Biological Cybernetics - About the Editors
Editor-in-Chief
Benjamin Lindner received his Ph.D in Physics at Humboldt University Berlin in Germany. He worked as a postdoctoral fellow at the University of Ottawa (Canada) and as a research group leader at the Max Planck Institute PKS in Dresden (Germany). Since 2011 he is a Professor for the Theory of Complex Systems and Neurophysics at the Bernstein Center for Computational Neuroscience Berlin and at the Physics Department of Humboldt University Berlin. In his research, he applies methods from statistical physics to study complex biological systems, predominantly in neuroscience.
Co-Editors-in-Chief
Peter Thomas is a professor in the Department of Mathematics, Applied Mathematics 
and Statistics at Case Western Reserve University. He received his Ph.D. in mathematics from the University of Chicago, did postdoctoral work in computational neurobiology at the Salk Institute for Biological Studies in La Jolla, Calif, and taught at Oberlin College, before joining CWRU in 2006. He has held visiting positions at Ohio State University and Humboldt University (Berlin, Germany). His work has been supported by the National Science Foundation, the National Institutes of Health, the Simons Foundation, and the Council for the International Exchange of Scholars (Fulbright Program).
Peter Thomas' research interests include mathematical neuroscience, computational cell biology, and the application of information and control theory in biology. Using a combination of mathematical analysis and computational modeling, he works closely with biological collaborators to understand principles of communication and control in a variety of biological systems.
Jean-Marc Fellous did his graduate work in Computer Science and Artificial 
Intelligence at the University of Southern California (with M. Arbib and C. von der Malsburg, Los Angeles, CA), working on computational models of face recognition. He then held a postdoctoral position at Brandeis University (with J. Lisman, Boston, MA) and conducted experiments on rat brain slices to study pharmacologically elicited oscillations in the hippocampus. He then moved to the Salk Institute (with T. Sejnowski, San Diego, CA) to work on experimental and theoretical aspects of neuron reliability and precision. Dr. Fellous became an Assistant professor in Biomedical Engineering at Duke University (Durham, NC) in 2004, and joined the University of Arizona (Tucson, AZ) in 2006. He is currently a Professor in the Departments of Psychology and Biomedical Engineering and the director of the Computational and Experimental Neuroscience Laboratory. His current research projects are multidisciplinary and include 1) understanding the neural mechanisms of emotions in general and PTSD in particular, 2) how rats and human optimize their spatial navigation in complex spaces and 3) The role of sleep in memory consolidation.
Paul Tiesinga is professor of Neuroinformatics and chair of the department of Neuroinformatics at Radboud University (Nijmegen, the Netherlands). He received his masters in Theoretical Physics (1992) as well as his PhD in physics (1996) from Utrecht University. He was a postdoc in the physics department at Northeastern University (1997-1998, Boston, US) and a Sloan postdoctoral fellow at the Salk Institute (1998-2002, La Jolla, US). In 2002, he became an assistant professor in the Physics & Astronomy department at the University of North Carolina in Chapel Hill and was in 2008 promoted to associate professor. In 2009, he moved to the Radboud University Nijmegen to establish the Neuroinformatics department. He served as director of the Donders Centre for Neuroscience from 2010 to 2014 and is member of the Council for Training, Science and Infrastructure (CTSI) of the International Neuroinformatics Facility (INCF). He is an expert on modeling cortical oscillations using models ranging from simple nonlinear oscillators to large-scale models with hundreds of thousand neurons with Hodgkin-Huxley type voltage-gated channels. He is using model data to further develop methods for analyzing multivariate electrophysiological data. In addition, he is applying neuroinformatics techniques to organize, co-registering and analyze neuroimaging, optical imaging, anatomical, gene expression and electrophysiology data.
