scholarly journals The role of visual attention and high-level object information on short-term visual working memory in a change detection task.

2017 ◽  
Vol 17 (10) ◽  
pp. 61 ◽  
Author(s):  
Moreno Coco ◽  
Antje Nuthmann ◽  
Sergio Della Sala
Keyword(s):  
Working Memory ◽  
Visual Attention ◽  
Change Detection ◽  
Visual Working Memory ◽  
Detection Task ◽  
Change Detection Task ◽  
Short Term ◽  
High Level

scholarly journals Unsupervised Online Assessment of Visual Working Memory in 4- to 10-Year-Old Children: Array Size Influences Capacity Estimates and Task Performance

2021 ◽  
Vol 12 ◽  
Author(s):  
Shannon Ross-Sheehy ◽  
Esther Reynolds ◽  
Bret Eschman
Keyword(s):  
Working Memory ◽  
Change Detection ◽  
Visual Working Memory ◽  
Detection Task ◽  
Array Size ◽  
Online Testing ◽  
Change Detection Task ◽  
Mixed Effect ◽  
Effect Analysis ◽  
Capacity Estimates

The events of the COVID-19 Pandemic forced many psychologists to abandon lab-based approaches and embrace online experimental techniques. Although lab-based testing will always be the gold standard of experimental precision, several protocols have evolved to enable supervised online testing for paradigms that require direct observation and/or interaction with participants. However, many tasks can be completed online in an unsupervised way, reducing reliance on lab-based resources (e.g., personnel and equipment), increasing flexibility for families, and reducing participant anxiety and/or demand characteristics. The current project demonstrates the feasibility and utility of unsupervised online testing by incorporating a classic change-detection task that has been well-validated in previous lab-based research. In addition to serving as proof-of-concept, our results demonstrate that large online samples are quick and easy to acquire, facilitating novel research questions and speeding the dissemination of results. To accomplish this, we assessed visual working memory (VWM) in 4- to 10-year-old children in an unsupervised online change-detection task using arrays of 1–4 colored circles. Maximum capacity (max K) was calculated across the four array sizes for each child, and estimates were found to be on-par with previously published lab-based findings. Importantly, capacity estimates varied markedly across array size, with estimates derived from larger arrays systematically underestimating VWM capacity for our youngest participants. A linear mixed effect analysis (LME) confirmed this observation, revealing significant quadratic trends for 4- through 7-year-old children, with capacity estimates that initially increased with increasing array size and subsequently decreased, often resulting in estimates that were lower than those obtained from smaller arrays. Follow-up analyses demonstrated that these regressions may have been based on explicit guessing strategies for array sizes perceived too difficult to attempt for our youngest children. This suggests important interactions between VWM performance, age, and array size, and further suggests estimates such as optimal array size might capture both quantitative aspects of VWM performance and qualitative effects of attentional engagement/disengagement. Overall, findings suggest that unsupervised online testing of VWM produces reasonably good estimates and may afford many benefits over traditional lab-based testing, though efforts must be made to ensure task comprehension and compliance.

The Nature of Haptic Working Memory Capacity and Its Relation to Visual Working Memory

2020 ◽  
Vol 33 (8) ◽  
pp. 837-864
Author(s):  
Taku Morimoto
Keyword(s):  
Working Memory ◽  
Change Detection ◽  
Visual Working Memory ◽  
Working Memory Capacity ◽  
Storage System ◽  
Colour Change ◽  
Detection Task ◽  
Change Detection Task ◽  
Dual Task Paradigm ◽  
Visual Shape

Abstract I conducted three experiments to investigate haptic working memory capacity using a haptic change detection task with 2D stimuli. I adopted a single-task paradigm comprising haptic single-feature (orientation or texture) and haptic multifeature (orientation and texture) conditions in Experiment 1 and a dual-task paradigm with a primary haptic orientation or texture change detection task and a concurrent secondary visual shape or colour change detection task in Experiments 2–3. I observed that in the single-task paradigm, haptic change detection capacity was higher for single features than it was for multiple features. In haptic working memory, unlike in visual working memory, features of two different dimensions within an object cannot be integrated. In the dual-task paradigm, interference was observed when the concurrent visual shape change detection task was combined with the haptic orientation change detection task although interference was not observed when the concurrent visual colour change detection task was combined with it. In addition, the concurrent visual shape or colour change detection task did not interfere with the capacity for haptic texture memory, which was higher than that for haptic orientation memory. These findings demonstrate that geometric properties perhaps retained a common storage system shared between haptic working memory and visual working memory; however, haptic texture might be retained in an independent stable storage system that is haptic-specific.

Visual working memory for letters varies with familiarity but not complexity

2018 ◽  
Author(s):  
William Xiang Quan Ngiam ◽  
Kimberley L. C. Khaw ◽  
Alex O. Holcombe ◽  
Patrick T. Goodbourn
Keyword(s):  
Working Memory ◽  
Change Detection ◽  
Visual Working Memory ◽  
Detection Task ◽  
Stimulus Complexity ◽  
Object Representations ◽  
Change Detection Task ◽  
English Alphabet ◽  
Character Set ◽  
Change Detection Performance

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 two 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 modelled 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/sec; ~4 items) than for unfamiliar alphabets (~12 items/sec; ~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.

