jiversen / DDC

Code for dynamical differential covariance

Dynamical differential covariance (DDC)

Checkout the latest manuscript version through bioRxiv: https://www.biorxiv.org/content/10.1101/2021.06.18.448901v2.full.pdf+html
All scripts were carefully annotated. Below is a quick summary.

Connectivity estimation:

• estimators.m: Common estimators including covariance <x,x>, Precision matrix, nonlinear averaging matrix <R(x),x>, dCov computed by symmetric difference quotient
• dCov_numerical.m: dCov calculated by different numerical estimations of the time derivative
• derivative_123.m: Supporting file for dCov_numerical.m
• DDC calculation: matrix product of dCov and <x,x>^{-1} or <R(x),x>^{-1}

Network simulations:

• Linear_simulation.m: simulation of linear stochastic systems
• Nonlinear_simulation.m: simulation of nonlinear stochastic systems
• LIF_network_YC.m: Leaky-integrate-and-Fire network simulation
• simulate_reduced_wong_wang.ipynb: Reduced Wong-Wang simulation

Performance evaluation:

• FC_GT_ROC.m: classification sensitivity for LIF network recovery
• c_sensitivity_YC.m: c-sensitivity calculation

HCP dataset

• rs-fMRI time series data available through https://www.humanconnectome.org
• dMRI dataset available through https://www.eneuro.org/content/8/1/ENEURO.0416-20.2020/tab-article-info
• ATLAS_HCP_dMRIparcel_to_IC100node_connectivity.m: convert parcel-level dMRI strength to IC-level dMRI strength