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Neuroscience is generating vast amounts of highly diverse data which is of potential interest to researchers beyond the laboratories in which it is collected. In particular, quantitative neuroanatomical data is relevant to a wide variety of areas, including studies of development, aging, pathology and in biophysically oriented computational modelling. Moreover, the relatively discrete and well-defined nature of the data make it an ideal application for developing systems designed to facilitate data archiving, sharing and reuse. At present, the only widely used forms of dissemination are figures and tables in published papers which suffer from inaccessibility and the loss of machine readability. They may also present only an averaged or otherwise selected subset of the available data. Numerous database projects are in progress to address these shortcomings. They employ a variety of architectures and philosophies, each with its own merits and disadvantages. One axis on which they may be distinguished is the degree of top-down control, or curation, involved in data entry. Here we consider one extreme of this scale in which there is no curation, minimal standardization and a wide degree of freedom in the form of records used to document data. Such a scheme has advantages in the ease of database creation and in the equitable assignment of perceived intellectual property by keeping the control of data in the hands of the experts who collected it. It does, however, require a more sophisticated infrastructure than conventional databases since the software must be capable of organizing diverse and differently documented data sets in an effective way. Several components of a software system to provide this infrastructure are now in place. Examples are presented, showing how these tools can be used to archive and publish neuronal morphology data, and how they can give an integrated view of data stored at many different sites.

1. The heartbeat central pattern-generating network of the medicinal leech contains elemental neural oscillators, comprising reciprocally inhibitory pairs of segmental heart interneurons, that use graded as well as spike-mediated synaptic transmission. We are in the process of developing a general computer model of this pattern generator. Our modeling goal is to explore the interaction of membrane currents and synaptic transmission that promote oscillation in heart interneurons. As a first step toward this goal, we have developed a computer model of graded synaptic transmission between reciprocally inhibitory heart interneurons. Previously gathered voltage-clamp data of presynaptic Ca2+ currents and simultaneous postsynaptic currents and potentials (5 mM external [Ca2+]) were used as the bases of the model. 2. We assumed that presynaptic Ca2+ current was composed of distinct fast (ICaF) and slow (Icas) components because there are two distinct time courses of inactivation for this current. We fitted standard Hodgkin-Huxley equations (Eq. 1 and 2, APPENDIX) to these components using first-order activation and inactivation kinetics. 3. Graded synaptic transfer in the model is based on calculation of a dimensionless variable [P]. A portion of both IcaF and ICaS determined by a factor A contributes to [P], and a removal factor B decreases [P] (Eq. 4, APPENDIX). [P] can be roughly equated to the [Ca2+] in an unspecified volume that is effective in causing transmitter release. Transmitter release, and thus postsynaptic conductance, is related to [P]3 (Eq. 3, APPENDIX). 4. We adapted our model to voltage-clamp data gathered at physiological external [Ca2+] (2.0 mM) and tested it for shorter presynaptic voltage steps. Presynaptic Ca2+ currents and synaptic transfer were well simulated under all conditions. 5. The graded synaptic transfer model could be used in a network simulation to reproduce the oscillatory activity of a reciprocally inhibitory pair of heart interneurons. Because synaptic transmission in the model is an explicit function of presynaptic Ca2+ current, the model should prove useful to explore the interaction between membrane currents and synaptic transmission that promote and modulate oscillation in reciprocally inhibitory heart interneurons.