57 citations · 155 across the 31 of their papers we have counts for
72 papers
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…
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…
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…