Automated Food-Procuring Movement-Related Neuronal Activity in the Basolateral Amygdala of the Rat

We studied the impulse activity of neurons of the basal and lateral amygdalar nuclei generated when experimental animals (rats) performed fast stereotyped food-procuring movements by the forelimb. Within the basolateral amygdala, there are neurons whose activity is related to different stages of getting off the food, and according to the characteristics of their spiking these neurons should be divided into a number of subpopulations. Activation forestalling the movement initiation by 0.5-1.0 sec was observed in most neurons of the basolateral amygdala; this is considered a manifestation of excitation related to a motivation component of the food-procuring behavior. Activation of amygdalar neurons following movement initiation can result from generation in this structure of additional excitation necessary for successful performance of a complete food-procuring motor cycle.     

Nearest Neighbor Classification Rule for Mixtures of Discrete and Continuous Random Variables

In this paper very simple nonparametric classification rule for mixtures of discrete and continuous random variables is described. It is based on the method of nearest neighbor proposed by Cover and Hart (1967). The bounds on the limit of the nearest neighbor rule risks are given. Both lower and upper bound depend on the Bayes risk and the loss function. Finally the method is compared with other existing methods on some practical data set.