In this paper a neural network model of Visual Short-Term Memory (VSTM) is presented. The model links closely with Bundesen’s (1990) well-established mathematical theory of visual attention. We evaluate the model’s ability to fit experimental data from a classical whole and partial report study. Previous statistic models have successfully assessed the spatial distribution of visual attention; our neural network meets this standard and offers a neural interpretation of how objects are consolidated in VSTM at the same time. We hope that in the future, the model will be able to fit temporally dependent phenomena like the attentional blink effect, lag-1 sparing, and attentional dwell-time.
|Title of host publication||International Conference on Cognitive Modeling|
|Publication status||Published - 2009|
|Event||9th International Conference on Cognitive Modeling - Manchester, United Kingdom|
Duration: 24 Jul 2009 → 26 Jul 2009
Conference number: 9
|Conference||9th International Conference on Cognitive Modeling|
|Period||24/07/2009 → 26/07/2009|