Catalyzing communities of research rigour champions.

The biomedical sciences must maintain and enhance a research culture that prioritizes rigour and transparency. The US National Institute of Neurological Disorders and Stroke convened a workshop entitled 'Catalyzing Communities of Research Rigor Champions' that brought together a diverse group of leaders in promoting research rigour and transparency (identified as 'rigour champions') to discuss strategies, barriers and resources for catalyzing technical, cultural and educational changes in the biomedical sciences. This article summarizes 2 days of panels and discussions and provides an overview of critical barriers to research rigour, perspectives behind reform initiatives and considerations for stakeholders across science. Additionally, we describe applications of network science to foster, maintain and expand cultural changes related to scientific rigour and opportunities to embed rigourous practices into didactic courses, training experiences and degree programme requirements. We hope this piece provides a primer for the wider research community on current discussions and actions and inspires individuals to build, join or expand collaborative networks within their own institutions that prioritize rigourous research practices.

Object-based encoding constrains storage in visual working memory.

The fundamental unit of visual working memory (WM) has been debated for decades. WM could be object-based, such that capacity is set by the number of individuated objects, or feature-based, such that capacity is determined by the total number of feature values stored. The present work examined whether object- or feature-based models would best explain how multifeature objects (i.e., color/orientation or color/shape) are encoded into visual WM. If maximum capacity is limited by the number of individuated objects, then above-chance performance should be restricted to the same number of items as in a single-feature condition. By contrast, if the capacity is determined by independent storage resources for distinct features-without respect to the objects that contain those features-then successful storage of feature values could be distributed across a larger number of objects than when only a single feature is relevant. We conducted four experiments using a whole-report task in which subjects reported both features from every item in a six-item array. The crucial finding was that above-chance recall-for both single- and multifeatured objects-was restricted to the first three or four responses, while the later responses were best modeled as guesses. Thus, whole-report with multifeature objects reveals a distribution of recalled features that indicates an object-based limit on WM capacity. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Distinguishing guesses from fuzzy memories: Further evidence for item limits in visual working memory.

There is consistent debate over whether capacity in working memory (WM) is subject to an item limit, or whether an unlimited number of items can be held in this online memory system. The item limit hypothesis clearly predicts guessing responses when capacity is exceeded, and proponents of this view have highlighted evidence for guessing in visual working memory tasks. Nevertheless, various models that deny item limits can explain the same empirical patterns by asserting extremely low fidelity representations that cannot be distinguished from guesses. To address this ambiguity, we employed a task for which guess responses elicited a qualitatively distinct pattern from low fidelity memories. Inspired by work from Rouder et al. (2014), we employed an orientation WM task that required subjects to recall the precise orientation of each of six memoranda presented 1 s earlier. The orientation stimuli were created by rotating the position of a "clock hand" inside a circular region that was demarcated by four colored quadrants. Critically, when observers guess with these stimuli, the distribution of responses is biased towards the center of these quadrants, creating a "banded" pattern that cannot be explained by a low precision memory. We confirmed the presence of this guessing pattern using formal model comparisons, and we show that the prevalence of this pattern matches observers' own reports of when they thought they were guessing. Thus, these findings provide further evidence for guessing behaviors predicted by item limit models of WM capacity.

Estimating the statistical power to detect set-size effects in contralateral delay activity.

The contralateral delay activity (CDA) is an event-related potential component commonly used to examine the online processes of visual working memory. Here, we provide a robust analysis of the statistical power that is needed to achieve reliable and reproducible results with the CDA. Using two very large EEG datasets that examined the contrast between CDA amplitude with set sizes 2 and 6 items and set sizes 2 and 4 items, we present a subsampling analysis that estimates the statistical power achieved with varying numbers of subjects and trials based on the proportion of significant tests in 10,000 iterations. We also generated simulated data using Bayesian multilevel modeling to estimate power beyond the bounds of the original datasets. The number of trials and subjects required depends critically on the effect size. Detecting the presence of the CDA-a reliable difference between contralateral and ipsilateral electrodes during the memory period-required only 30-50 clean trials with a sample of 25 subjects to achieve approximately 80% statistical power. However, for detecting a difference in CDA amplitude between two set sizes, a substantially larger number of trials and subjects were required; approximately 400 clean trials with 25 subjects to achieve 80% power. Thus, to achieve robust tests of how CDA activity differs across conditions, it is essential to be mindful of the estimated effect size. We recommend researchers designing experiments to detect set-size differences in the CDA collect substantially more trials per subject.

