Cognitive modelling of attentional networks: efficiencies, interactions, impairments and development

According to the attention network theory, attention is viewed as an organ system comprising specialised networks that carry out functions of alerting, orienting and executive control. The Attention Network Test (ANT) is a simple and popular experiment that measures the efficiencies and interactions of these three subcomponents of attention in a single task, and has been used for adults, children and attention deficit patients. In this thesis, cognitive modelling is used as a research tool to simulate the performance of subjects on the ANT, as well as variations of the ANT using ACT-R 6.0 cognitive architecture. All models are validated against human data using various goodness-of-fit criteria at multiple measures of the latency, accuracy and efficiency of the three networks.
Once the simulation of healthy human performance on the ANT is established, modifications inspired by psychology literature are made to simulate the performance on ANT by children and patients affected with Alzheimer‘s disease (AD) and mild traumatic brain injury (mTBI). The implementation of networks, their interactions and impairments in the models are shown to be theoretically grounded. Based on the simulation results and the understanding gained through model processes, a number of novel predictions are made, behaviour of the networks and a few discrepancies in human data are explained. The model predicts that in the case of Alzheimer‘s disease, the orienting network may be impaired and cueing may have a positive effect on conflict resolution. Also, in the case of mTBI, it was predicted that the validity effect may be impaired only in the earlier weeks after the injury. For children, a possible relationship between processing speed and mechanism of inhibitory control is predicted. It is posited that there is not always a 'global clock' that controls processing speed and further different processes may be running with different processing times.