The ultimate goal of neuroscience is to relate the complex activity of cells and cell-networks to behavior and cognition. This requires tools and techniques to visualize neuronal activity. Fluorescence microscopy is an ideal tool to measure activity of cells in the brain due to the high sensitivity of the technique and the growing portfolio of optical hardware and fluorescent sensors. Here, we give a chemist's perspective on the recent progress of fluorescent activity indicators that enable the measurement of cellular events in the living brain. We discuss advances in both chemical and genetically encoded sensors and look forward to hybrid indicators, which incorporate synthetic organic dyes into genetically encoded protein constructs.

Single-particle tracking (SPT) has become an important method to bridge biochemistry and cell biology since it allows direct observation of protein binding and diffusion dynamics in live cells. However, accurately inferring information from SPT studies is challenging due to biases in both data analysis and experimental design. To address analysis bias, we introduce 'Spot-On', an intuitive web-interface. Spot-On implements a kinetic modeling framework that accounts for known biases, including molecules moving out-of-focus, and robustly infers diffusion constants and subpopulations from pooled single-molecule trajectories. To minimize inherent experimental biases, we implement and validate stroboscopic photo-activation SPT (spaSPT), which minimizes motion-blur bias and tracking errors. We validate Spot-On using experimentally realistic simulations and show that Spot-On outperforms other methods. We then apply Spot-On to spaSPT data from live mammalian cells spanning a wide range of nuclear dynamics and demonstrate that Spot-On consistently and robustly infers subpopulation fractions and diffusion constants.