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Computer assisted detection of axonal bouton structural plasticity in in vivo time-lapse images

Published ineLife, vol. 6
Publication date2017
Abstract

The ability to measure minute structural changes in neural circuits is essential for long-term in vivo imaging studies. Here, we propose a methodology for detection and measurement of structural changes in axonal boutons imaged with time-lapse two-photon laser scanning microscopy (2PLSM). Correlative 2PLSM and 3D electron microscopy (EM) analysis, performed in mouse barrel cortex, showed that the proposed method has low fractions of false positive/negative bouton detections (2/0 out of 18), and that 2PLSM-based bouton weights are correlated with their volumes measured in EM (r = 0.93). Next, the method was applied to a set of axons imaged in quick succession to characterize measurement uncertainty. The results were used to construct a statistical model in which bouton addition, elimination, and size changes are described probabilistically, rather than being treated as deterministic events. Finally, we demonstrate that the model can be used to quantify significant structural changes in boutons in long-term imaging experiments.

Keywords
  • CLEM
  • Bouton detection
  • Bouton volume
  • Mouse
  • Neuroscience
  • Structural plasticity
  • Synaptic strength
  • Time-lapse imaging
Citation (ISO format)
GALA, Rohan et al. Computer assisted detection of axonal bouton structural plasticity in in vivo time-lapse images. In: eLife, 2017, vol. 6. doi: 10.7554/eLife.29315
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Article (Published version)
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ISSN of the journal2050-084X
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