Automated criteria-based selection and analysis of fluorescent synaptic puncta.

The use of fluorescent probes such as FM 1-43 or synapto-pHluorin to study the dynamic aspects of synaptic function has dramatically increased in recent years. The analysis of such experiments is both labor intensive and subject to potentially significant experimenter bias. For our analysis of fluorescently labeled synapses in cultured hippocampal neurons, we have developed an automated approach to punctum identification and classification. This automatic selection and processing of fluorescently labeled synaptic puncta not only reduces the chance of subjective bias and improves the quality and reproducibility of the analyses, but also greatly increases the number of release sites that can be rapidly analyzed from a given experiment, increasing the signal-to-noise ratio of the data. An important innovation to the automation of analysis is our method for objectively selecting puncta for analysis, particularly important for studying and comparing dynamic functional properties of a large population of individual synapses. The fluorescence change for each individual punctum is automatically scored according to several criteria, allowing objective assessment of the quality of each site. An entirely automated and thus unbiased analysis of fluorescence in the study of synaptic function is critical to providing a comprehensive understanding of the cellular and molecular underpinnings of neurotransmission and plasticity.