"Memory compression" effects in visual working memory are contingent on explicit long-term memory.

Brady, Konkle, and Alvarez (2009) argued that statistical learning boosts the number of colors that can be held online in visual working memory (WM). They showed that when specific colors are consistently paired together in a WM task, subjects can take optimal advantage of these regularities to recall more colors, an effect they labeled memory compression. They proposed that memory compression is a product of visual statistical learning, an automatic apprehension of statistical regularities that has been shown in prior work to be disconnected from explicit learning. If statistical learning enables an expansion of the number of individuated representations in visual WM, it would require revision of virtually all models of capacity in this online memory system. That said, this provocative claim is inconsistent with multiple studies that have found no improvement in WM performance following numerous repetitions of specific sample displays (e.g., Logie, Brockmole, & Vandenbroucke, 2009; Olson & Jiang, 2004). Here, we replicate the Brady et al. (2009) findings but show that memory compression effects were restricted to subjects who had perfect explicit recall of the color pairs at the end of the study, suggesting that statistical regularities boosted performance by enabling contributions from long-term memory. Thus, while memory compression effects provide an interesting example of the tight collaboration between online and offline memory representations, they do not provide evidence that statistical regularities can augment the number of individuated representations that can be concurrently stored in visual WM. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Visual working memory for letters varies with familiarity but not complexity.

Visual working memory (VWM) is limited in both the capacity of information it can retain and the rate at which it encodes that information. We examined the influence of stimulus complexity on these 2 limitations of VWM. Observers performed a change-detection task with English letters of various fonts or letters from unfamiliar alphabets. Average perimetric complexity (κ)-an objective correlate of the number of features comprising each letter-differed among the fonts and alphabets. Varying the time between the memory array and mask, we used change-detection performance to estimate the number of items held in VWM (K) as a function of encoding time. For all alphabets, K increased over 270 ms (indicating the rate of encoding) before reaching an asymptote (indicating capacity). We found that rate and capacity for each alphabet were unrelated to complexity: Performance was best modeled by assuming that both were limited by number of items (K), rather than by number of features (K × κ). We also found a higher encoding rate and capacity for familiar alphabets (∼45 items s-1; ∼4 items) than for unfamiliar alphabets (∼12 items s-1; ∼1.5 items). We then compared the familiar English alphabet to an unfamiliar artificial character set matched in complexity. Again, rate and capacity was higher for the familiar than for the unfamiliar stimuli. We conclude that rate and capacity for encoding into visual working memory is determined by the number of familiar feature-integrated object representations. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Correction: Relational encoding of objects in working memory: Changes detection performance is better for violations in group relations.

[This corrects the article DOI: 10.1371/journal.pone.0203848.].

Relational encoding of objects in working memory: Change detection performance is better for violations in group relations.

Research has indicated that working memory is based on forming relations between individual elements. In this study, we considered the congruency of object clusters during a change detection task. We demonstrate that changes which violate the relational encoding of a probe display (single-object changes where one object shifts independently from its corresponding group) are more easily detected than changes that maintain group structure (cluster changes where all objects in the group shift in location together)-despite cluster changes involving more objects moving overall. We explore this effect across interactions with direction of single-object movement (distancing from the cluster vs. uniting with the cluster) and trial order, demonstrating that naïve participants improve at a faster rate on single-object changes than cluster changes. It is concluded that storage in working memory functions by building relational bindings between objects and their place within the chunk, rather than by binding objects to their spatial location.