The Parallel Distributed Processing Approach

The Parallel Distributed Processing (PDP) model of memory is based on the idea that the brain does not function in a series of activities but rather performs a range of activities at the same time, parallel to each other. PDP differs from other models as it does not focus on distinctions among different kinds of memory. Instead it proposes that cognitive processes can be represented by a model in which activation flows through networks that link together neuron-like units or nodes, i.e. Parallel - more than one process occurring at a time; distributed processing - processing occurring in a number of different locations. For example, information about a person, object or event is stored in several interconnected units rather than in a single place. This approach to memory explains why people can still come to a correct conclusion even when incorrect information has been given. We are also able to make generalisations based on the links between information that were already know.

Learning involves gaining access to one or more of these units, which then activate the other units and re-create your knowledge of the object, event. Each unit is involved in the representation of several different individuals or objects. James McClelland is one of the major developers of the PDP Approach. He described how our knowledge might be stored by connections that link these people with their personal characteristics. According to the PDP Approach, memory consists of networks of units linked according to varying connection weights; when a unit reaches a critical level of activation, it may affect another unit either by exciting it (if the connection weight is positive) or by inhibiting it (if the connection weight is negative). Cognitive processes involve parallel operations; new events change the strength of the connections, but sometimes we have only partial memory for some information, rather than complete, perfect memory. The brains ability to produce partial is called graceful degradation. There are many advantages to the PDP Approach:

The PDP Approach has generated tremendous enthusiasm, though it works better for pattern recognition, categorisation, and memory search than for higher mental processes that are more serial in nature; the approach is so new that it cannot yet be evaluated adequately.
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