In the domain of working memory, recent theories postulate that the maintenance of serial order is driven by position marking. According to this idea, serial order is maintained though associations of each item with an independent representation of the position that the item constitutes in the sequence. Recent studies suggest that those position markers are spatial in nature, with the beginning items associated with left side and the end elements with the right side of space (i.e., the ordinal position effect). So far however, it is unclear whether serial order is coded along the same principles in the verbal and the visuospatial domain. The aim of the current study was to investigate whether serial order is coded in a domain general fashion or not. To unravel this question, 6 experiments were conducted. The first 3 experiments revealed that the ordinal position effect is found with verbal but not with spatial information. In the subsequent experiments, the authors isolated the origin of this dissociation and conclude that to obtain spatial coding of serial order, it is not the nature of the encoded information (verbal, visual, or spatial) that is crucial, but whether the memoranda are semantically processed or not. This work supports the idea that serial order is coded in a domain general fashion, but suggests that position markers are only spatially coded when the to-be-remembered information is processed at the semantic level.

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Proactive interference occurs when previously learned information interrupts the storage or retrieval of new information. Congruent with previous reports, traditional analyses dealing with response times and error rates separately have indicated an increase in sensitivity to proactive interference in older adults. We reanalyzed the same data using diffusion decision model (DDM). Such models enable a more fine-grained interpretation concerning the latent processing mechanisms underlying performance. Now a different picture emerged. The DDM results showed that older adults needed more evidence than young adults before responding. The results also clearly indicated that peripheral processes (encoding time and motor execution), as well as recognition memory, decline with age. However, the drift rates, reflecting proactive interference, were similar, suggestingcontrary to earlier reports-that the inhibitory processes observed with this paradigm remain intact in older adults.

In a wide variety of cognitive domains, participants have access to several alternative strategies to perform a particular task and, on each trial, one specific strategy is selected and executed. Determining how many strategies are used by a participant as well as their identification at a trial level is a challenging problem for researchers. In the current paper, we propose a new method – the non-parametric mixture model – to efficiently disentangle hidden strategies in cognitive psychological data, based on observed response times. The developed method derived from standard hidden Markov modeling. Importantly, we used a model-free approach where a particular shape of a response time distribution does not need to be assumed. This has the considerable advantage of avoiding potentially unreliable results when an inappropriate response time distribution is assumed. Through three simulation studies and two applications to real data, we repeatedly demonstrated that the non-parametric mixture model is able to reliably recover hidden strategies present in the data as well as to accurately estimate the number of concurrent strategies. The results also showed that this new method is more efficient than a standard parametric approach. The non-parametric mixture model is therefore a useful statistical tool for strategy identification that can be applied in many areas of cognitive psychology. To this end, practical guidelines are provided for researchers wishing to apply the non-parametric mixture models on their own data set.