1. A computer system for analyzing neural response data, the system comprising: a processor, a computer-readable memory, and a computer-readable storage media; the computer-readable storage media comprising a training module and a classifier module, wherein the training module uses a loss function to determine relevant features in a set of neural response training data, identifies a set of optimal weights that produce a minimum for the loss function according to an iterative procedure of setting at least one of the optimal weights to zero and identifying features based on partial derivatives of the loss function, and creates a classifier using the set of optimal weights; the classifier module applies the classifier to a new set of neural response data and calculates, for a data point in the new set of neural response data, a probability that the data point is associated with a class, wherein the class represents an available choice for the neural response data; and the training module and the classifier module are stored on the computer-readable storage media for execution by the processor via the computer-readable memory.