Analyzing sensory data using non-linear preference learning with feature subset selection

15th European Conference on Machine Learning, Pisa, Italy, September 20-24, 2004The quality of food can be assessed from different points of view. In this paper, we deal with those aspects that can be appreciated through sensory impressions. When we are aiming to induce a function that maps object descriptions into ratings, we must consider that consumers’ ratings are just a way to express their preferences about the products presented in the same testing session. Therefore, we postulate to learn from consumers’ preference judgments instead of using an approach based on regression. This requires the use of special purpose kernels and feature subset selection methods. We illustrate the benefits of our approach in two families of real-world data base

Geometry and dimensionality reduction of feature spaces in primary visual cortex

Some geometric properties of the wavelet analysis performed by visual neurons are discussed and compared with experimental data. In particular, several relationships between the cortical morphologies and the parametric dependencies of extracted features are formalized and considered from a harmonic analysis point of view

Visuomotor association orthogonalizes visual cortical population codes

The brain should be best able to associate distinct behavioral responses to sensory stimuli if these stimuli evoke population firing patterns that are close to orthogonal. To investigate whether task training orthogonalizes population codes in primary visual cortex (V1), we measured the orientation tuning of 4,000-neuron populations in mouse V1 before and after training on a visuomotor task. The effect of task training on population codes could be captured by a simple mathematical transformation of firing rates, which suppressed responses to motor-associated stimuli, but only in cells responding to them at intermediate levels. This transformation orthogonalized the representations of the task orientations by sparsening the population responses to these stimuli. The strength of response transformation varied from trial to trial, suggesting a dynamic circuit mechanism rather than static synaptic plasticity. These results indicate a simple process by which visuomotor associations orthogonalize population codes as early as in primary visual cortex

Gaze Behaviour during Space Perception and Spatial Decision Making

A series of four experiments investigating gaze behavior and decision making in the context of wayfinding is reported. Participants were presented with screen-shots of choice points taken in large virtual environments. Each screen-shot depicted alternative path options. In Experiment 1, participants had to decide between them in order to find an object hidden in the environment. In Experiment 2, participants were first informed about which path option to take as if following a guided route. Subsequently they were presented with the same images in random order and had to indicate which path option they chose during initial exposure. In Experiment 1, we demonstrate (1) that participants have a tendency to choose the path option that featured the longer line of sight, and (2) a robust gaze bias towards the eventually chosen path option. In Experiment 2, systematic differences in gaze behavior towards the alternative path options between encoding and decoding were observed. Based on data from Experiments 1 & 2 and two control experiments ensuring that fixation patterns were specific to the spatial tasks, we develop a tentative model of gaze behavior during wayfinding decision making suggesting that particular attention was paid to image areas depicting changes in the local geometry of the environments such as corners, openings, and occlusions. Together, the results suggest that gaze during a wayfinding tasks is directed toward, and can be predicted by, a subset of environmental features and that gaze bias effects are a general phenomenon of visual decision making