A novel estimation method for the counting of dendritic spines

Background: Since Cajal's visualisations of the synaptic spine, this feature of the neuron has been of interest to neuroscientists and has been investigated usually in reference to degeneration or proliferation of dendrites and their neurons. Synaptic spine measurement often forms a critical element of any study investigating neuronal morphology. However, the way researchers have counted spines hasn't changed for almost a century. Some of the currently used legacy methods fail to accommodate obscured spines or factor-in visibility differences between histological stains. New method: Here we investigate the neuronal dendrite and its synaptic spines, and reveal that using confocal or bright-field technologies may in fact obfuscate spine counts. A mathematical model is developed for the distribution of synaptic spines within the rat, that should, by nature of the formula and the impartiality of probability quotients, be applied to estimate the number of synaptic spines across any length of dendrite that has protrusions within any species.Results: Using this estimation method, we show that, depending on the method of image capture, there are in fact more spines present than typically counted on lengths of dendrite, something that may have biased morphological studies in the past.Comparison with existing methods: This new estimation method has been collapsed down into an easy-to-use free website. With input of only four fields, we provide the researcher with a more accurate estimation of the amount of spines on a length of dendrite. This was made possible by fluorescing a Golgi stain and comparing two-photon, bright-field and confocal images.Conclusions: An easy web-based resource has been made available to use this new method for spine calculation. Using this method improves the validity of spine measurement and provides a means to review previously published work.

Automated summary

This study investigates the dendrites of neuronal cells and the synaptic spines associated with them, highlighting the possibility of inaccurate counting due to the use of certain imaging technologies. By developing a mathematical model, the researchers propose a more unbiased estimation method for quantifying the number of spines on dendrites. Using this new method, the study reveals that previous studies may have been biased in their morphological analysis. The researchers have created a user-friendly website where researchers can input data to obtain more accurate estimates of spine counts. This method improves the validity of spine measurement and allows for a reevaluation of previously published work.