Different effects of unexpected changes in environmental conditions on prepulse inhibition in rats and humans

The reduction of the startle response to an auditory stimulus caused by the presentation of another stimulus of lower intensity closely preceding it, a phenomenon known as prepulse inhibition (PPI), can be modulated by changes in dopaminergic activity. Schmajuk, Larrauri, De la Casa, and Levin (2009) demonstrated that this dopaminergic modulation of PPI in rats can be influenced by manipulating the experimental context, specifically by introducing changes in the ambient lighting condition that include novel elements. In this paper we analyze the effects of introducing changes in context illumination on PPI in male rats (Experiment 1) and humans (Experiment 2). The results with rats showed a reduction of PPI when the illumination condition switched from dark to light, but not from light to dark. In the experiment with human participants the reduction of PPI occurred for both changes in illumination conditions. The animal experiment results are interpreted in terms of competing exploratory behavior that appear when the context is illuminated after the dark–light transition; while in the case of human participants a perceptual and/or attentional mechanism after both illumination transitions is proposed, which may result in a reduced processing of the prepulse and subsequent lower PPI.Junta de Andalucía SEJ-02618Ministerio de Ciencia e Innovación de España PSI2009-753

Computational Models of Classical Conditioning guest editors’ introduction

In the present special issue, the performance of current computational models of classical conditioning was evaluated under three requirements: (1) Models were to be tested against a list of previously agreed-upon phenomena; (2) the parameters were fixed across simulations; and (3) the simulations used to test the models had to be made available. These requirements resulted in three major products: (a) a list of fundamental classical-conditioning results for which there is a consensus about their reliability; (b) the necessary information to evaluate each of the models on the basis of its ordinal successes in accounting for the experimental data; and (c) a repository of computational models ready to generate simulations. We believe that the contents of this issue represent the 2012 state of the art in computational modeling of classical conditioning and provide a way to find promising avenues for future model development

Stimulus configuration, classical conditioning, and hippocampal function

Hippocampal participation in classical conditioning is described in terms of a multilayer network that portrays stimulus configuration. The network (a) describes behavior in real time, (b) incorporates a layer of "hidden " units positioned between input and output units, (c) includes inputs that are connected to the output directly as well as indirectly through the hidden-unit layer, and (d) uses a biologically plausible backpropagation procedure to train the hidden-unit layer. Nodes and connections in the neural network are mapped onto regional cerebellar, cortical, and hippocampal circuits, and the effect of lesions of different brain regions is formally studied. Computer simulations of the following classical conditioning paradigms are presented: acquisition of delay and trace conditioning, extinction, acquisition-extinction series of delay conditioning, blocking, overshadowing, discrimination acquisition, discrimination reversal, feature-positive discrimination, conditioned inhibition, negative patterning, positive patterning, and generalization. The model correctly describes the effect of hippocampal and cortical lesions in many of these paradigms, as well as neural activity in hippocampus and medial septum during classical conditioning. Some of these results might be extended to the description of anterograde amnesia in human patients. In spite of the vast amount of behavioral and physiologica