How do recall requirements affect decision-making in free recall initiation? A linear ballistic accumulator approach.

Models of free recall describe free recall initiation as a decision-making process in which items compete to be retrieved. Recently, Osth and Farrell (Psychological Review, 126, 578-609, 2019) applied evidence accumulation models to complete RT distributions and serial positions of participants' first recalls in free recall, which resulted in some novel conclusions about primacy and recency effects. Specifically, the results of the modeling favored an account in which primacy was due to reinstatement of the start-of-the-list, and recency was found to be exponential in shape. In this work, we examine what happens when participants are given alternative recall instructions. Prior work has demonstrated weaker primacy and greater recency when fewer items are required to report (Ward & Tan, Memory & Cognition, 2019), and a key question is whether this change in instructions qualitatively changes the nature of the recall process, or merely changes the parameters of the recall competition. We conducted an experiment where participants studied six- or 12-item lists and were post-cued as to whether to retrieve a single item, or as many items as possible. Subsequently, we applied LBA models with various assumptions about primacy and recency, implemented using hierarchical Bayesian techniques. While greater recency was observed when only one item was required for output, the model selection did not suggest that there were qualitative differences between the two conditions. Specifically, start-of-list reinstatement and exponential recency functions were favored in both conditions.

Competitive guided search: meeting the challenge of benchmark RT distributions.

Historically, visual search models were mainly evaluated based on their account of mean reaction times (RTs) and accuracy data. More recently, Wolfe, Palmer, and Horowitz (2010) have demonstrated that the shape of the entire RT distributions imposes important constraints on visual search theories and can falsify even successful models such as guided search, raising a challenge to computational theories of search. Competitive guided search is a novel model that meets this important challenge. The model is an adaptation of guided search, featuring a series of item selection and identification iterations with guidance towards targets. The main novelty of the model is its termination rule: A quit unit, which aborts the search upon selection, competes with items for selection and is inhibited by the saliency map of the visual display. As the trial proceeds, the quit unit both increases in strength and suffers less saliency-based inhibition and hence the conditional probability of quitting the trial accelerates. The model is fitted to data the data from three classical search task that have been traditionally considered to be governed by qualitatively different mechanisms, including a spatial configuration, a conjunction, and a feature search (Wolfe et al., 2010). The model is mathematically tractable and it accounts for the properties of RT distributions and for error rates in all three search tasks, providing a unifying theoretical framework for visual search.

Dissociating models of visual working memory by reaction-time distribution analysis.

There have been heated debates on whether visual working memory (VWM) represents information in discrete-slots or a reservoir of flexible-resources. However, one key aspect of the models has gone unnoticed, the speed of processing when stored information in memory is assessed for accuracy. The present study evaluated contrasting predictions from the two models regarding the change detection decision times spent on the assessment of stored information by estimating the ex-Gaussian parameters from change detection RT distributions across different set sizes (2, 4, 6, or 8). The estimation showed that the Gaussian components µ and σ became larger as the set size increased from 2 to 4, but stayed constant as it reached 6 and 8, with an exponential component τ increasing at above-capacity set sizes. Moreover, we found that an individual's capacity limit correlates with the memory set size where the Gaussian µ reaches a plateau. These results indicate that the decision time for assessing in-memory items is constant regardless of memory set sizes whereas the time for the remaining not-in-memory items increases as the set size exceeds VWM storage capacity. The findings suggest that the discrete-slot model explains the observed RT distributions better than the flexible-resource model.

On the Dissociation of Word/Nonword Repetition Effects in Lexical Decision: An Evidence Accumulation Account.

A number of models of visual-word recognition assume that the repetition of an item in a lexical decision experiment increases that item's familiarity/wordness. This would produce not only a facilitative repetition effect for words, but also an inhibitory effect for nonwords (i.e., more familiarity/wordness makes the negative decision slower). We conducted a two-block lexical decision experiment to examine word/nonword repetition effects in the framework of a leading "familiarity/wordness" model of the lexical decision task, namely, the diffusion model (Ratcliff et al., 2004). Results showed that while repeated words were responded to faster than the unrepeated words, repeated nonwords were responded to more slowly than the nonrepeated nonwords. Fits from the diffusion model revealed that the repetition effect for words/nonwords was mainly due to differences in the familiarity/wordness (drift rate) parameter. This word/nonword dissociation favors those accounts that posit that the previous presentation of an item increases its degree of familiarity/wordness.

The Simon Effect With Saccadic Eye Movements.

In the Simon effect performance is faster and more accurate when the task-irrelevant spatial dimension of the stimulus corresponds to the location of the response, compared to when they do not correspond. In the prosaccade-antisaccade effect the latencies of saccades away from the stimulus location (i.e., antisaccades) are slower than the latencies of saccades toward the stimulus location (i.e., prosaccades). Because these two effects share a similar basis, the study of the Simon effect with saccadic eye movements needs to be decoupled from the prosaccade-antisaccade effect. A standard Simon task (Experiment 1) and a Simon task in which a distractor stimulus was also presented (Experiment 2) were implemented. In Experiment 1, results showed an effect likely attributable to the sum of the Simon effect and the prosaccade-antisaccade effect. In Experiment 2, in which the difference between the prosaccade and antisaccade was eliminated, only a Simon effect, cognitive in nature, manifested itself.

Serial vs. parallel models of attention in visual search: accounting for benchmark RT-distributions.

Visual search is central to the investigation of selective visual attention. Classical theories propose that items are identified by serially deploying focal attention to their locations. While this accounts for set-size effects over a continuum of task difficulties, it has been suggested that parallel models can account for such effects equally well. We compared the serial Competitive Guided Search model with a parallel model in their ability to account for RT distributions and error rates from a large visual search data-set featuring three classical search tasks: 1) a spatial configuration search (2 vs. 5); 2) a feature-conjunction search; and 3) a unique feature search (Wolfe, Palmer & Horowitz Vision Research, 50(14), 1304-1311, 2010). In the parallel model, each item is represented by a diffusion to two boundaries (target-present/absent); the search corresponds to a parallel race between these diffusors. The parallel model was highly flexible in that it allowed both for a parametric range of capacity-limitation and for set-size adjustments of identification boundaries. Furthermore, a quit unit allowed for a continuum of search-quitting policies when the target is not found, with "single-item inspection" and exhaustive searches comprising its extremes. The serial model was found to be superior to the parallel model, even before penalizing the parallel model for its increased complexity. We discuss the implications of the results and the need for future studies to resolve the debate.