Visual cortex and motor cortex lie at opposing ends of the braina**s processing pathway. The goal of visual cortex is to compute representations of its input. The goal of primary motor cortex is to generate movementa**the braina**s output. Here, we analyze datasets from both areas. All data is arranged in a neuron by stimulus by time tensor. We show how the a**tensor structurea** of the data can reveal fundamentally different computational strategies employed by both areasa**namely, whether an area encodes external variables or acts as a dynamical system. I will also include my current attempts on applying persistent homology and mapper to the data, as well try to gear the talk toward the question, "How might TDA be helpful for this type of data?"