137 citations · 284 across the 10 of their papers we have counts for
12 papers
Symmetry breaker governs synchrony patterns in neuronal inspired networks
Anil Kumar, Edmilson Roque dos Santos, Paul J. Laurienti +1
Experiments in the human brain reveal switching between different activity patterns and functional network organization over time. Recently, multilayer modeling has been employed a…
Fractal Basins as a Mechanism for the Nimble Brain
Erik Bollt, Jeremie Fish, Anil Kumar +2
An interesting feature of the brain is its ability to respond to disparate sensory signals from the environment in unique ways depending on the environmental context or current bra…
Entropic Causal Inference for Neurological Applications
Jeremie Fish, Alexander DeWitt, Abd AlRahman R. AlMomani +2
The ultimate goal of cognitive neuroscience is to understand the mechanistic neural processes underlying the functional organization of the brain. Key to this study is understandin…
Learning Common Harmonic Waves on Stiefel Manifold -- A New Mathematical Approach for Brain Network Analyses
Jiazhou Chen, Guoqiang Han, Hongmin Cai +5
Converging evidence shows that disease-relevant brain alterations do not appear in random brain locations, instead, its spatial pattern follows large scale brain networks. In this…
Disentangling Brain Graphs: A Note on the Conflation of Network and Connectivity Analyses
Sean L. Simpson, Paul J. Laurienti
Understanding the human brain remains the Holy Grail in biomedical science, and arguably in all of the sciences. Our brains represent the most complex systems in the world (and som…
A Two-Part Mixed-Effects Modeling Framework For Analyzing Whole-Brain Network Data
Sean L. Simpson, Paul J. Laurienti
Whole-brain network analyses remain the vanguard in neuroimaging research, coming to prominence within the last decade. Network science approaches have facilitated these analyses a…
The ubiquity of small-world networks
Qawi K. Telesford, Karen E. Joyce, Satoru Hayasaka +2
Small-world networks by Watts and Strogatz are a class of networks that are highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs.…
Assessing the consistency of community structure in complex networks
Matthew Steen, Satoru Hayasaka, Karen Joyce +1
In recent years, community structure has emerged as a key component of complex network analysis. As more data has been collected, researchers have begun investigating changing comm…
An exponential random graph modeling approach to creating group-based representative whole-brain connectivity networks
Sean L. Simpson, Malaak N. Moussa, Paul J. Laurienti
Group-based brain connectivity networks have great appeal for researchers interested in gaining further insight into complex brain function and how it changes across different ment…
Universal fractal scaling of self-organized networks
Paul J. Laurienti, Karen E. Joyce, Qawi K. Telesford +2
There is an abundance of literature on complex networks describing a variety of relationships among units in social, biological, and technological systems. Such networks, consistin…
Exponential Random Graph Modeling for Complex Brain Networks
Sean L. Simpson, Satoru Hayasaka, Paul J. Laurienti
Exponential random graph models (ERGMs), also known as p* models, have been utilized extensively in the social science literature to study complex networks and how their global str…
Degree distributions in mesoscopic and macroscopic functional brain networks
Satoru Hayasaka, Paul J. Laurienti
We investigated the degree distribution of brain networks extracted from functional magnetic resonance imaging of the human brain. In particular, the distributions are compared bet…