Authors:
Gadea Mata
1
;
Jónathan Heras
1
;
Miguel Morales
2
;
Ana Romero
1
and
Julio Rubio
1
Affiliations:
1
Universidad de La Rioja, Spain
;
2
Universitat Autònoma de Barcelona, Spain
Keyword(s):
Synapses, Synaptic Density, Image Processing, ImageJ.
Related
Ontology
Subjects/Areas/Topics:
Bioimaging
;
Biomedical Engineering
;
Confocal Microscopy
;
Feature Recognition and Extraction Methods
;
Image Processing Methods
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, 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 quan
tify the number of synapses of neuron cultures; as a result, the time
required for such an analysis is greatly reduced.
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