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Computational characterization of the role of an attention schema in controlling visuospatial attention
We found that the more uncertain the agent was about the location of its attentional window, the more it benefited from these additional resources, which developed an attention schema.
Characterising representation dynamics in recurrent neural networks for object recognition
Recurrent neural networks (RNNs) have yielded promising results for both recognizing objects in challenging conditions and modeling aspects of primate vision.
End-to-end topographic networks as models of cortical map formation and human visual behaviour: moving beyond convolutions
Computational models are an essential tool for understanding the origin and functions of the topographic organisation of the primate visual system.
Semantic scene descriptions as an objective of human vision
Interpreting the meaning of a visual scene requires not only identification of its constituent objects, but also a rich semantic characterization of object interrelations.
The neuroconnectionist research programme
Artificial Neural Networks (ANNs) inspired by biology are beginning to be widely used to model behavioral and neural data, an approach we call neuroconnectionism.
