Rabbits were trained to discriminate patterns consisting of straight bars and rows of dots of different orientation. It was found that using proximal pattern presentation, at a distance of 5 cm in front of the animal, dot rows of different orientation are not discriminated on the basis of tilt extrapolation, but by the use of regional cues.

We consider linear discriminant analysis in the setting where the objects signals images have many dimensions samples pixels and there are relatively few training samples We discuss ways that time frequency dictionaries can be used to adaptively select a small set of derived features which lead to improved misclassi cation rates

Fourteen cats were trained to discriminate between 5 and 20 s periods of confinement as evidenced by differential responding to two feeders. In a subsequent titration procedure the cats discriminated 5 from 10 or even 8 s. Positional mediation of correct responses was observed only in some animals. The present task may complement the classical and operant conditioning situations in which the te...

In a seminal article, Todd (Journal of Experimental Psychology: Human Perception and Performance 7:795-810, 1981) reported a difference threshold of about 50 ms to discriminate the times of arrival of two differently sized objects that simultaneously approached head-on at constant but different velocities. Subsequent investigators, however, have often found much higher thresholds. We did one co...

Introduction Previous functional neuroimaging studies have demonstrated a brain network responsible of time discrimination (TD) processes, which may play significant mediating role in other cognitive such as change detection and control. The study TD its dysfunction psychosis has become matter growing interest. We hypothesize that the impairment is involved both mechanisms deficit presented by ...

For time series discrimination,the main idea behind the proposed approach is to use a variance/covariance criterion to strengthen or weaken aligned observations according to their contribution to the variability within and between classes. To this end, the classical variance/covariance expression is extended to a set of time series, as well as to a partition of time series.