How Important Are Mental Representations in Cognitive Theories

1787 Words May 7th, 2005 8 Pages

How the world around us is represented mentally is the corner stone of cognitive architectures. It facilitates understanding of information received and perceived from our environment. The storage and retrieval of knowledge would be impossible without mental representations.

Mental representations are the way in which we create ‘copies' of the real things around us, which we perceive. A description of a representation is a symbol, sign, image or a depiction that takes the place of a real object in the real world.
Representations were broadly categorised into three. The ‘analogue representation' the ‘propositional representation' and ‘procedural rules'. Analogue
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Unlike schema theory ACT* is modular and processing is strictly serial. Information retrieved from declarative memory is achieved via a spreading activation. The procedural memory has to check conditions (rules) in the long-term memory with the working memory active node patterns to achieve a match. This gives rise to a bottle-neck in processing as the pattern matching is serial. Goals are achieved by acting on production rules in a prescriptive hierarchy.
The last comparison is the PDP model. This model has a network structure whose mental representations are sub symbolic. It has a structure where elementary units (compared to neurons in the brain) are connected together and like schema relates only to long-term memory not addressing overall structure. The nodes themselves do not hold the meaning but meaning is represented in the patterns of activation across the network or a number of localised nodes.

A Multi-layered Connectivist Network

Output units

Hidden units

Input units

The difference between the pattern matching here and that seen in ACT* is tat PDP is parallel processing and not serial and so is faster at processing.

Schema theory gives a good account of top down effects on what we learn or remember. However, the detail in the process and the how in learning are not specified very well.
ACT* gives a good account of how skill learning takes place by proceduralisation. This is not so

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