1.9k citations · 2.8k across the 15 of their papers we have counts for
10 papers · 1 filter
A Matrix Autoencoder Framework to Align the Functional and Structural Connectivity Manifolds as Guided by Behavioral Phenotypes
Niharika Shimona D'Souza, Mary Beth Nebel, Deana Crocetti +4
We propose a novel matrix autoencoder to map functional connectomes from resting state fMRI (rs-fMRI) to structural connectomes from Diffusion Tensor Imaging (DTI), as guided by su…
A Joint Network Optimization Framework to Predict Clinical Severity from Resting State Functional MRI Data
Niharika Shimona D'Souza, Mary Beth Nebel, Nicholas Wymbs +2
We propose a novel optimization framework to predict clinical severity from resting state fMRI (rs-fMRI) data. Our model consists of two coupled terms. The first term decomposes th…
Brain State Flexibility Accompanies Motor-Skill Acquisition
Pranav G. Reddy, Marcelo G. Mattar, Andrew C. Murphy +4
Learning requires the traversal of inherently distinct cognitive states to produce behavioral adaptation. Yet, tools to explicitly measure these states with non-invasive imaging --…
Explicitly Linking Regional Activation and Function Connectivity: Community Structure of Weighted Networks with Continuous Annotation
Andrew C. Murphy, Shi Gu, Ankit N. Khambhati +4
A major challenge in neuroimaging is understanding the mapping of neurophysiological dynamics onto cognitive functions. Traditionally, these maps have been constructed by examining…
Structural Pathways Supporting Swift Acquisition of New Visuo-Motor Skills
Ari E. Kahn, Marcelo G. Mattar, Jean M. Vettel +3
Human skill learning requires fine-scale coordination of distributed networks of brain regions that are directly linked to one another by white matter tracts to allow for effective…
Graph Frequency Analysis of Brain Signals
Weiyu Huang, Leah Goldsberry, Nicholas F. Wymbs +3
This paper presents methods to analyze functional brain networks and signals from graph spectral perspectives. The notion of frequency and filters traditionally defined for signals…
Learning-Induced Autonomy of Sensorimotor Systems
Danielle S. Bassett, Muzhi Yang, Nicholas F. Wymbs +1
Distributed networks of brain areas interact with one another in a time-varying fashion to enable complex cognitive and sensorimotor functions. Here we use novel network analysis a…
Task-Based Core-Periphery Organisation of Human Brain Dynamics
Danielle S. Bassett, Nicholas F. Wymbs, M. Puck Rombach +3
As a person learns a new skill, distinct synapses, brain regions, and circuits are engaged and change over time. In this paper, we develop methods to examine patterns of correlated…
Dynamic Network Centrality Summarizes Learning in the Human Brain
Alexander V. Mantzaris, Danielle S. Bassett, Nicholas F. Wymbs +5
We study functional activity in the human brain using functional Magnetic Resonance Imaging and recently developed tools from network science. The data arise from the performance o…
Dynamic reconfiguration of human brain networks during learning
Danielle S. Bassett, Nicholas F. Wymbs, Mason A. Porter +3
Human learning is a complex phenomenon requiring flexibility to adapt existing brain function and precision in selecting new neurophysiological activities to drive desired behavior…