Simulation of the autistic characteristics of attention shift impairment and novelty avoidance using self-organizing artificial neural networks

Autism is a developmental disorder with possibly multiple etiologies. Attention shift impairment and negative response to novelty are prevalent in individuals with autism and researchers argue which one of these two features is primary to other deficits in autism. Cortical feature maps make it possible to classify stimuli, such as phonemes of speech, disregarding incidental detail. Hierarchies of such maps are instrumental in creating abstract codes and representations of objects and events. It has been theorized that cortical feature maps in individuals with autism are inadequate for forming abstract codes and representations, explaining the importance paid to detail, rather than salient features. Self-Organizing Maps (SOMs) are artificial neural networks (ANNs) which offer insights into the development of cortical feature maps. We model the attention shift by presenting an ANN with stimuli from two sources in four different modes, namely: 1)novelty seeking (regarded as normal learning), 2) attention shift impairment (shifts are made with a low probability), 3)novelty avoidance (shifts made if the new stimulus is not too different from earlier stimuli and 4) novely avoidance in conjunction with attention shift impairment. The resulting feature maps from learning with novelty seeking and with attention shift impairment are, perhaps surprisingly, much the same. In contrast, the resulting maps from learning with novelty avoidance are adapted to one of the sources at the expense of the other and if one of the sources has a reduced set of stimuli the resulting maps are adapted to stimuli from that reduced source. When ANNs with an excess of nodes are employed, the resulting maps from learning with novelty avoidance are strikingly different, either normal or restricted to the reduced source. Such learning, in many different maps, would result in very uneven capacities, common in individuals with autism Learning with attention shift impairment in conjunction with novely avoidance further reduces the probabilities for normal maps.