We have decided, based on the current design of the database system, to focus the development of the database prototype specifically on the models we have constructed related to the mammalian cerebellum. We have determined that this specific focus will allow us to fully develop a working prototype of the database system. At present, several models exist at the single cell level, which will form the basis for the database. Over the last year, we have completed construction of a systems level-network model within GENESIS which includes major projections to cerebellar folium, crus IIa. The model incorporates physiological data on the structure of cerebellar tactile maps as well as maps for the trigeminal nuclei (Principalis and Interpolaris), thalamic nuclei (VPM and POM) and somatosensory cortex. This later data was obtained from the literature. Over the last year, we have also begun to develop a network model of cerebellar cortex. This large project will take several years to complete, but will, when finished allow us to link the systems level model to the single cell models currently complete or being constructed. From the point of view of the database, linking these models together will provide a prototype for a multi-level browsing interface of neurobiological data relevant to the functional organization of the cerebellar cortex.
The following example illustrates the way in which the database would be used. In this example, we assume that the interface to the multibase system has been implemented on a high-end graphics workstation where a windowing environment and mouse is a standard means for interaction. Let us assume that a neuroscientist is interested in exploring ways in which calcium channels affect the firing of Purkinje cells in the cerebellum.
Figure 1 shows a prototype for the top level interface to the database. After entering the keyword ``purkinje'', the user is presented with a number of contexts in which Purkinje cells appear in the database, grouped into several categories. From left to right, the categories are (a) behavioral studies (of tactile exploration and cerebellar lesions), (b) the systems level (in this case, what is known about the connections between regions of the cerebellar system), (c) the network level (a model of the cerebellar cortex), (d) the cellular level (Purkinje cell model), (e) the subcellular level (ion channels, etc.), and (f) pertinent references to the literature. These various categories may be accessed both from the top level interface (the Multi-Browser), and from within other categories.
Figure 1: The prototype for the top level interface to the database. Several levels of contexts for the keyword "purkinje" are displayed, ranging from behavioral studies of the animal to subcellular properties of the Purkinje cell, plus pertinent references to the literature.
The selection of the De Schutter and Bower (1994a,b) Purkinje cell model leads to a tutorial on the model, with the opportunity to view a description of the model and simulation results of voltage clamp, current injection, synaptic input, and simulated in vivo responses. (See COLOR PLATE.)
Click HERE to see the large color figure.
COLOR PLATE: A tutorial on the cerebellar Purkinje cell is used as an entry point to queries on Purkinje cells, when using the GENESIS Simulator-based Neuronal Database. Here, the user has selected the Voltage Clamp tutorial. In addition to showing both simulated and experimental results for voltage clamp results, this tutorial provides a list of suitable keywords for additional searches. For example, "channels" will allow the the user to extract information regarding the voltage dependent channels which are found in Purkinje cells. The detailed cell model (De Schutter & Bower 1994a,b) is showing a false color representation of the membrane potential throughout the cell, as a result of a previously performed current clamp simulation.
Each of these categories allow an examination of the experimental data for comparison. From within the tutorial, as well as from the subcellular category of the top level interface, the object shown in Figure 2 may be accessed. Here, it is possible to query the model for the parameters used to characterize each of the ten types of channels used in the model (lower left), the distribution of these conductances within the cell model, and references to the papers which provided the descriptions of the channels which were implemented in the model.
Figure 2: The tutorial on Purkinje cell channels, accessible from either the top level interface or the Purkinje cell tutorial, provides a basis for queries regarding channel properties. The detailed cell model shown (De Schutter & Bower 1994a,b) uses 4550 compartments to model the dendrites and dendritic spines, and contains 8021 ion channels which fall into 10 categories. The tool box at the lower left provides a way to import and export other data, and to make comparisions with other objects in the database.
