activity
20142020
most citedControllability of Brain Networks

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

collaborators

25 papers

cond-mat.soft2020

Crystallinity characterization of white matter in the human brain

Erin G. Teich, Matthew Cieslak, Barry Giesbrecht +4

White matter microstructure underpins cognition and function in the human brain through the facilitation of neuronal communication, and the non-invasive characterization of this st…

q-bio.NC2020

Flexibility of brain regions during working memory curtails cognitive consequences to lack of sleep

Nina Lauharatanahirun, Kanika Bansal, Steven M. Thurman +7

Previous research has shown a clear relationship between sleep and memory, examining the impact of sleep deprivation on key cognitive processes over very short durations or in spec…

q-bio.NC2020★ 16 cited

Scale-specific dynamics of large-amplitude bursts in EEG capture behaviorally meaningful variability

Kanika Bansal, Javier O. Garcia, Nina Lauharatanahirun +3

Cascading large-amplitude bursts in neural activity, termed avalanches, are thought to provide insight into the complex spatially distributed interactions in neural systems. In hum…

q-bio.NC2019

Learning in brain-computer interface control evidenced by joint decomposition of brain and behavior

Jennifer Stiso, Marie-Constance Corsi, Jean M. Vettel +5

Motor imagery-based brain-computer interfaces (BCIs) use an individuals ability to volitionally modulate localized brain activity as a therapy for motor dysfunction or to probe cau…

q-bio.NC2019

Functional brain network architecture supporting the learning of social networks in humans

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

Most humans have the good fortune to live their lives embedded in richly structured social groups. Yet, it remains unclear how humans acquire knowledge about these social structure…

q-bio.NC2018★ 158 cited

Cognitive chimera states in human brain networks

Kanika Bansal, Javier O. Garcia, Steven H. Tompson +3

The human brain is a complex dynamical system that gives rise to cognition through spatiotemporal patterns of coherent and incoherent activity between brain regions. As different r…

stat.AP2018

Local White Matter Architecture Defines Functional Brain Dynamics

Yo Joong Choe, Sivaraman Balakrishnan, Aarti Singh +2

Large bundles of myelinated axons, called white matter, anatomically connect disparate brain regions together and compose the structural core of the human connectome. We recently p…

cs.LG2018★ 268 cited

Compact Convolutional Neural Networks for Classification of Asynchronous Steady-state Visual Evoked Potentials

Nicholas R. Waytowich, Vernon Lawhern, Javier O. Garcia +4

Steady-State Visual Evoked Potentials (SSVEPs) are neural oscillations from the parietal and occipital regions of the brain that are evoked from flickering visual stimuli. SSVEPs a…

q-bio.NC2018★ 47 cited

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…

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…

q-bio.NC2016

The Energy Landscape Underpinning Module Dynamics in the Human Brain Connectome

Arian Ashourvan, Shi Gu, Marcelo G. Mattar +2

Human brain dynamics can be profitably viewed through the lens of statistical mechanics, where neurophysiological activity evolves around and between local attractors representing…

q-bio.NC2016

Cliques and Cavities in the Human Connectome

Ann Sizemore, Chad Giusti, Ari Kahn +2

Encoding brain regions and their connections as a network of nodes and edges captures many of the possible paths along which information can be transmitted as humans process and pe…

q-bio.NC2016

Animated 3D Human Models for Use in Person Recognition Experiments

Jean M. Vettel, Justin Kantner, Matthew Jaswa +1

The development of increasingly realistic experimental stimuli and task environments is important for understanding behavior outside the laboratory. We report a process for generat…

q-bio.NC2016★ 1 cited

Temporal and Semantic Effects on Multisensory Integration

Jean M. Vettel, Julia R. Green, Laurie Heller +1

How do we integrate modality-specific perceptual information arising from the same physical event into a coherent percept? One possibility is that observers rely on information acr…

q-bio.NC2016

Estimating direction in brain-behavior interactions: Proactive and reactive brain states in driving

Javier O. Garcia, Justin Brooks, Scott Kerick +3

Conventional neuroimaging analyses have revealed the computational specificity of localized brain regions, exploiting the power of the subtraction technique in fMRI and event-relat…

q-bio.NC2016

A novel method linking neural connectivity to behavioral fluctuations: Behavior-Regressed Connectivity

Antony D. Passaro, Jean M. Vettel, Jonathan McDaniel +3

Background: During an experimental session, behavioral performance fluctuates, yet most neuroimaging analyses of functional connectivity derive a single connectivity pattern. These…

q-bio.NC2016

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…

q-bio.NC2016

Stimulation-based control of dynamic brain networks

Sarah Feldt Muldoon, Fabio Pasqualetti, Shi Gu +4

The ability to modulate brain states using targeted stimulation is increasingly being employed to treat neurological disorders and to enhance human performance. Despite the growing…