Online experimentation is emerging in many areas of cognitive psychology as a viable alternative or supplement to classical in-lab experimentation. While performance- and reaction-time-based paradigms are covered in recent studies, one instrument of cognitive psychology has not received much attention up to now: eye tracking. In this study, we used JavaScript-based eye tracking algorithms recently made available by Papoutsaki et al. (International Joint Conference on Artificial Intelligence, 2016) together with consumer-grade webcams to investigate the potential of online eye tracking to benefit from the common advantages of online data conduction. We compared three in-lab conducted tasks (fixation, pursuit, and free viewing) with online-acquired data to analyze the spatial precision in the first two, and replicability of well-known gazing patterns in the third task. Our results indicate that in-lab data exhibit an offset of about 172 px (15% of screen size, 3.94° visual angle) in the fixation task, while online data is slightly less accurate (18% of screen size, 207 px), and shows higher variance. The same results were found for the pursuit task with a constant offset during the stimulus movement (211 px in-lab, 216 px online). In the free-viewing task, we were able to replicate the high attention attribution to eyes (28.25%) compared to other key regions like the nose (9.71%) and mouth (4.00%). Overall, we found web technology-based eye tracking to be suitable for all three tasks and are confident that the required hard- and software will be improved continuously for even more sophisticated experimental paradigms in all of cognitive psychology.
Using the Internet to acquire behavioral data is currently on the rise. However, very basic questions regarding the feasibility of online psychophysics are still open. Here, we aimed to replicate five well-known paradigms in experimental psychology (Stroop, Flanker, visual search, masked priming, attentional blink) in three settings (classical Blab^, Bweb-inlab^, Bweb^) to account for possible changes in technology and environment. Lab and web-in-lab data were both acquired in an in-lab setting with lab using BGold Standard^methods, while web-in-lab used web technology. This allowed for a direct comparison of potential differences in acquisition software. To account for additional environmental differences, the web technology experiments were published online to participate from home (setting web), thereby keeping the software and experimental design identical and only changing the environmental setting. Our main results are: First, we found an expected fixed additive timing offset when using web technology (M = 37 ms, SD = 8.14) and recording online (M = 87 ms, SD = 16.04) in comparison to lab data. Second, all taskspecific effects were reproduced except for the priming paradigm, which couldn't be replicated in any setting. Third, there were no differences in error rates, which are independent of the timing offset. This finding further supports the assumption of data equality over all settings. Fourth, we found that browser type might be influencing absolute reaction times. Together, these results contribute to the slowly but steadily growing literature that online psychophysics is a suitable complement -or even substitute -to lab data acquisition.
New technological devices, particularly those with touch screens, have become virtually omnipresent over the last decade. Practically from birth, children are now surrounded by smart phones and tablets. Despite being our constant companions, little is known about whether these tools can be used not only for entertainment, but also to collect reliable scientific data. Tablets may prove particularly useful for collecting behavioral data from those children (1–10 years), who are, for the most part, too old for studies based on looking times and too young for classical psychophysical testing. Here, we analyzed data from six studies that utilized touch screen tablets to deliver experimental paradigms in developmental psychology. In studies 1 and 2, we employed a simple sorting and recall task with children from the ages of 2–8. Study 3 (ages 9 and 10) extended these tasks by increasing the difficulty of the stimuli and adding a staircase-based perception task. A visual search paradigm was used in study 4 (ages 2–5), while 1- to 3-year-olds were presented with an extinction learning task in study 5. In study 6, we used a simple visuo-spatial paradigm to obtain more details about the distribution of reaction times on touch screens over all ages. We collected data from adult participants in each study as well, for comparison purposes. We analyzed these data sets in regard to four metrics: self-reported tablet usage, completeness of data, accuracy of responses and response times. In sum, we found that children from the age of two onwards are very capable of interacting with tablets, are able to understand the respective tasks and are able to use tablets to register their answers accordingly. Results from all studies reiterated the advantages of data collection through tablets: ease of use, high portability, low-cost, and high levels of engagement for children. We illustrate the great potential of conducting psychological studies in young children using tablets, and also discuss both methodological challenges and their potential solutions.
Online experimentation is emerging as a new methodology within classical data acquisition in psychology. It allows for easy, fast, broad, and cheap data conduction from the comfort of people’s homes. To add another method to the array of available tools, here we used recent developments in web technology to investigate the technical feasibility of online HyperText Markup Language-5/JavaScript-based video data recording. We employed a preferential looking task with children between 4 and 24 months. Parents and their children participated from home through a three-stage process: First, interested adults registered and took pictures through a webcam-based photo application. In the second step, we edited the pictures and integrated them into the design. Lastly, participants returned to the website and the video data acquisition took place through their webcam. In sum, we were able to create and employ the video recording application with participants as young as 4 months old. Quality-wise, no participant had to be removed due to the framerate or quality of videos and only 7% of data was excluded due to behavioral factors (lack of concentration). Results-wise, interrater reliability of rated looking side (left/right) showed a high agreement between raters, Fleiss’ Kappa, κ = 0.97, which can be translated to sufficient data quality for further analyses. With regard to on-/off-screen attention attribution, we found that children lost interest after about 10 s after trial onset using a static image presentation or 60 s total experimental time. Taken together, we were able to show that online video data recording is possible and viable for developmental psychology and beyond.
Face recognition undergoes prolonged development from childhood to adulthood, thereby raising the question which neural underpinnings are driving this development. Here, we address the development of the neural foundation of the ability to recognize a face across naturally varying images. Fourteen children (ages, 7-10) and 14 adults (ages, 20-23) watched images of either the same or different faces in a functional magnetic resonance imaging adaptation paradigm. The same face was either presented in exact image repetitions or in varying images. Additionally, a subset of participants completed a behavioral task, in which they decided if the face in consecutively presented images belonged to the same person. Results revealed age-related increases in neural sensitivity to face identity in the fusiform face area. Importantly, ventral temporal face-selective regions exhibited more image-invariance - as indicated by stronger adaptation for different images of the same person - in adults compared to children. Crucially, the amount of adaptation to face identity across varying images was correlated with the ability to recognize individual faces in different images. These results suggest that the increase of image-invariance in face-selective regions might be related to the development of face recognition skills.
We investigated the ability to detect a face among other visual objects in a complex visual array in 3-, 4-, and 5-year-old children, as well as in adults. To this end, we used a visual search paradigm implemented on a touch-tablet device. Subjects ( N = 100) saw up to eighty 3 × 3 visual search arrays and had to find and tap upon a target—a face or a car—among eight objects that served as distractors. Our data revealed a relative face detection advantage, which did not differ in its extent between children and adults. This suggests that, beginning in young childhood and ending in adulthood, face detection performance advances as a consequence of other cognitive functions such as a general advance in visual search performance. Our study closes a gap in the knowledge about the development of face detection—as a prototype for social stimuli and their capacity to attract attention—from early to middle childhood.
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