The tool box at the lower left provides a way to import and export other data. As it is important to understand the basis of assumptions which were made in the model, there is access to the experimental current injection results which were used to ``tune'' the model parameters. Links to remote sites are provided so that it is possible to access the full data set, as well as the data used for tuning. Objects from the database may be exported to GENESIS simulations, data analysis tools, and visualization tools. The COMPARE button provides tools for aggregate operations such as making automated comparisions with other objects in the database. For example, comparisons may be made with channels found in another model. Within the tutorial it will be possible to perform searches to answer questions like ``what are all the single-cell models which use this type of Ca channel with parameters in this range; what are all the bursting models that were based on spiking behaviour with these statistics?" The researcher can also move from a Ca channel in a Purkinje cell to a listing of all the places Ca channels are currently used in models in GENESIS.
At this point, the user elects to view predictions of in vivo physiological responses to real stimuli, bringing up the display shown in Figure 3. The link at the lower left allows the viewing of experimental extracellular recordings and peri-stimulus time (PST) histograms for comparison with the simulated results. By clicking on a set of results, it is possible to find a reference for the source of these results (De Schutter & Bower, 1994b).
Figure 3: Predictions of in vivo physiological responses to appied stimuli are accessed from the Purkinje cell tutorial. Both simulated and experimentally obtained measurements of PST histograms, spike trains, and other data may be viewed.
Having explored the single cell level, the user may switch to the cerebellar network level and explore the response of the model of the cerebellar cortex (crus IIa) of the rat to selected input patterns of stimulus. Figure 4 shows the result of a query for the corresponding experimental results. Here, the cursor is used to select tactile stimulation applied to the ipsilateral upper lip area (IUL) in the diagram at the upper right. This results in a display of the PST histogram obtained from recordings from the point marked ``X'' in crus IIa, which is within the patch that is somatopically mapped to the IUL. The peaks in the PST histogram correspond to information coming from two different pathways - the direct pathway through the trigeminal nucleus, and the indirect pathway from the somatosensory cortex. A query for the source of the experimental data leads to a reference to the work of Thompson and Bower (1993).
Figure 4: The result of a query for experimental results showing the response of the cerebellar cortex of a rat to facial stimulation. The ipsilateral upper lip area (IUL) was selected, and the PST histogram displayed is for recordings at the corresponding somatopically mapped area of crus IIa.
Moving up another level, the user then shifts to the cerebellar system model in order to learn more about the pathways which are involved. Figure 5 shows a simplified representation of the major sensory pathways to the cerebellum. This is an interface to the high level GENESIS systems level model of the cerebellum and the regions projecting to it. This model lets one click on particular regions of either somatosensory cortex, the thalamus, the trigeminal nucleus, the cerebellum, the pons, or the animal's face, and see all the related regions in each structure. It is possible to see where they connect as well as what their receptive fields are. One can also click on different buttons and see the secondary receptive fields. This can be done in the normal animal simulation as well as in the simulation of an animal with lesioned trigeminal nerve. When the trigeminal nerve is cut, these original projections are kept constant and the model may be used to test the hypothesis that the reorganization that is observed experimentally in the cerebellum could happen without any new projections.
Figure 5: The graphical interface for queries regarding Purkinje cells at the systems level. Selecting particular regions in the diagram of the major sensory pathways to the cerebellum allows one to see both simulated and experimental data for primary and secondary receptive fields under various conditions.
The projections are all established based on the reports in the literature of the receptive field size of each different brain area. It is possible to query this data, as well as descriptions of the experimental procedures. By clicking at the lower left of Figure 5, it is possible to query the highest level of the database, and examine data for the behavior of the rat before and after severing the trigeminal nerve.
The user can repeat all of the above for the other models found in the original query in order to make comparisons between them. With all this information available, the researcher can develop a better understanding of the difference between the models as well as their similarities. If the neuroscientist is interested in developing a new model or exploring different mechanisms, then the database will provide information on which sets of parameters are the most appropriate to use in the simulations that will be performed.