activity
20142020
most citedControllability of Brain Networks

998 citations · 1.6k across the 16 of their papers we have counts for

collaborators
Showing 2017Show all

7 papers · 1 filter

q-bio.NC2017

Global Brain Dynamics During Social Exclusion Predict Subsequent Behavioral Conformity

Nick Wasylyshyn, Brett Hemenway, Javier O. Garcia +6

Individuals react differently to social experiences; for example, people who are more sensitive to negative social experiences, such as being excluded, may be more likely to adapt…

q-bio.NC2017★ 1 cited

Individual Differences in Learning Social and Non-Social Network Structures

Steven H. Tompson, Ari E. Kahn, Emily B. Falk +2

Learning about complex associations between pieces of information enables individuals to quickly adjust their expectations and develop mental models. Yet, the degree to which human…

q-bio.NC2017

Network constraints on learnability of probabilistic motor sequences

Ari E. Kahn, Elisabeth A. Karuza, Jean M. Vettel +1

Human learners are adept at grasping the complex relationships underlying incoming sequential input. In the present work, we formalize complex relationships as graph structures der…

q-bio.NC2017★ 1 cited

Parsing spatiotemporal dynamical stability in ECoG during seizure onset, propagation, and termination

Arian Ashourvan, Sérgio Pequito, Ankit N. Khambhati +7

Understanding brain dynamics in epilepsy is critical for establishing rigorous control objectives that enable new therapeutic methods to mitigate seizure occurrence. In multichanne…

q-bio.NC2017

Multi-scale detection of hierarchical community architecture in structural and functional brain networks

Arian Ashourvan, Qawi K. Telesford, Timothy Verstynen +2

Community detection algorithms have been widely used to study the organization of complex systems like the brain. A principal appeal of these techniques is their ability to identif…

q-bio.NC2017★ 154 cited

Topological Principles of Control in Dynamical Network Systems

Jason Kim, Jonathan M. Soffer, Ari E. Kahn +3

Networked systems display complex patterns of interactions between a large number of components. In physical networks, these interactions often occur along structural connections t…

cs.LG2017★ 2 cited

Riemannian-geometry-based modeling and clustering of network-wide non-stationary time series: The brain-network case

Konstantinos Slavakis, Shiva Salsabilian, David S. Wack +5

This paper advocates Riemannian multi-manifold modeling in the context of network-wide non-stationary time-series analysis. Time-series data, collected sequentially over time and a…