18 citations · 28 across the 5 of their papers we have counts for
7 papers
Network Clustering Via Kernel-ARMA Modeling and the Grassmannian The Brain-Network Case
Cong Ye, Konstantinos Slavakis, Pratik V. Patil +3
This paper introduces a clustering framework for networks with nodes annotated with time-series data. The framework addresses all types of network-clustering problems: State cluste…
Brain-Network Clustering via Kernel-ARMA Modeling and the Grassmannian
Cong Ye, Konstantinos Slavakis, Pratik V. Patil +2
Recent advances in neuroscience and in the technology of functional magnetic resonance imaging (fMRI) and electro-encephalography (EEG) have propelled a growing interest in brain-n…
Data-driven brain network models predict individual variability in behavior
Kanika Bansal, John D. Medaglia, Danielle S. Bassett +2
The relationship between brain structure and function has been probed using a variety of approaches, but how the underlying structural connectivity of the human brain drives behavi…
Implementing a Concept Network Model
Sarah H. Solomon, John D. Medaglia, Sharon L. Thompson-Schill
The same concept can mean different things or be instantiated in different forms depending on context, suggesting a degree of flexibility within the conceptual system. We propose t…
Network Controllability in the IFG Relates to Controlled Language Variability and Susceptibility to TMS
John D. Medaglia, Denise Y. Harvey, Nicole White +2
In language production, humans are confronted with considerable word selection demands. Often, we must select a word from among similar, acceptable, and competing alternative words…
Inter-regional ECoG correlations predicted by communication dynamics, geometry, and correlated gene expression
Richard F. Betzel, John D. Medaglia, Ari E. Kahn +3
Electrocorticography (ECoG) provides direct measurements of synchronized postsynaptic potentials at the exposed cortical surface. Patterns of signal covariance across ECoG sensors…