The annual conference on Neural Information Processing Systems (NIPS) is the flagship conference on neural computation. These proceedings contain all of the papers that were presented.

The annual conference on Neural Information Processing Systems (NIPS) is the flagship conference on neural computation. It draws preeminent academic researchers from around the world and is widely considered to be a showcase conference for new developments in network algorithms and architectures. The broad range of interdisciplinary research areas represented includes computer science, neuroscience, statistics, physics, cognitive science, and many branches of engineering, including signal processing and control theory. Only about 30 percent of the papers submitted are accepted for presentation at NIPS, so the quality is exceptionally high. These proceedings contain all of the papers that were presented.

Part 1 Cognitive science: synchronized auditory and cognitive 40 Hz attentional streams and the impact of rhythmic expectations on auditory scene analysis, Bill Baird
on parallel versus serial processing - a computational study of visual search, Eyal Cohen, Eytan Ruppin
task and spatial frequency effects on face specialization, Matthew N. Dailey, Garrison W. Cottrell
Neural basis of object-centred representations, Sophie Debeve, Alexandre Pouget
a neural network model of naive preference and filial imprinting in the domestic chick, Lucy E. Hadden
adaptation in speech motor control, John F. Houde, Michael I. Jordan
learning human-like knowledge by singular value decomposition - a progress report, Thomas K. Landauer et al
multi-modular associative memory, Nir Levy et al
serial order in reading aloud - connectionist models and neighbourhood structure, Jeanne C. Milostan, Garrison W. Cottrell
a superadditive-impairment theory of optic aphasia, Michael C. Mozer et al
a hippocampal model of recognition memory, Randall C. O'Reilly et al
correlates of attention in a model of dynamic visual recognition, Rajesh P.N. Rao
recurrent neural networks can learn to implement symbol-sensitive counting, Paul Rodriguez, Janet Wiles
comparison of human and machine word recognition, Markus Schenkel et al. Part 2 Neuroscience: coding of naturalistic stimuli by auditory midbrain neurons, Hagai Atias, Christoph E. Schreiner
refractoriness and neural precision, Michael J. Berry II, Markus Meister
statistical models of conditioning, Peter Dayan, Theresa Long
characterizing neurons in the primary auditory cortex of the awake primate using reverse correlation, R. Christopher de Charms, Michael M. Merzenich
using Helmholtz machines to analyze multi-channel neuronal recordings, Virginia R. de Sa et al
instabilities in eye movement control - a model of periodic alternating nystagmus, Ernst R. Dow, Thomas J. Anastasio
hippocampal model of rat spatial abilities using temporal difference learning, David J. Foster et al
gradients for retinotectal mapping, Geoffrey J. Goodhill
a mathematical model of axon guidance by diffusible factors, Geoffrey J. Goodhill
computing with action potentials (invited talk), John J. Hopfield et al
a model of early visual processing, Laurent Itti et al
perturbative M-sequences for auditory systems identification, Mark Kvale, Christoph E. Schreiner
effects of spike timing underlying binocular integration and rivalry in a neural model of early visual cortex, Erik D. Lumer. (Part contents).