@Article{Ritz97,
  author = 	 "R. Ritz and T. J. Sejnowski",
  title = 	 "Synchronous oscillatory activity in sensory systems:
		  new vistas on mechanisms.",
  journal =	 "Curr. Opin. Neurobiol.",
  year =	 1997,
  volume =	 7,
  number =	 4,
  pages =	 "536--546"
}

@Book{Ritz95,
  author = 	 "R. Ritz",
  title = 	 "Informationsverarbeitung durch koh{\"a}rente {A}ktivit{\"a}t
  in neuronalen {S}ystemen.",
  publisher = 	 "Verlag Harri Deutsch",
  year = 	 1995,
  number =	 42,
  series =	 "Rheihe Physik",
  address =	 "Frankfurt am Main"
}

@Booklet{Ritz2003,
  title = 	 {A Beginners Guide to the World of Zope},
  author =	 {Raphael Ritz},
  URL =          {http://www.neuroinf.de/Miscellaneous/BeginnersGuide},
  howpublished = {web-published},
  month =	 {March},
  year =	 2003
}

@InBook{Ritz94,
  author = 	 "R. Ritz and W. Gerstner and J. L.  van Hemmen",
  title = 	 "Associative binding and segregation in a network of spiking
  neurons.",
  editor =	 "E. Domany and J. L.  van Hemmen and K. Schulten",
  booktitle =	 "Models of neural networks II",
  year =	 1994,
  publisher =	 "Springer",
  address = 	 "New York",
  pages =	 "177--223"
}

@InCollection{Ritz2003a,
  author = 	 {Raphael Ritz and Rainer F{\"o}rster and Andreas V.M. Herz},
  title = 	 {Facilitating Data and Software Sharing in the Neurosciences - a Neuroinformatics Portal.},
  booktitle = 	 {Neuroscience Databases - A Practical Guide},
  pages =	 {293--306},
  publisher =	 {Kluwer Academic},
  year =	 2003,
  editor =	 {Rolf K{\"o}tter},
  chapter =	 20,
  address =	 {Boston}
}

@InProceedings{Ritz96,
  author = 	 "R. Ritz and T. J. Sejnowski",
  title = 	 "Correlation coding in a stochastic network model of
		  auditory binding.",
  volume =	 6,
  pages =	 "161--171",
  booktitle =	 "Proceedings of the 3rd Joint Symposium on Neural
		  Computation",
  year =	 1996,
  publisher =	 "Institute for Neural Computation",
  address =	 "La Jolla, CA"
}

@Manual{Ritz2004,
  title = 	 {Programming Plone - The MySite Tutorial},
  author =	 {Raphael Ritz},
  URL =          {http://www.neuroinf.de/LabTools/MySite},
  organization = {Humboldt-University},
  address =	 {Berlin},
  month =	 {May},
  year =	 2004,
  note =	 {work in progress}
}

@MastersThesis{Ritz91,
  author = 	 "R. Ritz",
  title = 	 "Kollektive Oszillationen in neuronalen Netzen.",
  school = 	 "Technische Universit{\"a}t M{\"u}nchen",
  year = 	 1991,
  type =	 "Diplomarbeit"
}

@Misc{Ritz2004a,
  author =	 {Raphael Ritz and the Berlin Neuroscience Community},
  title =	 {Computational Neuroscience in Berlin},
  URL =          {http://www.cns-berlin.org},
  howpublished = {web-site},
  year =	 {2003-2004}
}

@PhdThesis{Schuetze99,
  author = 	 {Hartmut Sch{\"u}tze},
  title = 	 {Elektrophysiologische Untersuchungen zur neuronalen Mustergenese der Stridulation bei der Feldheuschrecke Stenobothrus rubicundus (Germar 1817)},
  school = 	 {Georg-August-Universit{\"a}t zu G{\"o}ttingen},
  year = 	 1999
}

@Preprint{Gollisch2004,
  author = {Tim Gollisch and Andreas VM Herz},
  authorURLs = {http://www.cns-berlin.org/People/gollisch and http://www.cns-berlin.org/People/herz},
  title = {Identification of sensory transduction chains in vivo},
  year = {2004},
  URL = {http://www.cns-berlin.org/ResearchGroups/Herz/Papers/Gollisch2004},
  abstract = {Every sensation begins with the conversion of a sensory stimulus into the response of a receptor neuron. Typically, this involves a sequence of multiple biophysical processes that cannot all be monitored directly. Here we present a method that makes it nevertheless possible to extract their individual features by comparing different stimuli that cause the same final output, the only signal to be measured. Applied to auditory receptor cells, the technique reveals the sub-millisecond dynamics of mechanosensory signal processing and yields a quantitative four-step transduction model. The model accounts for the tuning properties of this class of neurons and explains their high temporal resolution under natural stimulation. Owing to its simplicity and generality, the method is readily applicable to other non-linear cascades and a large variety of signal-processing systems.}
}

@Proceedings{Fogel2003,
  title = 	 {Computational Intelligence - The Experts Speak},
  year = 	 2003,
  author =	 {David B. Fogel and Charles J. Robinson},
  organization = {IEEE Press},
  publisher =	 {Wiley Interscience}
}

@TechReport{WisMal96a,
  author =       "Laurenz Wiskott and Christoph von der Malsburg",
  year =         "1996",
  title =        "Face Recognition by Dynamic Link Matching",
  institution =  "Institut f{\"u}r Neuroinformatik",
  address =      "Ruhr-Universit{\"a}t Bochum, D-44780 Bochum, Germany",
  number =       "IR-INI 96-05",
  url =          "http://itb.biologie.hu-berlin.de/~wiskott/Publications/WisMal96a-faceRecognitionDLM-IRINI9605.ps.gz",
}

@Unpublished{Ritz2004c,
  author = 	 {Raphael Ritz},
  title = 	 {Flexible Topic},
  year =         2004,
  note = 	 {A Plone product that was never published individually but that is available together with the MySite package.}
}

@Webpublished{BerkWisk2003a,
  author = {Pietro Berkes and Laurenz Wiskott},
  title = {Slow Feature Analysis Yields a Rich Repertoire of Complex-Cell Properties},
  year = {2003},
  URL = {http://itb.biologie.hu-berlin.de/~wiskott/Abstracts/BerkWisk2003a.html},
  abstract = {In this study, we investigate temporal slowness as a learning principle for receptive fields using slow feature analysis, a new algorithm to determine functions that extract slowly varying signals from the input data. We find that the learned functions trained on image sequences develop many properties fo
und also experimentally in complex cells of primary visual cortex, such as direction selectivity, non-orthogonal inhibition, end-inhibition and side-inhibition. Our results demonstrate that a single unsupervised learning principle can account for such a rich repertoire of receptive field properties. },
  note = {Cognitive Sciences EPrint Archive (CogPrints) 2804, http://cogprints.ecs.soton.ac.uk/archive/00002804/}
}
