Use this skill when writing code that uses the NeMoS (Neural Models and Statistics) Python package for fitting Generalized Linear Models (GLMs) to neuroscience data. Covers basis functions, single-neuron and population GLMs, observation models (Poisson, Gaussian, Gamma), regularization, cross-validation with scikit-learn, and encoding/decoding analyses. Use when the user mentions NeMoS, nmo, GLM fitting for neural data, basis functions for neural modeling, or population GLMs.