Analysis and Modeling of Neural Systems

The recentexplosionofactivity inneural modelingseemsto have beendriven more by advances inthe theories and applicationsoflearning paradigms for artificial neural networks than by advances in our knowledge of real nervous systems. In the past few years, major conferences on neural networks and neural modeling have emerged and, appropriately, have focussed on technological exploitation of these advances. Sensingthat the recentleaps in both computational powerand knowledge ofthe nervous system may have setthe stage for a revolution intheoretical neurobiology, neuroscientists have welcomed thenew neural modeling; butmanyofthem would like tosee itdirected as heavily toward understanding of the nervou$ system as it is presently directed toward computertechnology and control-system engineering. Furthermore, some neuroscientists believe thattechnologists shouldnotbe satisfiedonly with exploiting or extending the recent advances in learning paradigms, that emerging knowledge about real nervous systems will suggest other, comparably valuable, paradigms forsignal processingand control.Ourmotive as organizers was to have a conference that focussed on both of these areas -- emerging modeling tools and concepts for neurobiologists, and emerging neurobiological concepts and neurobiological knowledge ofpotential use to technologists. Ourprinciple ofdesign was simple. We attempted to organize aconference withagroup ofspeakers that would be most illuminating and exciting to us and to our students. We succeeded. EdwinR. Lewis INTRODUCTION This volume contains the collected papers of the 1990 Conference on Analysis and ModelingofNeural Systems, held July 25-27, in Berkeley, California. There were 21 invited talks at the meeting, covering aspects ofanalysis and modeling from the subcellularlevel to the networklevel. Inaddition, thirty six posters were accepted forpresentation.