Shifting development in mid-childhood: the influence of between-task interference

Performance on the task-switching paradigm is greatly affected by the amount of conflict between tasks. Compared to adults, children appear to be particularly influenced by this conflict, suggesting that the ability to resolve interference between tasks improves with age. We used the task-switching paradigm to investigate how this ability develops in mid-childhood. Experiment 1 compared 5- to 8-year-olds’ and 9- to 11-year-olds’ ability to switch between decisions about the colour of an object and its shape. The 5- to 8-year-olds were slower to switch task and experienced more interference from the irrelevant task than the 9-to 11-year-olds, suggesting a developmental improvement in resolving conflict between tasks during mid-childhood. Experiment 2 explored this further, examining the influence of stimulus and response interference at different ages. This was done by separating the colour and shape dimensions of the stimulus and reducing overlap between responses. The results supported the development of conflict resolution in task-switching during mid-childhood. They also revealed that a complex interplay of factors, including the tasks used and previous experience with the task, affected children’s shifting performance.

Neural fields with sigmoidal firing rates: approximate solutions

Many tissue level models of neural networks are written in the language of nonlinear integro-differential equations. Analytical solutions have only been obtained for the special case that the nonlinearity is a Heaviside function. Thus the pursuit of even approximate solutions to such models is of interest to the broad mathematical neuroscience community. Here we develop one such scheme, for stationary and travelling wave solutions, that can deal with a certain class of smoothed Heaviside functions. The distribution that smoothes the Heaviside is viewed as a fundamental object, and all expressions describing the scheme are constructed in terms of integrals over this distribution. The comparison of our scheme and results from direct numerical simulations is used to highlight the very good levels of approximation that can be achieved by iterating the process only a small number of times.