Odor space and olfactory processing: Collective algorithms and neural implementation

Several basic olfactory tasks must be solved by highly olfactory animals, including background suppression, multiple object separation, mixture separation, and source identification. The large number N of classes of olfactory receptor cells—hundreds or thousands—permits the use of computational strategies and algorithms that would not be effective in a stimulus space of low dimension. A model of the patterns of olfactory receptor responses, based on the broad distribution of olfactory thresholds, is constructed. Representing one odor from the viewpoint of another then allows a common description of the most important basic problems and shows how to solve them when N is large. One possible biological implementation of these algorithms uses action potential timing and adaptation as the “hardware” features that are responsible for effective neural computation.

Visual attention to surfaces in three-dimensional space.

Although attention plays a significant role in vision, its spatial deployment and spread in the third dimension is not well understood. In visual search experiments we show that we cannot easily focus attention across isodepth loci unless they are part of a well-formed surface with locally coplanar elements. Yet we can easily spread our attention selectively across well-formed surfaces that span an extreme range of stereoscopic depths. In cueing experiments, we show that this spread of attention is, in part, obligatory. Attentional selectivity is reduced when targets and distractors are coplanar with or rest on a common receding stereoscopic plane. We conclude that attention cannot be efficiently allocated to arbitrary depths and extents in space but is linked to and spreads automatically across perceived surfaces.