Search Results for author: Theodore D. Satterthwaite

Found 8 papers, 1 papers with code

Compression supports low-dimensional representations of behavior across neural circuits

no code implementations29 Nov 2022 Dale Zhou, Jason Z. Kim, Adam R. Pines, Valerie J. Sydnor, David R. Roalf, John A. Detre, Ruben C. Gur, Raquel E. Gur, Theodore D. Satterthwaite, Dani S. Bassett

Using a large sample of youth ($n=1, 040$), we test predictions in two ways: by measuring the dimensionality of spontaneous activity from sensorimotor to association cortex, and by assessing the representational capacity for 24 behaviors in neural circuits and 20 cognitive variables in recurrent neural networks.

Association Dimensionality Reduction

A structurally informed model for modulating functional connectivity

no code implementations24 Aug 2022 Andrew C. Murphy, Romain Duprat, Theodore D. Satterthwaite, Desmond J. Oathes, Dani S. Bassett

For each individual, we measured the TMS-induced change in FC between the FPS and DMS (the FC network), and the structural coupling between the stimulated area and the FPS and DMS (the structural context network (SCN)).

Efficient Coding in the Economics of Human Brain Connectomics

1 code implementation14 Jan 2020 Dale Zhou, Christopher W. Lynn, Zaixu Cui, Rastko Ciric, Graham L. Baum, Tyler M. Moore, David R. Roalf, John A. Detre, Ruben C. Gur, Raquel E. Gur, Theodore D. Satterthwaite, Danielle S. Bassett

In doing so, we introduce the metric of compression efficiency, which quantifies the trade-off between lossy compression and transmission fidelity in structural networks.

Extraction of hierarchical functional connectivity components in human brain using resting-state fMRI

no code implementations19 Jun 2019 Dushyant Sahoo, Theodore D. Satterthwaite, Christos Davatzikos

This paper provides a novel method for the extraction of hierarchical connectivity components in the human brain using resting-state fMRI.

Community Detection

Influence of Neighborhood SES on Functional Brain Network Development

no code implementations20 Jul 2018 Ursula A. Tooley, Allyson P. Mackey, Rastko Ciric, Kosha Ruparel, Tyler M. Moore, Ruben C. Gur, Raquel E. Gur, Theodore D. Satterthwaite, Danielle S. Bassett

We quantitatively characterize this topology using a local measure of network segregation known as the clustering coefficient, and find that it accounts for a greater degree of SES-associated variance than meso-scale segregation captured by modularity.

Neurons and Cognition

Brain Age Prediction Based on Resting-State Functional Connectivity Patterns Using Convolutional Neural Networks

no code implementations11 Jan 2018 Hongming Li, Theodore D. Satterthwaite, Yong Fan

Whole brain voxel-wise FC measures could provide fine-grained FC information of the brain and may improve the prediction performance.

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