Abstract
The quantification of synapses is instrumental to measure the evolution of synaptic densities of neurons under the effect of some physiological conditions, neuronal diseases or even drug treatments. However, the manual quantification of synapses is a tedious, error-prone, time-consuming and subjective task; therefore, reliable tools that might automate this process are desirable. In this paper, we present SynapCountJ, an ImageJ plugin, that can measure synaptic density of individual neurons obtained by immunofluorescence techniques, and also can be applied for batch processing of neurons that have been obtained in the same experiment or using the same setting. The procedure to quantify synapses implemented in SynapCountJ is based on the colocalization of three images of the same neuron (the neuron marked with two antibody markers and the structure of the neuron) and is inspired by methods coming from Computational Algebraic Topology. SynapCountJ provides a procedure to semi-automatically quantify the number of synapses of neuron cultures; as a result, the time required for such an analysis is greatly reduced. The computations performed by SynapCountJ have been validated by comparing the results with those of a formally verified algorithm (implemented in a different system).
This work was supported by the Ministerio de Economía y Competitividad projects [MTM2013-41775-P, MTM2014-54151-P, BFU2010-17537]. G. Mata was also supported by a PhD grant awarded by the University of La Rioja [FPI-UR-13].
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Mata, G., Cuesto, G., Heras, J., Morales, M., Romero, A., Rubio, J. (2017). SynapCountJ: A Validated Tool for Analyzing Synaptic Densities in Neurons. In: Fred, A., Gamboa, H. (eds) Biomedical Engineering Systems and Technologies. BIOSTEC 2016. Communications in Computer and Information Science, vol 690. Springer, Cham. https://doi.org/10.1007/978-3-319-54717-6_3
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