Preface

This Special Issue of Mathematical Biosciences and Engineeringcontains 11 selected papers presented at the Neural Coding 2014workshop. The workshop was held in the royal city of Versailles inFrance, October 6-10, 2014. This was the 11th of a series ofinternational workshops on this subject, the first held in Prague(1995), then Versailles (1997), Osaka (1999), Plymouth (2001), Aulla(2003), Marburg (2005), Montevideo (2007), Tainan (2009), Limassol(2010), and again in Prague (2012). Also selected papers from Praguewere published as a special issue of Mathematical Biosciences andEngineering and in this way a tradition was started. Similarly to theprevious workshops, this was a single track multidisciplinary eventbringing together experimental and computational neuroscientists. TheNeural Coding Workshops are traditionally biennial symposia. They arerelatively small in size, interdisciplinary with major emphasis on thesearch for common principles in neural coding. The workshop wasconceived to bring together scientists from different disciplines foran in-depth discussion of mathematical model-building andcomputational strategies. Further information on the meeting can befound at the NC2014 website athttps://colloque6.inra.fr/neural_coding_2014. The meeting wassupported by French National Institute for Agricultural Research, theworld's leading institution in this field.
   Understanding how the brain processes information is one of the mostchallenging subjects in neuroscience. The papers presented in thisspecial issue show a small corner of the huge diversity of this field,and illustrate how scientists with different backgrounds approach thisvast subject. The diversity of disciplines engaged in theseinvestigations is remarkable: biologists, mathematicians, physicists,psychologists, computer scientists, and statisticians, all haveoriginal tools and ideas by which to try to elucidate the underlyingmechanisms.In this issue, emphasis is put on mathematical modeling of singleneurons. A variety of problems in computational neuroscienceaccompanied with a rich diversity of mathematical tools and approachesare presented. We hope it will inspire and challenge the readers intheir own research.
   We would like to thank the authors for their valuable contributionsand the referees for their priceless effort of reviewing themanuscripts. Finally, we would like to thank Yang Kuangfor supporting us and making this publication possible.