Dr Benjamin Fulcher

Lecturer in Brain Dynamics and Neurophysics

A28 - Physics Building
The University of Sydney

Telephone +61 86276708

Website Website
Twitter
Curriculum vitae Curriculum vitae

Biographical details

Ben Fulcher completed a B.Sc. (Adv) (Hons) at the University of Sydney with majors in Physics and Nanoscience and Technology in 2007, and an M.Sc. (Physics) in 2008 on the topic of physiologically-based modeling of sleep-wake dynamics. Ben completed a DPhil at the University of Oxford in 2012 on time-series analysis and machine learning. He worked as an NHMRC early career researcher at Monash University from 2013-2017 on brain connectivity, gene expression, and computational neuroscience. He commenced work as a Lecturer in the School of Physics at Sydney Unviersity November 2017. His current research includes theoretical developments in statistical time-series analysis, as well as applications of data science and physics-based modeling approaches to computational neuroscience.

Research interests

time-series analysis; complex systems; complex networks; graph theory; computational neuroscience; network neuroscience; brain gene expression; brain development; physiologically-based modeling; machine learning

Teaching and supervision

PhD Students:

  • Sarab Sethi (with Nick Jones), Department of Mathematics, Imperial College London, London, UK.
  • Stuart Oldham (with Alex Fornito), School of Psychological Sciences, Monash University, Melbourne, Australia.
  • Aurina Arnatkeviciute (with Alex Fornito), School of Psychological Sciences, Monash University, Melbourne, Australia.
  • Linden Parkes (with Alex Fornito and Murat Yücel), School of Psychological Sciences, Monash University, Melbourne, Australia.
  • Leah Braganza (with Murat Yücel, Ben Harrison, Carsten Murawski and Valentina Lorenzetti), Melbourne University, Melbourne, Australia.
  • Elizabeth Seabrook (with Nikki Rickard and Peggy Kern), School of Psychological Sciences, Monash University, Melbourne, Australia.
  • Simonne Cohen (completed 2016) (with Kim Cornish, Russell Conduit, Steven Lockley, Shanthakumar Rajaratnam), School of Psychological Sciences, Monash University, Melbourne, Australia.

Current projects

  • Understanding interdisciplinary relationships between feature-based representations of time series, and how these can be leveraged to automate understanding of dynamical patterns in data, including inference of constraints on low-dimensional systems.
  • Understanding how gene transcriptional data in the brain can be combined with brain connectivity data to give insights into principles underlying brain organization.
  • Modeling the response of the brain to transcranial magnetic stimulation using physiologically-based modeling.
  • Predicting drug targets for brain disorders by combining diverse datasets.
  • Obtaining biomarkers to inform treatment response in brain disorders like schizophrenia using methods from time-series analysis and machine learning.

Associations

Ben Fulcher is an NHMRC Early Career Fellow.

Awards and honours

Australian representative for 9th Annual HOPE Meeting with Nobel Laureates (one of six Australians; Tokyo, 2017)

Selected grants

2015

  • From brain maps to mechanisms and back again: modelling the pathophysiology of schizophrenia; Fulcher B; National Health and Medical Research Council (NHMRC)/Early Career Fellowships.

Selected publications

Download citations: PDF RTF Endnote

Book Chapters

  • Fulcher, B. (2018). Feature-based time-series analysis. In 1st edition (Eds.), Feature Engineering for Machine Learning and Data Analytics, (pp. 1-30). Boca Raton: CRC Press. [More Information]
  • Robinson, P., Postnova, S., Abeysuriya, R., Kim, J., Roberts, J., McKenzie-Sell, L., Karanjai, A., Kerr, C., Fung, F., Anderson, R., Breakspear, M., Drysdale, P., Fulcher, B., Phillips, A., Rennie, C., Yin, G. (2015). A Multiscale "Working Brain" Model. In Basabdatta Sen Bhattacharya, Fahmida N. Chowdhury (Eds.), Validating NeuroComputational Models of Neurological and Psychiatric Disorders, (pp. 107-140). Cham: Springer. [More Information]

