Foraging Tempo: Human run patterns in multiple target search are constrained by the rate of successive responses.

Abstract

Human foraging tasks are beginning to provide new insights into the roles of vision, attention and working memory during complex search, particularly with respect to individual differences. Here, we test the idea that “foraging tempo” -- the rate of successive target selections -- helps determine patterns of behaviour in these tasks. Previously, we established that the majority of target selections during unconstrained foraging happen at regular, rapid intervals, forming the “cruise phase” of a foraging trial. Furthermore, we noted that when the temporal interval between cruise phase responses was longer, the tendency to switch between target categories increased. To directly explore this relationship, we modified our standard iPad foraging task so that observers had to synchronize each response with an auditory metronome signal. Across trials, we increased the tempo and examined how this changed patterns of foraging when targets were defined either by a single feature or by a conjunction of features. The results were very clear. Increasing tempo systematically decreased the tendency for participants to switch between target categories. While this was true for both feature and conjunction trials, there was also evidence that time constraints and target complexity interacted. As in our previous work, we also observed clear individual differences in how participants responded to changes in task difficulty. Overall, our results show that foraging tempo does influence the way participants respond, and we suggest this parameter may prove be useful in further explorations of group and individual strategies during multiple target search.

The Predation Game: Does dividing attention affect patterns of human foraging?

“…The basic group size ( N = 12) was determined prior to data collection and was chosen to directly match recent studies from our group where within-subject differences in run behaviour had been successfully measured (Thornton et al, 2019 , 2020 ). To further verify that this sample size would provide sufficient power to detect the within-group feature/conjunction foraging patterns of interest, we conducted an a priori power analysis using the “Bias and Uncertainty Corrected Sample Size” (BUCSS) toolbox described by Anderson et al ( 2017 ).…”

“…BUCSS uses the reported F values and sample size from previous factorial studies—rather than derived estimates of effect size—to generate necessary sample sizes for planned studies. Here, we chose the previous study from our group (Thornton et al, 2020 ) that most closely matched the current within-group factorial design. Specifically, we chose a 2 (Target: feature/conjunction) × 5 (Foraging Tempo) repeated measures analysis of variance conducted on run length with a sample size of 11, focusing our a priori analysis on the main effect of Target, F (1,10) = 40.0, p < 0.001, MSE = 6.3, = 0.8.…”

“…Specifically, we chose a 2 (Target: feature/conjunction) × 5 (Foraging Tempo) repeated measures analysis of variance conducted on run length with a sample size of 11, focusing our a priori analysis on the main effect of Target, F (1,10) = 40.0, p < 0.001, MSE = 6.3, = 0.8. We used this F value, along with the sample size and alpha parameters from Thornton et al ( 2020 ) as input to the BUCSS ss.power.wa function. We chose custom settings of assumed alpha for the planned study = 0.05, level of assurance = 0.95, and desired power of 0.8.…”

“…Traditional visual search—involving a single target and a variable set-size of distractors—has taught us much about the cognitive processes we use to successfully locate items of interest in the world around us (Treisman & Gelade, 1980 ; Wolfe & Horowitz, 2017 ). Extending the classic single-target paradigm, a number of groups have also examined search behaviour in tasks where multiple targets must be located on a given trial (see Kristjánsson et al, 2019 ; Thornton et al, 2020 for recent discussion). Much of this work stems from the observation that real-life activities—such as finding the correct change, shopping in a store, assembling a new piece of furniture—often involve a series of identification and selection events.…”

“…As noted above, these studies form part of a more general research trend exploring multiple-target visual search in humans. To-date, selection difficulty (Kristjánsson et al, 2014 ), selection modality (Jóhannesson et al, 2016 ; Tagu & Kristjánsson, 2020 ; Thornton et al, 2019 ), patch-leaving (Wolfe, 2013 ), time constraints (Kristjánsson et al, 2018 ; Thornton et al, 2020 ) and reward (Wolfe et al, 2018 ) have all been used to directly modulate multiple-target search behaviour in humans.…”