activity
20102023
most citedEnergy landscape analysis of neuroimaging data

143 citations · 349 across the 6 of their papers we have counts for

collaborators

6 papers

q-bio.NC2023★ 4 cited

State-transition dynamics of resting-state functional magnetic resonance imaging data: Model comparison and test-to-retest analysis

Saiful Islam, Pitambar Khanra, Johan Nakuci +3

Electroencephalogram (EEG) microstate analysis entails finding dynamics of quasi-stable and generally recurrent discrete states in multichannel EEG time series data and relating pr…

q-bio.NC2020★ 24 cited

Modeling state-transition dynamics in resting-state brain signals by the hidden Markov and Gaussian mixture models

Takahiro Ezaki, Yu Himeno, Takamitsu Watanabe +1

Recent studies have proposed that one can summarize brain activity into dynamics among a relatively small number of hidden states and that such an approach is a promising tool for…

physics.soc-ph2018★ 129 cited

Clustering coefficients for correlation networks

Naoki Masuda, Michiko Sakaki, Takahiro Ezaki +1

The clustering coefficient quantifies the abundance of connected triangles in a network and is a major descriptive statistics of networks. For example, it finds an application in t…

q-bio.NC2016★ 143 cited

Energy landscape analysis of neuroimaging data

Takahiro Ezaki, Takamitsu Watanabe, Masayuki Ohzeki +1

Computational neuroscience models have been used for understanding neural dynamics in the brain and how they may be altered when physiological or other conditions change. We review…

nlin.CD2011

Rich-club network topology to minimize synchronization cost due to phase difference among frequency-synchronized oscillators

Takamitsu Watanabe

Functions of some networks, such as power grids and large-scale brain networks, rely on not only frequency synchronization, but also phase synchronization. Nevertheless, even after…

cond-mat.dis-nn2010★ 49 cited

Enhancing the spectral gap of networks by node removal

Takamitsu Watanabe, Naoki Masuda

Dynamics on networks are often characterized by the second smallest eigenvalue of the Laplacian matrix of the network, which is called the spectral gap. Examples include the thresh…