Anxiety-like behavior in rats: a computational model

This work describes a neural network model of the rat exploratory behavior in the elevated plus-maze, a test used to study anxiety. It involves three parameters: drive to explore; drive to avoid aversive stimuli; and spontane ous locomotor activity. Each network unit corresponds to a specific locatio n in the maze and the connections, only between closest neighbors, represen t the possible adjacent places to which a virtual rat can navigate. Competi tive learning is used to generate a sequence of network states that corresp ond to the virtual rat successive locations in the maze. To evaluate the ge nerality of the model it was also tested for two modifications of the eleva ted plus-maze: one with totally closed arms and the other with totally open arms. The results are compared with data obtained with rats. The simulatio ns are consistent with experimental evidence and may provide an efficient w ay of describing the anxiety-like rat behavior in the elevated plus-maze. T his could be useful for researching the emotional parameters involved in th is anxiety animal model. (C) 2000 Elsevier Science Ltd. All rights reserved .