Sharon Crook
School of Mathematical and Statistical Sciences
School of Life Sciences
My work focuses on developing and using mathematical and computational approaches to study the dynamics of neurons and neuronal networks. I am particularly interested in the mechanisms underlying structural plasticity in the nervous system and how sensory systems work and are integrated. I also contribute to an international effort to promote reproducibility, model sharing, and community-based collaborative model development in computational neuroscience research.
I earned my PhD in Applied Mathematics at the University of Maryland at College Park. My dissertation research was performed at the Mathematical Research Branch of the National Institutes of Health under Director Dr. John Rinzel. The work focused on the development of coupled oscillator models for representing cortical dynamics and was supervised by Dr. Bard Ermentrout at the University of Pittsburgh.
After graduating from the University of Maryland, I held a postdoctoral appointment at the Center for Computational Biology at Montana State University with Dr. John Miller and Dr. Gwen Jacobs where I performed joint work in neurophysiology, mathematical modeling and neuroinformatics.
Selected Peer-reviewed Publications
Berger, S, S Crook (2015) Modeling the influence of ion channels on neuron dynamics in Drosophila. Frontiers in Computational Neuroscience. 9:139. doi:10.3389/fncom/2015.00139.
Birgiolas, J, S Dietrich, S Crook, A Rajadesingan, C Zhang, S Velugoti Penchala, V Addepalli (2015) Ontology-assisted keyword search for NeuroML models. In Amarnath Gupta and Susan Rathbun, Eds, Proceedings of the 27th International Conference on Scientific and Statistical Database Management, ACM, New York, NY. Article 37. doi=10.1145/2791347.2791360.
Gardner, C, JR Jones, SM Baer, SM Crook (2014) Drift-diffusion simulation of the ephaptic effect in the triad synapse of the retina. Journal of Computational Neuroscience. 38:129-142. PubMed
Cannon, RC, P Gleeson, S Crook, G Gnapathy, B Marin, E Piasini, RA Silver (2014) LEMS: A language for expressing complex biological models in concise and hierarchical form and its use in underpinning NeuroML 2. Frontiers in Neuroinformatics. 8:79. PubMed
Vella, M, RC Cannon, S Crook, AP Davison, G Ganapathy, HPC Robinson, RA Silver, P Gleeson (2014) libNeuroML and PyLEMS: using Python to combine procedural and declarative modeing approaches in computational neuroscience. Frontiers in Neuroinformatics. 8:38. PubMed
Crook, SM, JA Bednar, SD Berger, RC Cannon, AP Davison, M Djurfeldt, J Eppler, B Kriener, S Furber, B Graham, M Hull, HE Plesser, L Schwabe, L Smith, V Steuber, S van Albada (2012) Creating, documenting and sharing network models. Network: Computation in Neural Systems.23(4):131-149. PubMed
Kurian, M, SM Crook, R Jung (2011) Motoneuron models of self-sustained firing after spinal cord injury. Journal of Computational Neuroscience. 31(3):625-645. PubMed, ModelDB
Gleeson, P, S Crook, R Cannon, M Hines, G Billings, M Farinella, TM Morse, A Davison, S Ray, U Bhalla, SR Barnes, YD Dimitrova and RA Silver (2010) NeuroML: a simulator-independent language for describing data-driven models of neurons and networks with a high degree of biological realism. PLoS Computational Biology. 6(6): e1000815. PubMed
Crook SM, M Dur-e-Ahmad and SM Baer (2007) A model of activity-dependent changes in dendritic spine density and spine structure. Mathematical Biosciences and Engineering. 4(4):617-631. PubMed, ModelDB
Crook, S, P Gleeson, F Howell, J Svitak and RA Silver (2007) MorphML: Level 1 of the NeuroML standards for neuronal morphology data and model specification. Neuroinformatics. 5(2):96-104. PubMed
Selected Book Chapters
Crook, S, HE Plesser, A Davison (2013) Lessons from the past: approaches for reproducibility in computational neuroscience. In JM Bower, ed. 20 Years of Computational Neuroscience, Springer.
Gleeson, P, V Steuber, RA Silver and S Crook (2012) NeuroML. In Le Novere, ed. Computational Systems Biology, Springer.
Venugopal, S, S Crook, M Srivatsan and R Jung (2011) Principles of computational neuroscience. In Jung, ed. Biomimetic and Biohybrid Living-Hardware Systems, Wiley.
Crook, S and F Howell (2007) XML for data representation and model specification in neuroscience. in Crasto, ed. Methods in Molecular Biology Book Series: Neuroinformatics, Humana Press. PubMed