Journals

  • Fornito, A., Arnatkeviciute, A., Fulcher, B. (2019). Bridging the Gap between Connectome and Transcriptome. Trends in Cognitive Sciences, 23(1), 34-50. [More Information]
  • Fulcher, B., Murray, J., Zerbi, V., Wang, X. (2019). Multimodal gradients across mouse cortex. Proceedings of the National Academy of Sciences of the United States of America, 116(10), 4689-4695. [More Information]
  • Parkes, L., Fulcher, B., Y�cel, M., Fornito, A. (2018). An evaluation of the efficacy, reliability, and sensitivity of motion correction strategies for resting-state functional MRI. NeuroImage, 171, 415-436. [More Information]
  • Wilson, M., Fulcher, B., Fung, P., Robinson, P., Fornito, A., Rogasch, N. (2018). Biophysical modeling of neural plasticity induced by transcranial magnetic stimulation. Clinical Neurophysiology, 129(6), 1230-1241. [More Information]
  • Bailey, N., Hoy, K., Rogasch, N., Thomson, J., McQueen, S., Elliot, D., Sullivan, C., Fulcher, B., Daskalakis, Z., Fitzgerald, P. (2018). Differentiating responders and non-responders to rTMS treatment for depression after one week using resting EEG connectivity measures. Journal of Affective Disorders, 242, 68-79. [More Information]
  • Arnatkeviciute, A., Fulcher, B., Pocock, R., Fornito, A. (2018). Hub connectivity, neuronal diversity, and gene expression in the Caenorhabditis elegans connectome. PLoS Computational Biology, 14(2), 1-31. [More Information]
  • Seabrook, E., Kern, M., Fulcher, B., Rickard, N. (2018). Predicting Depression From Language-Based Emotion Dynamics: Longitudinal Analysis of Facebook and Twitter Status Updates. Journal of Medical Internet Research, 20(5), 1-17. [More Information]
  • Bailey, N., Hoy, K., Rogasch, N., Thomson, R., McQueen, S., Elliot, D., Sullivan, C., Fulcher, B., Daskalakis, Z., Fitzgerald, P. (2018). Responders to rTMS for depression show increased fronto-midline theta and theta connectivity compared to non-responders. Brain Stimulation, 11(1), 190-203. [More Information]
  • Cohen, S., Fulcher, B., Rajaratnam, S., Conduit, R., Sullivan, J., St Hilaire, M., Phillips, A., Loddenkemper, T., Kothare, S., McConnell, K., et al (2018). Sleep Patterns Predictive of Daytime Challenging Behavior in Individuals with Low-Functioning Autism. Autism Research, 11(2), 391-403. [More Information]
  • Cohen, S., Fulcher, B., Rajaratnam, S., Conduit, R., Sullivan, J., St Hilaire, M., Phillips, A., Loddenkemper, T., Kothare, S., et al (2017). Behaviorally-determined sleep phenotypes are robustly associated with adaptive functioning in individuals with low functioning autism. Scientific Reports, 7(1), 1-8. [More Information]
  • Fulcher, B., Jones, N. (2017). hctsa: A Computational Framework for Automated Time-Series Phenotyping Using Massive Feature Extraction. Cell Systems, 5(5), 527-531.e3. [More Information]
  • Sethi, S., Zerbi, V., Wenderoth, N., Fornito, A., Fulcher, B. (2017). Structural connectome topology relates to regional BOLD signal dynamics in the mouse brain. Chaos, 27(4), 047405-1-047405-14. [More Information]
  • Parkes, L., Fulcher, B., Yucel, M., Fornito, A. (2017). Transcriptional signatures of connectomic subregions of the human striatum. Genes, Brain and Behavior, 16(7), 647-663. [More Information]
  • Fulcher, B., Fornito, A. (2016). A transcriptional signature of hub connectivity in the mouse connectome. Proceedings of the National Academy of Sciences of the United States of America, 113(5), 1435-1440. [More Information]
  • Baker, S., Lubman, D., Yucel, M., Allen, N., Whittle, S., Fulcher, B., Zalesky, A., Fornito, A. (2015). Developmental changes in brain network hub connectivity in late adolescence. Journal of Neuroscience, 35(24), 9078-9087. [More Information]
  • Fulcher, B., Phillips, A., Postnova, S., Robinson, P. (2014). A physiologically based model of orexinergic stabilisation of sleep and wake. PloS One, 9(3), 1-8. [More Information]
  • Fulcher, B., Jones, N. (2014). Highly comparative feature-based time-series classification. IEEE Transactions On Knowledge And Data Engineering, 26(12), 3026-3037. [More Information]
  • Fulcher, B., Little, M., Jones, N. (2013). Highly comparative time-series analysis: The empirical structure of time series and their methods. Journal of the Royal Society Interface, 10(83), 1-12. [More Information]
  • Phillips, A., Fulcher, B., Robinson, P., Klerman, E. (2013). Mammalian Rest/Activity Patterns Explained by Physiologically Based Modeling. PLoS Computational Biology, 9(9), 1-10. [More Information]
  • Fulcher, B., Cui, X., Delley, B., Stampfl, C. (2012). Hardness analysis of cubic metal mononitrides from first principles. Physical Review B, 85(18), 184106-1-184106-9. [More Information]
  • Fulcher, B., Georgieva, A., Redman, C., Jones, N. (2012). Highly comparative fetal heart rate analysis. IEEE Engineering in Medicine and Biology Society Conference Proceedings, 2012, 3135-3138.
  • Puckeridge, M., Fulcher, B., Phillips, A., Robinson, P. (2011). Incorporation of Caffeine into a Quantitative Model of Fatigue and Sleep. Journal of Theoretical Biology, 273(1), 44-54. [More Information]
  • Robinson, P., Phillips, A., Fulcher, B., Puckeridge, M., Roberts, J. (2011). Quantitative modelling of sleep dynamics. Philosophical Transactions of the Royal Society A, 369(1952), 3840-3854. [More Information]
  • Fulcher, B., Phillips, A., Robinson, P. (2010). Quantitative physiologically based modeling of subjective fatigue during sleep deprivation. Journal of Theoretical Biology, 264(2), 407-419. [More Information]
  • Fulcher, B., Phillips, A., Robinson, P. (2008). Modeling the impact of impulsive stimuli on sleep-wake dynamics. Physical Review E, 78, 051920-1-051920-14. [More Information]

