Publications

Here we list some key research publications from the Dynamics and Neural Systems Group.

For BD Fulcher’s full publication list, see Google Scholar.

We include a link to the journal article, alongside a link to an associated youtube explainer video, and any associated news article or plain-language summary.

Recent Highlights

More from our group

A feature-based information-theoretic approach for detecting interpretable, long-timescale pairwise interactions from time series.
A. Nguyen, O. McMullin, J.T. Lizier, B.D. Fulcher. Physical Review Research (2025).

Benchmarking overlapping community detection methods for applications in human connectomics.
A.G. Bryant, A. Jha, S. Agarwal, P. Cahill, B. Lam, S.G. Oldham, A. Arnatkeviciute, A. Fornito, B.D. Fulcher. Network Neuroscience (2025).

Canonical time-series features for characterizing biologically informative dynamical patterns in fMRI.
I. Alam, B. Harris, P. Cahill, O. Cliff, M. Markicevic, V. Zerbi, B.D. Fulcher. Aperture Neuroscience (2025).

Using matrix-product states for time-series machine learning.
J.B. Moore, H.P. Stackhouse, B.D. Fulcher, S. Mahmoodian. Physical Review Research (2025).

Extracting interpretable signatures of whole-brain dynamics through systematic comparison.
A.G. Bryant, K. Aquino, L. Parkes, A. Fornito, B.D. Fulcher. PLOS Computational Biology (2024).

Tracking the Distance to Criticality in Systems with Unknown Noise.
B. Harris, L. Gollo, B.D. Fulcher. Physical Review X (2024).

Analyzing the Brain’s Dynamic Response to Targeted Stimulation using Generative Modeling.
R. Maran, E.J. Müller, B.D. Fulcher. Network Neuroscience (2024).

Unifying Pairwise Interactions in Complex Dynamics.
O.M. Cliff, A. Bryant, J.T. Lizier, N. Tsuchiya, B.D. Fulcher. Nature Computational Science (2023).

On the information-theoretic formulation of network participation.
P. Cajic, D. Agius, O.M. Cliff, J.M. Shine, J.T. Lizier, B.D. Fulcher. Journal of Physics Complexity (2024).

Never a Dull Moment: Distributional Properties as a Baseline for Time-Series Classification.
T. Henderson, A.G. Bryant, B.D. Fulcher. arXiv (2022).

Feature-Based Time-Series Analysis in R using the theft Package.
T. Henderson, B.D. Fulcher. The R Journal (2025).

Classifying Kepler light curves for 12,000 A and F stars using supervised feature-based machine learning.
N.H. Barbara, T.R. Bedding, B.D. Fulcher, S.J. Murphy, T. Van Reeth. Monthly Notices of the Royal Astronomical Society (2022).

Extracting dynamical understanding from neural-mass models of mouse cortex.
P.H. Siu, E. Müller, V. Zerbi, K. Aquino, B.D. Fulcher. Frontiers in Computational Neuroscience (2022).

Overcoming false-positive gene-category enrichment in the analysis of spatially resolved transcriptomic brain atlas data.
B.D. Fulcher, A. Arnatkeviciute, A. Fornito. Nature Communications (2021).

Scaling of gene transcriptional gradients with brain size across mouse development.
H.Y. Gladys Lau, A. Fornito, B.D. Fulcher. NeuroImage (2021).

Timescales of spontaneous fMRI fluctuations relate to structural connectivity in the brain.
J. Fallon, P. Ward, L. Parkes, S. Oldham, A. Arnatkeviciute, A. Fornito, B.D. Fulcher. Network Neuroscience (2020).

A self-organizing, living library of time-series data.
B.D. Fulcher, C.H. Lubba, S.S. Sethi, N.S. Jones. Scientific Data (2020).

Multimodal gradients across mouse cortex.
B.D. Fulcher, J.D. Murray, V. Zerbi, X.-J. Wang. PNAS (2019).

catch22: CAnonical Time-series CHaracteristics.
C.H. Lubba, S.S. Sethi, P. Knaute, S.R. Schultz, N.S. Jones, B.D. Fulcher. Data Mining and Knowledge Discovery (2019).

Structural connectome topology relates to regional BOLD signal dynamics in the mouse brain.
S.S. Sethi, V. Zerbi, N. Wenderoth, A. Fornito, B.D. Fulcher. Chaos (2017).