A fast and robust method for automated analysis of axonal transport

Cargo movement along axons and dendrites is indispensable for the survival and maintenance of neuronal networks. Key parameters of this transport such as particle velocities and pausing times are often studied using kymograph construction, which converts the transport along a line of interest from a time-lapse movie into a position versus time image. Here we present a method for the automatic analysis of such kymographs based on the Hough transform, which is a robust and fast technique to extract lines from images. The applicability of the method was tested on simulated kymograph images and real data from axonal transport of synaptophysin and tetanus toxin as well as the velocity analysis of synaptic vesicle sharing between adjacent synapses in hippocampal neurons. Efficiency analysis revealed that the algorithm is able to detect a wide range of velocities and can be used at low signal-to-noise ratios. The present work enables the quantification of axonal transport parameters with high throughput with no a priori assumptions and minimal human intervention.