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AFFORDANCES AND COMPATIBILITY EFFECTS: A NEURAL-NETWORK COMPUTATIONAL MODEL

机译:可带来和兼容性效果:神经网络计算模型

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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.
机译:行为和脑成像证据表明,看到物体自动唤起“可取性”,例如,它倾向于激活与执行精度或功率夹具相关的内部表示。根据本证据,Tucker和Ellis [1]发现了物体大小(小而大)之间的兼容性效果,以及用于响应看到对象是否是人工制品或自然物体的种类之间的兼容性效果。这项工作提出了一种神经网络模型,表明与最近关于前额叶皮质的一般功能的理论一致地解释这些实验。前额叶皮质被视为携带不同信息的多种神经途径的行为表达竞争中的自上而下偏差的来源。该模型成功地再现了兼容性效应的实验结果,并展示了如何,尽管这种偏置使生物能够执行与物体带来的那些不同的动作,但这些仍然 - 施加对反应时间反映的影响的影响。

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