Volumetric Electron Microscopy Brain Data for Connectomics

18.2 GB of high-resolution volumetric electron microscopy data demonstrates a novel, cost-effective method for collecting thousands of ultrathin brain sections. The dataset provides synaptic-resolution image data for brain mapping and connectomics research, created by author Gregg Wildenberg and last updated in March 2026.

Use Cases

• Analyze synaptic-resolution image data for brain mapping and connectomics applications.
• Apply the novel ultramicrotome-based collection method to benchmark volumetric electron microscopy techniques.
• Use the high-quality image data to train segmentation models for neuronal structures.

Strengths

• Large-scale dataset at 18.2 GB, suitable for training complex models.
• Data is collected using a novel method designed to make volumetric electron microscopy easier and cheaper.
• High-quality image data captured at synaptic resolution for detailed analysis.

Limitations

• Specific row and column counts are unknown, limiting precise assessment of dataset scale.
• The dataset is an example collection, which may not represent the full scope of the described method.
• No sample data or column schema is provided to preview the data structure.

Provenance

Source

figshare

Collection Method

Collected using a novel method for producing thousands of ultrathin sections for volumetric electron microscopy.

Freshness

Last updated on 2026-03-23.