Conferences

  • Fulcher, B., Georgieva, A., Redman, C., Jones, N. (2012). Highly comparative fetal heart rate analysis. 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society EMBS 2012, Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]

2019

  • Fornito, A., Arnatkeviciute, A., Fulcher, B. (2019). Bridging the Gap between Connectome and Transcriptome. Trends in Cognitive Sciences, 23(1), 34-50. [More Information]
  • Fulcher, B., Murray, J., Zerbi, V., Wang, X. (2019). Multimodal gradients across mouse cortex. Proceedings of the National Academy of Sciences of the United States of America, 116(10), 4689-4695. [More Information]

2018

  • Parkes, L., Fulcher, B., Y�cel, M., Fornito, A. (2018). An evaluation of the efficacy, reliability, and sensitivity of motion correction strategies for resting-state functional MRI. NeuroImage, 171, 415-436. [More Information]
  • Wilson, M., Fulcher, B., Fung, P., Robinson, P., Fornito, A., Rogasch, N. (2018). Biophysical modeling of neural plasticity induced by transcranial magnetic stimulation. Clinical Neurophysiology, 129(6), 1230-1241. [More Information]
  • Bailey, N., Hoy, K., Rogasch, N., Thomson, J., McQueen, S., Elliot, D., Sullivan, C., Fulcher, B., Daskalakis, Z., Fitzgerald, P. (2018). Differentiating responders and non-responders to rTMS treatment for depression after one week using resting EEG connectivity measures. Journal of Affective Disorders, 242, 68-79. [More Information]
  • Fulcher, B. (2018). Feature-based time-series analysis. In 1st edition (Eds.), Feature Engineering for Machine Learning and Data Analytics, (pp. 1-30). Boca Raton: CRC Press. [More Information]
  • Arnatkeviciute, A., Fulcher, B., Pocock, R., Fornito, A. (2018). Hub connectivity, neuronal diversity, and gene expression in the Caenorhabditis elegans connectome. PLoS Computational Biology, 14(2), 1-31. [More Information]
  • Seabrook, E., Kern, M., Fulcher, B., Rickard, N. (2018). Predicting Depression From Language-Based Emotion Dynamics: Longitudinal Analysis of Facebook and Twitter Status Updates. Journal of Medical Internet Research, 20(5), 1-17. [More Information]
  • Bailey, N., Hoy, K., Rogasch, N., Thomson, R., McQueen, S., Elliot, D., Sullivan, C., Fulcher, B., Daskalakis, Z., Fitzgerald, P. (2018). Responders to rTMS for depression show increased fronto-midline theta and theta connectivity compared to non-responders. Brain Stimulation, 11(1), 190-203. [More Information]
  • Cohen, S., Fulcher, B., Rajaratnam, S., Conduit, R., Sullivan, J., St Hilaire, M., Phillips, A., Loddenkemper, T., Kothare, S., McConnell, K., et al (2018). Sleep Patterns Predictive of Daytime Challenging Behavior in Individuals with Low-Functioning Autism. Autism Research, 11(2), 391-403. [More Information]

