Spike Train Correlation in Random Walk Integrate and Fire Neurons Jonathan W. Yu 10.1184/R1/6686381.v1 https://kilthub.cmu.edu/articles/thesis/Spike_Train_Correlation_in_Random_Walk_Integrate_and_Fire_Neurons/6686381 <p>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.</p> 2014-04-29 00:00:00 Spike Train Correlation in Random Walk Integrate and Fire Neurons poisson process