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Magdalene College Cambridge

Professor Stephen Eglen

Dr Stephen Eglen is an Official Fellow and Director of Studies in Mathematics (Part II and Part III) at Magdalene. Dr Eglen is a Professor in Computational Neuroscience at the Department of Applied Mathematics and Theoretical Physics.

His undergraduate degree was in Cognitive Science, Psychology and Computer Science (Nottingham), followed by a doctorate in Computer Science and Artificial Intellegence (Sussex). 

His research interests focus on understanding the development of the nervous system: how do neurons form connections with each other into structured networks?  He works primarily on analysing and modeling of neuronal activity and development in the visual system.  Recent work has applied these techniques to understanding networks derived from human stem cells and for neurotoxicity testing. 

He is currently director of the MPhil in Computational Biology and would like to encourage all students to learn how to program.

 

Research Interests

Computational Neuroscience. Dr Eglen studies the formation of retinotopic maps and retinal mosaics in vertebrate visual systems. In addition, he is interested in the analysis of large-scale neurophysiological datasets, such as those recorded using multi-electrode arrays or calcium imaging.

Qualifications

BSc, DPhil, MA.

Key Publications

Eglen SJ, Marwick B, Halchenko YO, Hanke M, Sufi S, Gleeson P, Angus Silver R, Davison AP, Lanyon L, Abrams M, Wachtler T, Willshaw DJ, Pouzat C, Poline J-B (2017) 'Toward standard practices for sharing computer code and programs in neuroscience'. Nat Neurosci 20:770–773.

Cotterill E, Charlesworth P, Thomas CW, Paulsen O, Eglen SJ (2016) 'A comparison of computational methods for detecting bursts in neuronal spike trains and their application to human stem cell-derived neuronal networks'. J Neurophysiol 116:306–321.

Cutts CS, Eglen SJ (2014) 'Detecting Pairwise Correlations in Spike Trains: An Objective Comparison of Methods and Application to the Study of Retinal Waves'. Journal of Neuroscience 34:14288–14303.