Dr Paula Sanz-Leon

Postdoctoral Research Associate

F09 - Madsen Building
The University of Sydney


Biographical details

Paula Sanz-Leon currently works at the School of Physics as a Postdoctoral Research Associate. After getting her degree in biomedical engineering in Argentina she traveled to France where she obtained a M. Sc. in Computational Biology and later on a Ph.D. in Computational Neuroscience. Her specialty are realistic and large-scale simulations of the human brain. Her research aims to study the dynamics of the electrical activity of the brain, both in health and disease, based on subject specific structural data. She hopes that the tools she develops will become a useful way to understand diseases such as epilepsy and to enable other fellow researchers to study more complex brain phenomena. Paula loves programming in Python and is a strong supporter of open-knowledge and open-source software to which she has contributed as a developer and mentor.

Current research students

Project title Research student
Modes of brain activity and brain network Farah DEEBA

Associations

Complex Systems Group, School of Phsyics, Faculty of Science, University of Sydney

ARC Centre of Excellence: Centre of Integrative Brain Function

Centre for Complex Systems

Selected publications

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Journals

  • Roy, N., Sanz-Leon, P., Robinson, P. (2017). Spectral signatures of activity-dependent neural feedback in the corticothalamic system. Physical Review E, 96(5), 052310-1-052310-13. [More Information]
  • Sanz-Leon, P., Knock, S., Spiegler, A., Jirsa, V. (2015). Mathematical framework for large-scale brain network modelling in The Virtual Brain. NeuroImage, 111, 385-430. [More Information]
  • Woodman, M., Pezard, L., Domide, L., Knock, S., Sanz-Leon, P., Mersmann, J., McIntosh, A., Jirsa, V. (2014). Integrating neuroinformatics tools in TheVirtualBrain. Frontiers in Neuroinformatics, 8(APR), 1-9. [More Information]
  • Sanz-Leon, P., Woodman, M., Mcintosh, R., Jirsa, V. (2013). The Virtual Brain: a neuroinformatics platform for simulating large-scale brain network models. BMC Neuroscience, 14(suppl 1), 1-2. [More Information]
  • Sanz-Leon, P., Knock, S., Woodman, M., Domide, L., Mersmann, J., McIntosh, A., Jirsa, V. (2013). The Virtual Brain: a simulator of primate brain network dynamics. Frontiers in Neuroinformatics, 7(10), 1-23. [More Information]
  • Sanz-Leon, P., Knock, S., Woodman, M., Spiegler, A. (2013). The VirtualBrain. Scholarpedia, 8(7). [More Information]
  • Sanz-Leon, P., Vanzetta, I., Masson, G., Perrinet, L. (2012). Motion clouds: model-based stimulus synthesis of natural-like random textures for the study of motion perception. Journal of Neurophysiology, 107(11), 3217-3226. [More Information]

2017

  • Roy, N., Sanz-Leon, P., Robinson, P. (2017). Spectral signatures of activity-dependent neural feedback in the corticothalamic system. Physical Review E, 96(5), 052310-1-052310-13. [More Information]

2015

  • Sanz-Leon, P., Knock, S., Spiegler, A., Jirsa, V. (2015). Mathematical framework for large-scale brain network modelling in The Virtual Brain. NeuroImage, 111, 385-430. [More Information]

2014

  • Woodman, M., Pezard, L., Domide, L., Knock, S., Sanz-Leon, P., Mersmann, J., McIntosh, A., Jirsa, V. (2014). Integrating neuroinformatics tools in TheVirtualBrain. Frontiers in Neuroinformatics, 8(APR), 1-9. [More Information]

2013

  • Sanz-Leon, P., Woodman, M., Mcintosh, R., Jirsa, V. (2013). The Virtual Brain: a neuroinformatics platform for simulating large-scale brain network models. BMC Neuroscience, 14(suppl 1), 1-2. [More Information]
  • Sanz-Leon, P., Knock, S., Woodman, M., Domide, L., Mersmann, J., McIntosh, A., Jirsa, V. (2013). The Virtual Brain: a simulator of primate brain network dynamics. Frontiers in Neuroinformatics, 7(10), 1-23. [More Information]
  • Sanz-Leon, P., Knock, S., Woodman, M., Spiegler, A. (2013). The VirtualBrain. Scholarpedia, 8(7). [More Information]

2012

  • Sanz-Leon, P., Vanzetta, I., Masson, G., Perrinet, L. (2012). Motion clouds: model-based stimulus synthesis of natural-like random textures for the study of motion perception. Journal of Neurophysiology, 107(11), 3217-3226. [More Information]

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