AFFORDANCES AND COMPATIBILITY EFFECTS: A NEURAL-NETWORK COMPUTATIONAL MODEL

Behavioural and brain imaging evidence has shown that seeing objects automatically evokes "affordances", for example it tends to activate internal representations related to the execution of precision or power grips. In line with this evidence, Tucker and Ellis [1] found a compatibility effect between object size (small and large) and the kind of grip (precision and power) used to respond whether seen objects were artefacts or natural objects. This work presents a neural-network model that suggests an interpretation of these experiments in agreement with a recent theory on the general functions of prefrontal cortex. Prefrontal cortex is seen as a source of top-down bias in the competition for behavioural expression of multiple neural pathways carrying different information. The model successfully reproduces the experimental results on compatibility effects and shows how, although such a bias allows organisms to perform actions which differ from those suggested by objects' affordances, these still exert their influence on behaviour as reflected by longer reaction times.