2017

  • Cohen, S., Fulcher, B., Rajaratnam, S., Conduit, R., Sullivan, J., St Hilaire, M., Phillips, A., Loddenkemper, T., Kothare, S., et al (2017). Behaviorally-determined sleep phenotypes are robustly associated with adaptive functioning in individuals with low functioning autism. Scientific Reports, 7(1), 1-8. [More Information]
  • Fulcher, B., Jones, N. (2017). hctsa: A Computational Framework for Automated Time-Series Phenotyping Using Massive Feature Extraction. Cell Systems, 5(5), 527-531.e3. [More Information]
  • Sethi, S., Zerbi, V., Wenderoth, N., Fornito, A., Fulcher, B. (2017). Structural connectome topology relates to regional BOLD signal dynamics in the mouse brain. Chaos, 27(4), 047405-1-047405-14. [More Information]
  • Parkes, L., Fulcher, B., Yucel, M., Fornito, A. (2017). Transcriptional signatures of connectomic subregions of the human striatum. Genes, Brain and Behavior, 16(7), 647-663. [More Information]

2016

  • Fulcher, B., Fornito, A. (2016). A transcriptional signature of hub connectivity in the mouse connectome. Proceedings of the National Academy of Sciences of the United States of America, 113(5), 1435-1440. [More Information]

2015

  • Robinson, P., Postnova, S., Abeysuriya, R., Kim, J., Roberts, J., McKenzie-Sell, L., Karanjai, A., Kerr, C., Fung, F., Anderson, R., Breakspear, M., Drysdale, P., Fulcher, B., Phillips, A., Rennie, C., Yin, G. (2015). A Multiscale "Working Brain" Model. In Basabdatta Sen Bhattacharya, Fahmida N. Chowdhury (Eds.), Validating NeuroComputational Models of Neurological and Psychiatric Disorders, (pp. 107-140). Cham: Springer. [More Information]
  • Baker, S., Lubman, D., Yucel, M., Allen, N., Whittle, S., Fulcher, B., Zalesky, A., Fornito, A. (2015). Developmental changes in brain network hub connectivity in late adolescence. Journal of Neuroscience, 35(24), 9078-9087. [More Information]

2014

  • Fulcher, B., Phillips, A., Postnova, S., Robinson, P. (2014). A physiologically based model of orexinergic stabilisation of sleep and wake. PloS One, 9(3), 1-8. [More Information]
  • Fulcher, B., Jones, N. (2014). Highly comparative feature-based time-series classification. IEEE Transactions On Knowledge And Data Engineering, 26(12), 3026-3037. [More Information]

2013

  • Fulcher, B., Little, M., Jones, N. (2013). Highly comparative time-series analysis: The empirical structure of time series and their methods. Journal of the Royal Society Interface, 10(83), 1-12. [More Information]
  • Phillips, A., Fulcher, B., Robinson, P., Klerman, E. (2013). Mammalian Rest/Activity Patterns Explained by Physiologically Based Modeling. PLoS Computational Biology, 9(9), 1-10. [More Information]

2012

  • Fulcher, B., Cui, X., Delley, B., Stampfl, C. (2012). Hardness analysis of cubic metal mononitrides from first principles. Physical Review B, 85(18), 184106-1-184106-9. [More Information]
  • Fulcher, B., Georgieva, A., Redman, C., Jones, N. (2012). Highly comparative fetal heart rate analysis. 34th Annual International Conference of the IEEE Engineering in Medicine and Biology Society EMBS 2012, Piscataway: Institute of Electrical and Electronics Engineers (IEEE). [More Information]
  • Fulcher, B., Georgieva, A., Redman, C., Jones, N. (2012). Highly comparative fetal heart rate analysis. IEEE Engineering in Medicine and Biology Society Conference Proceedings, 2012, 3135-3138.

2011

  • Puckeridge, M., Fulcher, B., Phillips, A., Robinson, P. (2011). Incorporation of Caffeine into a Quantitative Model of Fatigue and Sleep. Journal of Theoretical Biology, 273(1), 44-54. [More Information]
  • Robinson, P., Phillips, A., Fulcher, B., Puckeridge, M., Roberts, J. (2011). Quantitative modelling of sleep dynamics. Philosophical Transactions of the Royal Society A, 369(1952), 3840-3854. [More Information]

2010

  • Fulcher, B., Phillips, A., Robinson, P. (2010). Quantitative physiologically based modeling of subjective fatigue during sleep deprivation. Journal of Theoretical Biology, 264(2), 407-419. [More Information]

2008

  • Fulcher, B., Phillips, A., Robinson, P. (2008). Modeling the impact of impulsive stimuli on sleep-wake dynamics. Physical Review E, 78, 051920-1-051920-14. [More Information]

To update your profile click here. For support on your academic profile contact .