NetPlotBrain: A Python package for visualizing networks and brains.

Area of Science:

• Neuroimaging
• Network Theory
• Data Visualization

Background:

• Network visualizations are complex, multidimensional, and information-rich, making accurate and effective figure generation challenging.
• The layout of network visualizations is crucial for conveying network or spatial properties.
• Generating high-quality network plots often requires expert knowledge and significant time.

Purpose of the Study:

• Introduce NetPlotBrain, a Python package for creating network visualizations on brain images.
• Provide a user-friendly interface for customizing and highlighting network results.
• Ensure plot accuracy through integration with TemplateFlow and other Python software.

Main Methods:

• Developed NetPlotBrain as a Python package compatible with Python 3.9+.
• Integrated NetPlotBrain with TemplateFlow for accurate spatial referencing.
• Enabled integration with NetworkX and network-based statistics implementations.

Main Results:

• NetPlotBrain offers a high-level interface for easy customization of network plots.
• The package ensures plot accuracy via TemplateFlow integration.
• Facilitates seamless integration with existing neuroimaging and network analysis software.

Conclusions:

• NetPlotBrain is a versatile and user-friendly package for generating high-quality network figures on brain images.
• It simplifies complex visualization tasks in neuroimaging and network theory research.
• Promotes accurate and reproducible network visualizations within the open research community.