Modelling the Efficiencies and Interactions of Attentional Networks

Authors:
Fehmida Hussain;Sharon Wood
Affiliations:
Representation & Cognition Group, Department of Informatics, University of Sussex, Falmer, UK BN1 9QJ;Representation & Cognition Group, Department of Informatics, University of Sussex, Falmer, UK BN1 9QJ
Venue:
Attention in Cognitive Systems
Year:
2009

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Abstract

Posner and colleagues [38,40] assert that attention comprises three distinct anatomical areas of the brain responsible for separate aspects of attention, namely alerting, orienting and executive control. Based on this view of attention, the work presented here computationally models the attentional networks task (ANT) which can be used to assess the efficiency and interactions of these disparate networks, collectively responsible for different functions related to attention mechanisms. The present research builds upon the model of ANT to show the modulation effects of one network on the other and suggests how the model can be used to simulate neglect conditions related to attention. The model is evaluated against data sets from experimental studies and the model's fit to data is assessed statistically. Building such models of attention benefits computer vision research, as they are, well informed from both cognitive psychology and neuroscience perspectives.