Unified theories of cognition
The perception of multiple objects: a connectionist approach
The perception of multiple objects: a connectionist approach
The computational brain
The Architecture of Cognition
Testing the Efficiency and Independence of Attentional Networks
Journal of Cognitive Neuroscience
Affective effects of program visualization
Proceedings of the second international workshop on Computing education research
Human Attentional Networks: A Connectionist Model
Journal of Cognitive Neuroscience
Modelling the Efficiencies and Interactions of Attentional Networks
Attention in Cognitive Systems
Mechanisms for human spatial competence
SC'06 Proceedings of the 2006 international conference on Spatial Cognition V: reasoning, action, interaction
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An increasing body of evidence has shown that attention is a multi-type and multilevel cognitive faculty. The dominant computational modeling approaches to attention have often focused on one specific type of attention at one specific level. In particular, various connectionist modeling techniques at the subsymbolic level have been widely adopted. In this paper, we report a symbolic computational model of the Attentional Network Test, which simultaneously involves different types of attention (alerting, orienting, and executive control), each subserved by distinctive attentional networks in the brain. The model was developed in ACT-R, a rule-based cognitive architecture. The results show that the model, by sequentially firing rules at a rate of about one every 40 ms, was able to capture the effect of each attentional network. The model implies that while the attentional networks can be distinguished at both neuroanatomical and behavioral levels, different attentional networks may adopt similar computational operations at least at a symbolic rule level.