scholarly journals Individual differences in visual attention: a short, reliable, open source, and multilingual test of multiple object tracking in PsychoPy

2020 ◽  
Vol 20 (11) ◽  
pp. 854
Author(s):  
Hauke Meyerhoff ◽  
Frank Papenmeier
Keyword(s):  
Individual Differences ◽  
Visual Attention ◽  
Object Tracking ◽  
Open Source ◽  
Multiple Object Tracking ◽  
Multiple Object

scholarly journals Individual Differences in Visual Attention: A Short, Reliable, Open Source, and Multilingual Test of Multiple Object Tracking in PsychoPy

2020 ◽  
Author(s):  
Hauke S. Meyerhoff ◽  
Frank Papenmeier
Keyword(s):  
Individual Differences ◽  
Visual Attention ◽  
Object Tracking ◽  
Open Source ◽  
Multiple Object Tracking ◽  
Object Motion ◽  
Laboratory Research ◽  
Multiple Object ◽  
Psychometric Measures ◽  
Interesting Approach

Individual differences in attentional abilities provide an interesting approach in studying visual attention as well as the relation of attention to other psychometric measures. However, recent research has demonstrated that many tasks from experimental research are not suitable for individual differences research as they fail to capture these differences reliably. Here, we provide a test for individual differences in visual attention which relies on the multiple object tracking task (MOT). This test captures individual differences reliably in 6-15 minutes. Within the task the participants have to maintain a set of targets (among identical distractors) across an interval of object motion. It captures the efficiency of attentional deployment. Importantly, this test was explicitly designed and tested for reliability under conditions that match those of most laboratory research (restricted sample of students, approximately n = 50). The test is free to use and runs fully under open source software. In order to facilitate the application of the test, we have translated it into 16 common languages (Chinese, Danish, Dutch, English, Finnish, French, German, Italian, Japanese, Norwegian, Polish, Portuguese, Russian, Spanish, Swedish, Turkish). The test can be downloaded at https://osf.io/qy6nb/. We hope that this MOT test supports researchers whose field of study requires capturing individual differences in visual attention reliably.

scholarly journals Examining the roles of working memory and visual attention in multiple object tracking expertise

2020 ◽  
Vol 21 (2) ◽  
pp. 209-222
Author(s):  
David J. Harris ◽  
Mark R. Wilson ◽  
Emily M. Crowe ◽  
Samuel J. Vine
Keyword(s):  
Working Memory ◽  
Visual Attention ◽  
Object Tracking ◽  
Multiple Object Tracking ◽  
Multiple Object

scholarly journals Studying visual attention using the multiple object tracking paradigm: A tutorial review

2017 ◽  
Vol 79 (5) ◽  
pp. 1255-1274 ◽  
Author(s):  
Hauke S. Meyerhoff ◽  
Frank Papenmeier ◽  
Markus Huff
Keyword(s):  
Visual Attention ◽  
Object Tracking ◽  
Multiple Object Tracking ◽  
Multiple Object

scholarly journals Gamma coherence mediates interhemispheric integration during multiple object tracking

2020 ◽  
Vol 123 (5) ◽  
pp. 1630-1644
Author(s):  
Nicholas S. Bland ◽  
Jason B. Mattingley ◽  
Martin V. Sale
Keyword(s):  
Individual Differences ◽  
Object Tracking ◽  
Objective Measure ◽  
Multiple Object Tracking ◽  
Tracking Performance ◽  
Eeg Coherence ◽  
Multiple Object ◽  
Predicting Performance ◽  
Trial Basis ◽  
Gamma Coherence

Using a multiple object tracking paradigm, we were able to manipulate the need for interhemispheric integration on a per-trial basis, while also having an objective measure of integration efficacy (i.e., tracking performance). We show that tracking performance reflects a cost of integration, which correlates with individual differences in interhemispheric EEG coherence. Gamma coherence appears to uniquely benefit between-hemifield tracking, predicting performance both across participants and across trials.

scholarly journals Normal Aging Delays and Compromises Early Multifocal Visual Attention during Object Tracking

2013 ◽  
Vol 25 (2) ◽  
pp. 188-202 ◽  
Author(s):  
Viola S. Störmer ◽  
Shu-Chen Li ◽  
Hauke R. Heekeren ◽  
Ulman Lindenberger
Keyword(s):  
Older Adults ◽  
Visual Attention ◽  
Object Tracking ◽  
Visual Processing ◽  
Normal Aging ◽  
Multiple Object Tracking ◽  
Attentional Modulation ◽  
Younger Adults ◽  
Multiple Object ◽  
Age Related

Declines in selective attention are one of the sources contributing to age-related impairments in a broad range of cognitive functions. Most previous research on mechanisms underlying older adults' selection deficits has studied the deployment of visual attention to static objects and features. Here we investigate neural correlates of age-related differences in spatial attention to multiple objects as they move. We used a multiple object tracking task, in which younger and older adults were asked to keep track of moving target objects that moved randomly in the visual field among irrelevant distractor objects. By recording the brain's electrophysiological responses during the tracking period, we were able to delineate neural processing for targets and distractors at early stages of visual processing (∼100–300 msec). Older adults showed less selective attentional modulation in the early phase of the visual P1 component (100–125 msec) than younger adults, indicating that early selection is compromised in old age. However, with a 25-msec delay relative to younger adults, older adults showed distinct processing of targets (125–150 msec), that is, a delayed yet intact attentional modulation. The magnitude of this delayed attentional modulation was related to tracking performance in older adults. The amplitude of the N1 component (175–210 msec) was smaller in older adults than in younger adults, and the target amplification effect of this component was also smaller in older relative to younger adults. Overall, these results indicate that normal aging affects the efficiency and timing of early visual processing during multiple object tracking.

scholarly journals Visual Attention is Required for Multiple Object Tracking

2013 ◽  
Vol 13 (9) ◽  
pp. 1282-1282
Author(s):  
A. Tran ◽  
J. Hoffman
Keyword(s):  
Visual Attention ◽  
Object Tracking ◽  
Multiple Object Tracking ◽  
Multiple Object
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