v1.1

• Ensure compatibility with macOS for CaliAli.
• Fix syntax errors to make CaliAli compatible with various operating systems.

Revised Statement:
MATLAB 2024a is currently not compatible with CaliAli on Windows. Compatibility with macOS has been addressed in the latest update. Some syntax errors that previously hindered CaliAli's suitability for other operating systems have been resolved.

v1.0.1

CaliAli 1.0.1 Release Notes

• Introduced a new app for determining optimal blood vessel (BV) size.
• Removed unnecessary or deprecated functions.
• Several improvements to the documentation.

Full Changelog: v1.0...v1.0.1

v1.0

CaliAli Stable Version 1.0 Release Notes

We are excited to announce the first stable version of CaliAli, featuring significant enhancements and improvements. Below are the key changes in this release:

Changes:

• Full Online Documentation: Access comprehensive documentation to guide you through using CaliAli efficiently.

• Optimized Computational Performance: CaliAli is now optimized for low memory requirements, ensuring smoother and more efficient processing.

• Improved Session Analysis: Analyze individual sessions and perform multisession concatenation seamlessly.

• Enhanced Blood Vessel (BV) Extraction: Minimized vignetting artifacts for improved accuracy in BV extraction.

• New BV Stability Metric: Evaluate tracking performance with a new stability metric integrated into BV extraction.

• Bug Fixes in GUIs: Addressed several bugs in the graphical user interfaces (GUIs) for improved usability.

• Enhanced Inter-Session Alignment: Further improvements to the inter-session alignment module for precise video session alignment.

For a complete list of changes, please refer to the Full Changelog on GitHub.

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This release of CaliAli marks a significant milestone, offering enhanced functionality and improved performance for extracting neural signals from multi-session calcium imaging data.

CaliAli v1-beta

CaliAli Beta Release

The first beta release of CaliAli is now available, offering advanced capabilities for extracting neural signals from one-photon calcium imaging data in free-moving conditions.

For details, refer to the BioRxiv preprint.

Explore CaliAli to analyze calcium imaging data with accuracy and efficiency, shaping the future of neural signal extraction in neuroscience research.