The Brain Activity Flow ("Actflow") Toolbox. Tools to quantify the relationship between connectivity and task activity through network simulations and machine learning prediction. Helps determine how connections contribute to specific brain functions.

Repository for Sanchez-Romero, R., & Cole, M. W. (2021). "Combining multiple functional connectivity methods to improve causal inferences". Journal of cognitive neuroscience, 33(2), 180-194. https://doi.org/10.1162/jocn_a_01580

Code to perform FWE-correction for multiple comparisons using permutation testing (see Nichols & Holmes, 2001)

Repository for Sanchez-Romero, R., Ito, T., Mill, R. D., Hanson, S. J., & Cole, M. W. (2023). "Causally informed activity flow models provide mechanistic insight into network-generated cognitive activations". NeuroImage, 120300. https://doi.org/10.1016/j.neuroimage.2023.120300

Code for running simulations and data analysis from: Cole MW, Ito T, Schultz D, Mill R, Chen R, Cocuzza C (2019). "Task activations produce spurious but systematic inflation of task functional connectivity estimates". NeuroImage. doi:10.1016/j.neuroimage.2018.12.054 https://authors.elsevier.com/a/1YNWs3lc~r3Jbx

Code release for McCormick et al. (2022): McCormick EM*, Arnemann KL*, Ito T, Hanson SJ, Cole MW (2022). "Latent functional connectivity underlying multiple brain states". Network Neuroscience; 6 (2): 570–590 doi:10.1162/netn_a_00234 [* = equal contribution]

Publicly available code for "A flexible hub connectivity mechanism for cognitive control". Manuscript in-preparation. Part of C. Cocuzza's dissertation (Aim 3).

Publicly available code for "Distributed network processes account for the majority of variance in localized visual category selectivity", Cocuzza et al., 2022.

Code for: "Flexible coordinator and switcher hubs for adaptive task control". Cocuzza et al., 2020 (In Press). Journal of Neuroscience.