There’s a new BOSS in town
BOSS is a standalone software package that facilitates offline spike sorting. It enables you to read continuous and neural-event data contained in a variety of file formats. Features include preprocessing signals, extracting action potentials from continuous data, calculating waveform features and sorting spikes according to state-of-the-art classification algorithms. Researchers can manually edit results and calculate statistics.
Neural signal data analysis has never been so simple and intuitive
The primary goal when developing BOSS was to make it intuitive and easy to understand for novice users. Even those new to spike sorting will find BOSS’ stepwise process to spike sorting gets them quickly up to speed due to its process-oriented organization and prioritization of relevant information at each process stage. The customizable user interface enables multiple researchers to share a system, each using a configuration most comfortable for her or him.
Greater speed, enhanced workflow
BOSS significantly expedites workflow because large files do not need to be split into pieces to work with. Close the program at anytime and continue right where you left off. BOSS saves the session state, enabling you to take breaks in sorting or work on another data set.
BOSS makes full use of the latest multi-core processors and performs many features in the background. This means you can move swiftly from loading an extremely large file to extracting spikes and sorting them without delay. BOSS easily loads any file size with no impact on front-end performance, an unparalleled capability.
BOSS key features & benefits
Intuitive and user friendly
Wizard-assisted sorting and extraction
Fully customizable user interface
Multi-platform (OS X, Windows, Linux)
Automatically saves file editing sessions for easy data analysis continuation after interruptions
Background thread for detection and sorting keeps user interface performance uncompromised
Background organization of data increases processing speed
Large file support
Manual and automated sorting algorithms including T-Distribution EM, K-Means and Manual Editing
Automatic estimation of most relevant feature spaces for faster and more accurate sorting
Allows saving and loading detection and sorting parameters to easily set up the environment for similar experiments across files
Minimum system requirements
|OS||Mac OS10, Windows® 7|
|CPU||≥ 4 physical cores at 2GHz|
|Hard drive||1TB 3Gbit/s SATA II HDD|
|Display||Video card with full OpenGL compatibility|