The Wisconsin Card Sorting Test (WCST) is commonly used to assess executive (dys-)function, particularly in neuropsychological patients. Performance on the test typically yields two types of error: perseverative errors, where participants persist in applying an inferred rule despite negative feedback, and set-loss errors, were participants cease applying an inferred rule despite positive feedback. The two types of error are known to dissociate. In this paper we apply an existing model of the WCST -- the model of Bishara et al. (2010) -- to a novel dataset, focussing specifically on the distribution of the two types of error over the duration of the task. Using Maximum Likelihood Estimation to fit the model to the data, we argue that the model provides a good account of the performance of some participants, but a poor account of individual differences. It is argued that this is because the model is essentially a competence model which fails to incorporate performance factors, and that accounting for the different types of error, and in particular the error distribution during the task, requires incorporating performance factors into the model. Some consequences of this for the broader enterprise of developing normative competence models are discussed.

 We present a schema-based model of a classicneuropsychological task, the Wisconsin Card Sorting Task(WCST), where competition between motor and cognitiveschemas is resolved using a variation of a neuroanatomicallydetailed model of the basal ganglia (Gurney et al., 2001). Weshow that the model achieves a good fit with existing data atthe group level, and correctly identifies two distinct cognitivemechanisms held to underlie two distinct types of error.However, at the individual level, the correlations amongstother error types produced by the model differ from thoseobserved in the human data. To address this, we clusterparticipant performance into distinct groups and show, byfitting each group separately, how the model can account forthe empirically observed correlations between error types.Methodologically, this demonstrates the importance ofmodelling participant performance at the sub-group orindividual level, rather than modelling group performance.We also discuss implications of the model for the WCSTperformance of elderly participants and Parkinson’s patients.

We present a computational model of sentence production thatemulates variation of the output of lexicalization andgrammatical encoding of the abstract pre-lexical message, interms of complexity and accuracy of the generated sentence aswell as fluency and cognitive costs of the sentence production.The model integrates approaches from routine action selectionmodels built on Dual Systems Theory (Norman & Shallice,1986) with ‘A Blueprint for the Speaker’ developed by Levelt(1989). The paper describes and justifies the modelarchitecture, explores factors affecting language variation inproduction, and applies the model for testing relationshipbetween complexity, accuracy, and fluency (CAF) of languageproduction as debated within Second Language Acquisition(SLA) research. A simulation that generated 78,750 sentencesprovides evidence of the trade-off relationship between CAFparameters as speakers have to sacrifice performance on one ofthe CAF factors in order to improve the remaining two.

In task switching, the n-2 repetition cost (informally, the elevation in RT associated with performing a recently abandoned task) is an indicator of residual task-set inhibition. One suggestion is that such inhibition is triggered by conflict between task-set elements. We present a novel computational model instantiating this proposal, by adding task-conflict monitoring units to an existing, interactive activation model of task switching. The model produces the empirical pattern, n-1 switch costs and n-2 repetition costs, as an intrinsic property of its architecture, but dependent on the inhibition of task demand units by the conflict detection mechanism. In a further simulation, we make predictions about n-2 repetition costs for asymmetric tasks, and show that one functional benefit of such a conflict-based, task inhibition mechanism is to facilitate topdown control of tasks by automatically reducing cross-task interference