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SynapTrack: An automated tool for synapse quantification.

Created on 06 Aug 2026

Authors

Carlos Gallego-García, Elena Martínez-Blanco, F Javier Díez-Guerra

Published in

Journal of microscopy. Aug 06, 2026. Epub Aug 06, 2026.

Abstract

Reliable synapse quantification remains challenging, particularly in high-throughput fluorescence imaging workflows. Here we present SynapTrack, a fully automated FIJI/ImageJ-based tool for quantifying synapses in cultured neurons and brain tissue sections with minimal user intervention. SynapTrack combines channel-specific preprocessing, background subtraction, and SynQuant-based detection of colocalised pre- and postsynaptic puncta. In cultured neurons, it additionally measures cell number and total dendritic length, enabling normalisation of synapse counts per cell and per 10 micrometer of dendrite. Using hippocampal cultures, SynapTrack reliably quantified excitatory and inhibitory synapses, captured the expected predominance of excitatory contacts, and reduced inter-sample variability through structural normalisation. Compared with SynBot, SynapTrack detected more synapses while better preserving biologically meaningful differences between synapse types. For tissue sections, in which cell counting and dendritic segmentation are impractical, we developed SynapTrack_Tissue, an adapted workflow based on presynaptic-postsynaptic colocalisation alone. Despite the lack of cellular normalisation, this approach produced stable measurements across heterogeneous neuropil regions. Because all spatial parameters are defined in micrometres, analysis settings are portable across imaging systems. SynapTrack therefore provides a standardised and scalable framework for synapse quantification in both cultured neurons and tissue sections.

PMID:
42560141
Bibliographic data and abstract were imported from PubMed on 06 Aug 2026.

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