Associative memory and segmentation in an oscillatory neural model of the olfactory bulb.

We discuss the first few stages of olfactory processing in the framework of a layered neural network. Its central component is an oscillatory associative memory, describing the external plexiform layer, that consists of inhibitory and excitatory neurons with dendrodendritic interactions. We explore the computational properties of this neural network and point out its possible functional role in the olfactory bulb.

Medical volume rendering over the WWW using VRML and JAVA.

The rapid growth of the World Wide Web (WWW) enables access to huge amounts of data and applications. The diversity of data-structures and applications has led to the concept of network computing where the data is encapsulated within the application. The end-user does not have to worry about tools for data manipulation as they are bundled together with the data itself.

The role of inhibition in an associative memory model of the olfactory bulb.

The external plexiform layer is where the interactions between the mitral (excitatory) and granule (inhibitory) cells of the olfactory bulb (OB) take place. Two outstanding features of these interactions are that they are dendrodendritic and that there seem to be none between excitatory cells. The latter are usually credited with the role of forming Hebbian cell assemblies.

Decomposition of a mixture of signals in a model of the olfactory bulb.

We describe models for the olfactory bulb which perform separation and decomposition of mixed odor inputs from different sources. The odors are unknown to the system; hence this is an analog and extension of the engineering problem of blind separation of signals. The separation process makes use of the different temporal fluctuations of the input odors which occur under natural conditions.