Research output per year

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Personal profile


Ben Fulcher is an NHMRC early career fellow at Brain and Mental Health Laboratory (BMH) in the School of Psychological Sciences, working with A/Prof Alex Fornito. His research draws on his background in physics-based modeling of biological systems, time-series analysis, and machine learning to aid understanding of brain connectivity. Ben works on time-series structure and brain connectivity in schizophrenia and the interplay between gene expression and connectivity.

Ben Fulcher completed a B.Sc. (Adv) (Hons) at the University of Sydney with majors in Physics and Nanoscience and Technology in 2007. He went on to obtain an M.Sc. in the School of Physics at the University of Sydney in 2008 on the topic of physiologically-based modeling of sleep-wake dynamics. This work focused on extending a neuronal population-based model of the sleep-wake switch, and using it to simulate such phenomena as sleep deprivation, impulsive external stimuli, and the effect of caffeine. Dr Fulcher went on to complete a DPhil at the University of Oxford in 2012 on highly comparative time-series analysis. This work involved comparing thousands of time series collected and synthesized across the scientific disciplines, and the behavior of thousands of time-series analysis methods on these data. The research has culminated in a collaborative online platform for time-series analysis that can be found at www.comp-engine.org/timeseries.

Related Links:

Research area keywords

  • community detection
  • connectome
  • dynamical models
  • machine learning
  • network analysis
  • sleep
  • time series
  • time-series analysis

Network Recent external collaboration on country level. Dive into details by clicking on the dots.



Anderson, C., Wilson Rajaratnam, S., Lockley, S., Cain, S., Gilbert, A., Maxik, F., Ftouni, S., Reynolds, K. J., Randhawa, S., Howard, M., Fulcher, B., Robinson, P. A., Smith, I., Gooley, J., Vakulin, A., D'Rozario, A., Dalton, C., Maruff, P. T., Irwin, B., Hocking, C., Pittman, S., Walker, J. & Tierney, P.


Project: Research

Research Output

  • 24 Article
  • 3 Review Article
  • 2 Chapter (Book)
  • 1 Conference Paper

Identifying and removing widespread signal deflections from fMRI data: Rethinking the global signal regression problem

Aquino, K. M., Fulcher, B. D., Parkes, L., Sabaroedin, K. & Fornito, A., 15 May 2020, In : NeuroImage. 212, 20 p., 116614.

Research output: Contribution to journalArticleResearchpeer-review

Open Access

A practical guide to linking brain-wide gene expression and neuroimaging data

Arnatkevic̆iūtė, A., Fulcher, B. D. & Fornito, A., 1 Apr 2019, In : NeuroImage. 189, p. 353-367 15 p.

Research output: Contribution to journalArticleResearchpeer-review

18 Citations (Scopus)

Bridging the Gap between Connectome and Transcriptome

Fornito, A., Arnatkevičiūtė, A. & Fulcher, B. D., 1 Jan 2019, In : Trends in Cognitive Sciences. 23, 1, p. 34-50 17 p.

Research output: Contribution to journalReview ArticleResearchpeer-review

9 Citations (Scopus)

Consistency and differences between centrality measures across distinct classes of networks

Oldham, S., Fulcher, B., Parkes, L., Arnatkeviciūtė, A., Suo, C. & Fornito, A., 26 Jul 2019, In : PLoS ONE. 14, 7, 23 p., e0220061.

Research output: Contribution to journalArticleResearchpeer-review

Open Access
6 Citations (Scopus)

Differentiating responders and non-responders to rTMS treatment for depression after one week using resting EEG connectivity measures

Bailey, NW., Hoy, KE., Rogasch, NC., Thomson, RH., McQueen, S., Elliot, D., Sullivan, CM., Fulcher, BD., Daskalakis, ZJ. & Fitzgerald, PB., 1 Jan 2019, In : Journal of Affective Disorders. 242, p. 68-79 12 p.

Research output: Contribution to journalArticleResearchpeer-review

11 Citations (Scopus)