1.9k citations · 9k across the 135 of their papers we have counts for
157 papers
Vibrational Stabilization of Cluster Synchronization in Oscillator Networks
Yuzhen Qin, Alberto Maria Nobili, Danielle S. Bassett +1
Cluster synchronization is of great importance for the normal functioning of numerous technological and natural systems. Deviations from normal cluster synchronization patterns are…
Vibrational Stabilization of Cluster Synchronization in Oscillator Networks
Yuzhen Qin, Alberto Maria Nobili, Danielle S. Bassett +1
Cluster synchronization is of paramount importance for the normal functioning of numerous technological and natural systems. Deviations from normal cluster synchronization patterns…
Vibrational Stabilization of Complex Network Systems
Alberto Maria Nobili, Yuzhen Qin, Carlo Alberto Avizzano +2
Many natural and man-made network systems need to maintain certain patterns, such as working at equilibria or limit cycles, to function properly. Thus, the ability to stabilize suc…
Compression supports low-dimensional representations of behavior across neural circuits
Dale Zhou, Jason Z. Kim, Adam R. Pines +7
Dimensionality reduction, a form of compression, can simplify representations of information to increase efficiency and reveal general patterns. Yet, this simplification also forfe…
Controlling collective dynamical states of mesoscale brain networks with local perturbations
Lia Papadopoulos, Demian Battaglia, Dani S. Bassett
Oscillatory synchrony is hypothesized to support the flow of information between brain regions, with different phase-locked configurations enabling activation of different effectiv…
A structurally informed model for modulating functional connectivity
Andrew C. Murphy, Romain Duprat, Theodore D. Satterthwaite +2
Functional connectivity (FC) between brain regions tracks symptom severity in many neuropsychiatric disorders. Transcranial magnetic stimulation (TMS) directly alters regional acti…
The Distributed Information Bottleneck reveals the explanatory structure of complex systems
Kieran A. Murphy, Dani S. Bassett
The fruits of science are relationships made comprehensible, often by way of approximation. While deep learning is an extremely powerful way to find relationships in data, its use…
Vibrational Control of Cluster Synchronization: Connections with Deep Brain Stimulation
Yuzhen Qin, Danielle S. Bassett, Fabio Pasqualetti
Cluster synchronization underlies various functions in the brain. Abnormal patterns of cluster synchronization are often associated with neurological disorders. Deep brain stimulat…
A Neural Programming Language for the Reservoir Computer
Jason Z. Kim, Dani S. Bassett
From logical reasoning to mental simulation, biological and artificial neural systems possess an incredible capacity for computation. Such neural computers offer a fundamentally no…
Exposure theory for learning complex networks with random walks
Andrei A. Klishin, Dani S. Bassett
Random walks are a common model for exploration and discovery of complex networks. While numerous algorithms have been proposed to map out an unknown network, a complementary quest…
Excitation and inhibition imbalance affects dynamical complexity through symmetries
Mathieu Ouellet, Jason Z. Kim, Harmange Guillaume +3
From the perfect radial symmetries of radiolarian mineral skeletons to the broken symmetry of homochirality, the logic of Nature's regularities has fascinated scientists for centur…
Optimizing the Human Learnability of Abstract Network Representations
William Qian, Christopher W. Lynn, Andrei A. Klishin +3
Precisely how humans process relational patterns of information in knowledge, language, music, and society is not well understood. Prior work in the field of statistical learning h…
Learning Continuous Chaotic Attractors with a Reservoir Computer
Lindsay M. Smith, Jason Z. Kim, Zhixin Lu +1
Neural systems are well known for their ability to learn and store information as memories. Even more impressive is their ability to abstract these memories to create complex inter…
The information content of brain states is explained by structural constraints on state energetics
Leon Weninger, Pragya Srivastava, Dale Zhou +6
Signal propagation along the structural connectome of the brain induces changes in the patterns of activity. These activity patterns define global brain states and contain informat…
Structural underpinnings of control in multiplex networks
Pragya Srivastava, Peter J. Mucha, Emily Falk +2
To design control strategies that predictably manipulate a system's behavior, it is first necessary to understand how the system's structure relates to its response. Many complex s…
The growing topology of the C. elegans connectome
Alec Helm, Ann S. Blevins, Danielle S. Bassett
Probing the developing neural circuitry in Caenorhabditis elegans has enhanced our understanding of nervous systems. The C. elegans connectome, like those of other species, is char…
Improving J-divergence of brain connectivity states by graph Laplacian denoising
Tiziana Cattai, Gaetano Scarano, Marie-Constance Corsi +3
Functional connectivity (FC) can be represented as a network, and is frequently used to better understand the neural underpinnings of complex tasks such as motor imagery (MI) detec…
Phase-Amplitude Coupling in Neuronal Oscillator Networks
Yuzhen Qin, Tommaso Menara, Danielle S. Bassett +1
Phase-amplitude coupling (PAC) describes the phenomenon where the power of a high-frequency oscillation evolves with the phase of a low-frequency one. We propose a model that expla…
Is the brain macroscopically linear? A system identification of resting state dynamics
Erfan Nozari, Maxwell A. Bertolero, Jennifer Stiso +6
A central challenge in the computational modeling of neural dynamics is the trade-off between accuracy and simplicity. At the level of individual neurons, nonlinear dynamics are bo…
Compressibility of complex networks
Christopher W. Lynn, Danielle S. Bassett
Many complex networks depend upon biological entities for their preservation. Such entities, from human cognition to evolution, must first encode and then replicate those networks…
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…
BCI learning induces core-periphery reorganization in M/EEG multiplex brain networks
Marie-Constance Corsi, Mario Chavez, Denis Schwartz +6
Brain-computer interfaces (BCIs) constitute a promising tool for communication and control. However, mastering non-invasive closed-loop systems remains a learned skill that is diff…
The network structure of scientific revolutions
Harang Ju, Dale Zhou, Ann S. Blevins +4
Philosophers of science have long postulated how collective scientific knowledge grows. Empirical validation has been challenging due to limitations in collecting and systematizing…
Network controllability in transmodal cortex predicts psychosis spectrum symptoms
Linden Parkes, Tyler M. Moore, Monica E. Calkins +7
The psychosis spectrum is associated with structural dysconnectivity concentrated in transmodal association cortex. However, understanding of this pathophysiology has been limited…