Tensorpac

Tensorpac analyzes Phase-Amplitude Coupling (PAC) in neurophysiological data to quantify cross-frequency interactions of neural oscillations relevant to multi-scale integration and cognitive processes.

Key Features:

• Computational Efficiency: Leverages tensor computations combined with parallel computing techniques to accelerate PAC analyses on large datasets.
• Comprehensive Methodological Implementation: Integrates a wide array of established PAC methods within a single package to facilitate comparative studies and method validation.
• Statistical Analysis Capabilities: Provides statistical tools for analyzing PAC measures to assess reliability and validity of results.
• Advanced Visualization: Offers extended visualization capabilities for exploration and presentation of PAC data.
• Mitigation of Spurious Results: Addresses issues related to spurious PAC arising from varying signal properties and analysis parameters.

Scientific Applications:

• Cross-frequency interaction analysis: Quantifies phase–amplitude coupling between neural oscillations to study cross-frequency interactions.
• Neural integration studies: Supports investigation of multi-scale integration mechanisms in the brain relevant to cognitive processes.
• Large-scale electrophysiology: Enables PAC analysis on large and complex electrophysiological datasets.
• Method comparison and validation: Facilitates comparative studies and validation of PAC estimation methods.

Methodology:

Implements tensor computations and parallel computing techniques to compute Phase-Amplitude Coupling using a variety of established PAC methods, accompanied by statistical analyses and visualization of PAC measures.