Spike Train Correlation in Random Walk Integrate and Fire Neurons

One way to analyze how our brains function is to apply statistical models to neural data. In 1998, Shadlen and Newsome observed that a balanced random walk integrateand-fire model can model experimental data such as single-unit recordings of rhesus monkeys. Using this model, I study the spike count correlation of two neurons under varying conditions. Through simulations, I look at the relationship of spike count correlation across two neurons to firing input rate when the inputs are independent and correlated. After this step, I look at whether an oscillatory input affects synchrony, i.e., synchronous firing of two neurons in close temporal proximity. It is crucial to understand what affects synchrony as a little change in synchrony can cause huge impacts in cellular processes in the brain and in how neurons communicate with each other.