The same set of axons was imaged 7 times within 80 min with various microscope settings and cranial window conditions (inset in A). Putative boutons detected based on the first imaging session (condition A) were chosen to be the gold standard. Precision (A) and recall (B) in bouton detection were measured under the remaining conditions, B-G. Both precision and recall increase with bouton weight. While for very small boutons ( < 2.0, dashed line) detection is unreliable, agreement with the gold standard is achieved across all imaging conditions in 95% of boutons with weights greater than 2.0. Numbers of boutons in the gold standard are indicated next to the data points in (A). Inset in (B) shows an example of one axon segment imaged in conditions A-G. (C) Bouton weights under different imaging conditions are plotted against the gold standard weight. Best fit lines show no significant bias for conditions B and C, however small, but significant reduction in mean bouton weight was observed in the remaining four conditions (all p < 0.03, two-sample t-test). Abbreviations used in the inset of A: LP is laser power in mW, PMT denotes photomultiplier tube voltage in Volts, and WC is cranial window condition, where ‘n’ stands for normal and ‘a’ indicates presence of a thin layer of agarose. Color code used in (A–C) is defined by the inset table in (A). (D) CDFs for differences in bouton weights across imaging conditions. Data from all conditions were pooled. Different lines show CDFs for various intervals of mean bouton weight. (E) Variance in bouton weight difference increases linearly with mean bouton weight (χ2 linear regression with , p = 0.33, α = 0.24 ± 0.01, mean ± s.d.). Error-bars indicate standard deviations obtained with bootstrap sampling with replacement. (F) Red line shows the distribution of true bouton weight for a putative bouton of measured weight = 1.5. Area under the curve to the right of = 2.0 gives = 0.12. Large putative boutons (e.g. blue curve, = 3.0) have high probability of being LM boutons.