The goal of this project was to examine whether the topology of the structural connectome—which we index using an undirected description of connectivty—confers asymmetries in signal propagation across the cortical hierarchy of cytoarchitecture. We use Network Control Theory to model state transitions that span the sensory-fugal axis of cytoarchitectonic similarity and examine whether and how dynamics differed for bottom-up state transitions compared to top-down.
The preprint for this work can be found here:
Asymmetric Signaling Across the Hierarchy of Cytoarchitecture within the Human Connectome. Linden Parkes, Jason Z Kim, Jennifer Stiso, Monica E Calkins, Matthew Cieslak, Raquel E Gur, Ruben C Gur, Tyler M Moore, Mathieu Ouellet, David R Roalf, Russell T Shinohara, Daniel H Wolf, Theodore D Satterthwaite, Dani S Bassett bioRxiv 2022.05.13.491642; https://www.biorxiv.org/content/10.1101/2022.05.13.491642v1
Also see the following YouTube video for a short animation describing this work: https://www.youtube.com/watch?v=cbnS6WamXzE
Python scripts that produce the figures from the above manuscript can be found in scripts. Many of these figure
scripts are supported by additional scripts that run on our cluster at Penn. Those scripts are stored here for documentation
purposes. However, the main results_figX.py scripts were designed to run with or without the outputs
from these cluster scripts. Of course, some of them will have much longer run times without the cluster outputs.
We also include results_demo.ipynb that walks through the main set of findings from the paper and links the equations
in the text to the functions in this repository.