AI Medical Compendium Topic:
Attention

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Selection-for-action emerges in neural networks trained to learn spatial associations between stimuli and actions.

Cognitive processing
The objects present in our environment evoke multiple conflicting actions at every moment. Thus, a mechanism that resolves this conflict is needed in order to avoid the production of chaotic ineffective behaviours. A plausible candidate for such role...

Neuromodelling based on evolutionary robotics: on the importance of motor control for spatial attention.

Cognitive processing
Mainstream approaches to modelling cognitive processes have typically focused on (1) reproducing their neural underpinning, without regard to sensory-motor systems and (2) producing a single, ideal computational model. Evolutionary robotics is an alt...

Learning feature representations with a cost-relevant sparse autoencoder.

International journal of neural systems
There is an increasing interest in the machine learning community to automatically learn feature representations directly from the (unlabeled) data instead of using hand-designed features. The autoencoder is one method that can be used for this purpo...

Robot teachers: The very idea!

The Behavioral and brain sciences
Insufficient attention has been paid to the use of robots in classrooms. Robot "teachers" are being developed, but because Kline ignores such technological developments, it is not clear how they would fit within her framework. It is argued here that ...

Use of Robotic Pets in Providing Stimulation for Nursing Home Residents with Dementia.

Studies in health technology and informatics
Trial experiments utilized robotic pets to facilitate self-reliance in nursing home residents. A remote-control robot modeled clear and meaningful behaviors to elderly residents. Special attention was paid to its effects on mental and social domains....