Vivid Imagers Are Better at Detecting Salient Changes

2006 ◽  
Vol 27 (4) ◽  
pp. 218-228 ◽  
Author(s):  
Paul Rodway ◽  
Karen Gillies ◽  
Astrid Schepman
Keyword(s):  
Individual Differences ◽  
Change Detection ◽  
Visual Imagery ◽  
Detection Task ◽  
Level Of Detail ◽  
Detection Accuracy ◽  
Change Detection Task ◽  
Term Change ◽  
High Level

This study examined whether individual differences in the vividness of visual imagery influenced performance on a novel long-term change detection task. Participants were presented with a sequence of pictures, with each picture and its title displayed for 17  s, and then presented with changed or unchanged versions of those pictures and asked to detect whether the picture had been changed. Cuing the retrieval of the picture's image, by presenting the picture's title before the arrival of the changed picture, facilitated change detection accuracy. This suggests that the retrieval of the picture's representation immunizes it against overwriting by the arrival of the changed picture. The high and low vividness participants did not differ in overall levels of change detection accuracy. However, in replication of Gur and Hilgard (1975) , high vividness participants were significantly more accurate at detecting salient changes to pictures compared to low vividness participants. The results suggest that vivid images are not characterised by a high level of detail and that vivid imagery enhances memory for the salient aspects of a scene but not all of the details of a scene. Possible causes of this difference, and how they may lead to an understanding of individual differences in change detection, are considered.

scholarly journals The Role of Phonological and Visual Working Memory in Carry Operations or Intermediate Solutions in Complex Mental Arithmetic

2021 ◽  
Author(s):  
◽  
Wei Dai
Keyword(s):  
Working Memory ◽  
Change Detection ◽  
Visual Working Memory ◽  
Visual Processing ◽  
Mental Arithmetic ◽  
Arithmetic Operation ◽  
Phonological Working Memory ◽  
Mental Addition ◽  
Memory Resources

<p>The present research comprises four experiments designed to explore the role of visual and phonological working memory resources in carry operations or intermediate solutions in complex mental addition and multiplication. A special consideration was given to the effect of arithmetic operation on the relative involvement of visual and phonological resources in complex addition and multiplication.  A pilot study was conducted prior to the experiments, aiming to examine the suitability of visual and phonological stimuli for change detection and working memory capacity estimation. Two staff of Victoria University of Wellington with normal or corrected vision attended the pilot study as participants. Pilot Experiments 1 to 4 tested the suitability for probing visual working memory (VWM) capacity of two types of visual stimulus with different feature dimensions: bars of different orientations and Gabor patches with different orientations and spatial frequencies. A single-probe change-detection experimental paradigm was used, with participants making decisions about whether or not probe items were the same as memory items presented previously. Both presentation durations and set sizes were manipulated. Stable estimates of visual working memory capacities were found when Gabor patches with varied spatial frequencies were used, suggesting its utility as a probe for estimating visual working memory capacity. Pilot Experiment 5 was designed to examine the suitability of pronounceable consonant-vowel-consonant non-words as a probe of phonological working memory (PWM). Valid estimates of PWM capacity were found for both participants, suggesting the suitability of phonological non-words as phonological stimuli of assessing PWM capacities and interfering with information phonologically-represented and maintained in working memory.  Experiments 1 to 4 investigated the relative involvement of visual and phonological working memory resources in carry operations or intermediate solutions in mental addition and multiplication. Fifty-six undergraduate students of Victoria University of Wellington participated all experiments, and 48 of them provided valid data for final analysis. A dual-task interference paradigm was used in all experiments, with arithmetic tasks and visual/phonological change-detection tasks either performed alone, or simultaneously. For arithmetic tasks, double-digit addition problems and multiplication problems comprising one single-digit and one double-digit were presented horizontally and continuously, and participants reported the final solutions verbally. For visual change-detection tasks, study items were visually presented to participants for 1,000ms before they disappeared. After a 4000ms retention interval, a probe item was presented and participants judged whether the probe item was the same as one of the memory items. For phonological change-detection tasks, phonological nonwords were verbally presented to participants sequentially. After a 4000ms retention interval, a probe nonword was presented to participants, and they indicated whether or not the probe was the same as one of the study non-words. Both numbers of carry operations involved in the arithmetic problems (zero, one, and two) and levels of visual/phonological loads (low, medium, and high) were manipulated in all experiments.   For all experiments, the effect of the number of carry operations on calculation performance was observed: arithmetic problems involving more carry operations were solved less rapidly and accurately. This effect was enlarged by concurrent visual and phonological loads, evidenced by significant interactions between task conditions and number of carry operations observed in the accuracy analyses of the arithmetic tasks in all experiments except Experiment 2, in which multiplication problems were solved under visual loads. These findings suggest that both visual and phonological resources are required for the temporary storage of intermediate solutions or carry information in mental addition, while for mental multiplication, only evidence for a role of phonological representations in carry operations was found.  For all experiments, the greater performance impairment of carry problems than no-carry problems associated with the presence of working memory loads was not further increased by increasing load level: There were no significant three-way interactions between task conditions, number of carry operations and load levels in accuracy analyses of arithmetic tasks. One possible explanation for this absence of significant three-way interactions might be attributable to some participants switching between phonological and visual working memory for the temporary storage of carrier information or intermediate solutions as a result of decreasing amount of available phonological or visual working memory resources.  In conclusion, the findings of the present research provide support for a role of both visual and phonological working memory resources in carry operations in mental addition, and a role of phonological working memory resources in carry operation in mental multiplication. Thus, it can be concluded that solving mental arithmetic problems involving carry-operations requires working memory resources. However, these results contradict the prediction of the Triple Code Model, which assumes addition mainly relies on visual processing, and multiplication mainly relies on verbal processing, while complex mental arithmetic is solved with the aid of visual processing regardless of the arithmetic operation. Thus, these results challenge the operation-specific involvement of working memory resources in complex mental arithmetic. However, it should be noted that the same arithmetic problems were solved three times by the same participants, which might have encouraged more activation in phonological processing than visual processing due to the practice effect.</p>

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