Statistical Significance Analysis of Functional Connectivity Measurements of the Brain

New optical methods for measuring and manipulating neural activity in the brain promise unprecedented insights into how signals propagate through a biological neural network at brain scale and single neuron resolution. However, the scale of these large-scale measurements poses challenges for interpretation. We recently measured how neural signals propagate in the nematode Caenorhabditis elegans by systematically activating individual neurons in the head and measuring the neural network's response at cellular resolution. The resulting dataset contains 10,438 measurements of neural responses to stimulation measured across 43 animals. The scale of the measurements requires a rigorous statistical framework in order to exclude apparent neural responses that could likely be attributed to random chance. Here we discuss a statistical framework for accurately conveying our confidence in attributing one neuron's response to the activation of another.