Abstract
Higher-order cognitive functions can be seen as a class of cognitive processes which are crucial in situations requiring a flexible adjustment of behaviour in response to changing demands of the environment. The cognitive assessment of these functions often relies on tasks which admit a dynamic, or longitudinal, component requiring participants to flexibly adapt their behaviour during the unfolding of the task. An intriguing feature of such experimental protocols is that they allow the performance of an individual to change as the task unfolds. In this work, we propose a Latent Markov Model approach to capture some dynamic aspects of observed response patterns of both healthy and substance dependent individuals in a set-shifting task. In particular, data from a Wisconsin Card Sorting Test were analysed in order to represent performance trends in terms of latent cognitive states dynamics. The results highlighted how a dynamic modelling approach can considerably improve the amount of information a researcher, or a clinician, can obtain from the analysis of a set-shifting task.
Highlights
In recent years there has been an increasing interest in modelling behavioural data from experimental tasks aimed at investigating higher-level cognitive functions [1,2,3,4,5,6]
Results clearly show that our model is able to capture differences in performance trend between Control and substance dependent individuals (SDI) groups in terms of differences in their latent process transition dynamics
Results show that a three-state model is a reasonable choice if we want to differentiate dynamics in strategy shifting between groups
Summary
In recent years there has been an increasing interest in modelling behavioural data from experimental tasks aimed at investigating higher-level cognitive functions [1,2,3,4,5,6]. Higher-order cognitive functions can be seen as a class of cognitive processes which are crucial in situations requiring a flexible adjustment of behaviour in order to correspond to changing demands of the environment [7]. They allow previous experiences and feedback related information to be integrated in order to maximize optimal choices [8]. Negative feedback should allow participants to conceive a feature as irrelevant, modifying their responses In this context, observed response patterns could consist of the occurrences of casual errors, feedback-related errors, and perseverations on shifting tasks, to name a few (e.g., [12]). The basic idea is that these response patterns reflect the presence (or the absence) of a cognitive impairment, either at a functional or neural level [13]
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