Lagged Hilbert autocoherence

Lagged Hilbert autocoherence, phase-locking value, and amplitude autocoherence. Library accompanying the paper Zhang et al. (2024) "Multi-scale parameterization of neural rhythmicity with lagged Hilbert autocoherence"

https://www.biorxiv.org/content/10.1101/2024.12.05.627017v2.abstract

Requirements

python version: joblib, scipy, numpy, statsmodels (>=0.13.5)

matlab version: parallel processing toolbox, signal processing toolbox

Python files

• lagged_autocoherence.py: core functions
• demo.ipynb: demonstration of the new lagged autocoherence algorithm
• multi_trial_demo.ipynb: demonstration of new lagged autocoherence algorithm with multiple trials
• sims.ipynb: tests with simulated data
• meg_sensor_data.ipynb: analysis of MEG sensor data
• lfp_data.ipynb: analysis of LFP monkey data

Matlab files

• lagged_hilbert_autocoherence.m: core function
• ar_surr.m: ARMA surrogate data generation
• demo.m: demonstration of new lagged autocoherence algorithm
• multi_trial_demo.m: demonstration of new lagged autocoherence algorithm with multiple trials
• rfft.m: Fourier transform of real signal
• irfft.m: inverse Fourier transform of real signal
• hilbert.m: hilbert transform