Modelling serial order in behaviour: studies of spelling

Serial order in behaviour remains an interesting problem for computational modelling in psychology, especially for connectionist approaches. The 'Competitive Queuing' (CQ) approach to sequence generation has the advantage of accounting for a number of common features apparent in several different types of serial behaviour. This thesis addresses the general account which the CQ approach can give for constraints on serial errors within sequences by developing models of an acquired disorder of spelling, 'graphemic buffer disorder' (GBD). Two approaches to the development of a simple initial model of GBD into more complex models are demonstrated, and are related to the general problem of accounting for serial category constraints in sequencing. The initial CQ model of GBD is based on an existing model of speech production with minimal spelling-specific changes. A number of shortcomings are identified in the I performance of this model, in particular the inability to distinguish consonant and vowel letters, which prevents a striking feature of GBD errors - the preservation of consonant/vowel status - from being modelled. An analysis of the general problem of adding domain-specific constraints to CQ models suggests two approaches to improving the initial model. Two alternative extended models are thus advanced. The first is a development of the initial model incorporating an external template to specify consonant/vowel information. Simulations with this model demonstrate a much improved fit to :the data. The second model" develops a novel architecture, generalising the CQ approach to multi-layer networks. The model is less detailed but demonstrates the correct general features of the GBD error pattern. The relationship between the models is discussed and possible future research directions are identified

Dynamic Representation of Structural Constraints in Models of Serial Behaviour

The Competitive Queuing (CQ) approach to the generation of serial order views sequential behaviour as the result of competition between a set of alternative responses all activated in parallel. This type of model can show a general error pattern when damaged which is very like that of psychological subjects in several different modalities and paradigms. However, many forms of serial behaviour are subject to tight, domain-specific constraints on just which sequences can be produced. Such constraints are revealed in the fine structure of the errors which subjects make. This paper identifies two general strategies for the representation of such domain-specific sequential constraints within the overall framework of CQ. These approaches are discussed in the context of a number of different models in the domains of speech generation and spelling. 1 Introduction Neural networks are parallel machines. When used to generate behaviour, rather than as perceptual systems, they lend themselves nat..