NeuroChaT

NeuroChaT provides analysis of neuronal signals recorded in vivo from freely-behaving animals, focusing on single-unit spatial coding, characterization of rhythmic properties and dynamics relative to local field potential signals, and end-to-end data handling using HDF5 for behavioral neurophysiology research.

Key Features:

• Single Unit Analysis and Spatial Coding: Implements analyses of single-unit activity with emphasis on spatial coding in freely-moving animals.
• Rhythmic Properties and Dynamics Characterization: Characterizes rhythmic properties of neuronal units and their dynamics in relation to local field potential signals.
• Complete Analysis Pipeline: Provides an end-to-end analysis pipeline that automates data processing tasks and generates publication-quality figures.
• Data Management with HDF5 Format: Stores raw and analyzed data using the Hierarchical Data Format version 5 (HDF5) for platform-independent data management.

Scientific Applications:

• Behavioral Neurophysiology: Enables studies of neuronal encoding dynamics during natural behaviors in freely-behaving animals, including analyses of spatial information and rhythmic coordination.

Methodology:

Algorithms and analysis routines are implemented in Python and use HDF5 to store raw and processed data.