Thus far, I have evaluated the approach developed here conceptually, but the goal is to apply the methods to actual data. Before applying a new approach to a new domain, though, it must first be evaluated on datasets where the true relationships are known. This chapter discusses two types of applications: validation on simulated neuronal and financial time series (to determine how well the algorithms can recover known causes) and experimentation on financial time series (to discover novel relationships).
7.1. Simulated Neural Spike Trains
We begin our study of applications with synthetically generated neural spike trains. The underlying relationships here are simple (one neuron causing another to fire in some predefined window ...