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Related Experiment Video

Updated: Nov 26, 2025

Correlative Microscopy for 3D Structural Analysis of Dynamic Interactions
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Targeting Functionally Characterized Synaptic Architecture Using Inherent Fiducials and 3D Correlative Microscopy.

Connon I Thomas1, Melissa A Ryan1, Benjamin Scholl2

  • 1Electron Microscopy Core Facility, Imaging Center, Max Planck Florida Institute for Neuroscience, 1 Max Planck Way, Jupiter, FL33458, USA.

Microscopy and Microanalysis : the Official Journal of Microscopy Society of America, Microbeam Analysis Society, Microscopical Society of Canada
|December 11, 2020
PubMed
Summary

This study presents a new workflow combining light and electron microscopy to analyze neural circuits. It enables detailed examination of synaptic connections in the ferret visual cortex.

Keywords:
3D CLEMEM-label-freeSBF-SEMin vivo 2-photon microscopyneuronal circuits

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Area of Science:

  • Neuroscience
  • Microscopy
  • Circuitry

Background:

  • Neuronal circuits are complex 3D structures with components varying in size.
  • Light microscopy (LM) visualizes neuronal activity, while electron microscopy (EM) is essential for synaptic connection resolution.

Purpose of the Study:

  • To develop a workflow correlating in vivo two-photon LM with volumetric scanning EM (SEM).
  • To enable quantitative characterization of synaptic ultrastructure in functionally imaged neurons.

Main Methods:

  • Established an EM-label-free workflow using inherent structural features for correlation.
  • Optimized volumetric SEM sample preparation, imaging with the OnPoint detector, and focal charge compensation.
  • Achieved high resolution and signal-to-noise ratio for analyzing hundreds of synapses.

Main Results:

  • Successfully correlated two-photon LM and volumetric SEM in ferret visual cortex.
  • Enabled analysis of synaptic ultrastructure in large sample volumes.
  • Provided a reliable method for quantitative synaptic analysis.

Conclusions:

  • The novel workflow reliably characterizes synaptic ultrastructure in functionally imaged neurons.
  • Offers new insights into neuronal circuit organization.
  • Combines the advantages of LM and EM for comprehensive neural feature analysis.