random excitatory afferent input by incorporating the receptor components AMPA and NMDA. In a diagonal band where average glutamatergic and tonic gabaergic input is roughly balanced, both single spike firing and bursting can be observed. Simulated SK channel block strengthens the correlation between pattern and rate and increases the number of spikes fired in bursts by increasing the spikes per burst. A simulated doubling of the AMPA/NMDA ratio leads to a frequency increase that becomes more prominent at high firing rates, and an increase in the percent spikes fired in bursts. Changes in pattern and rate are poorly correlated in the model. Manipulations of the neuron greatly depend on the background level of synaptic inputs, suggesting that interpretation of population data from dopamine neurons requires taking variability into account rather than averages.