Edited by: Allison B. Sekuler, McMaster University, Canada
Reviewed by: Natasha Sigala, University of Sussex, UK; Karla K. Evans, Harvard Medical School, USA; Patrick J. Bennett, McMaster University, Canada
This article was submitted to Frontiers in Perception Science, a specialty of Frontiers in Psychology.
This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in other forums, provided the original authors and source are credited and subject to any copyright notices concerning any third-party graphics etc.
The capacity to process complex dynamic scenes is of critical importance in real life. For instance, traveling through a crowd while avoiding collisions and maintaining orientation and good motor control requires fluent and continuous perceptual-cognitive processing. It is well documented that effects of healthy aging can influence perceptual-cognitive processes (Faubert,
In our daily activities, we constantly interact with our environment. This environment is dynamic and requires the integration of various objects, motions, speeds, locations etc. There is ample evidence that the healthy aging process affects visual perceptual processing. Age-related deficits are particularly noticeable when the cognitive processes involved in the integration of information are more complex and require simultaneous assimilation of many aspects of the environment (Faubert,
A perceptual-cognitive task of particular relevance for exploring multifocal attention and complex motion information is multiple object tracking (MOT). MOT is a task where the observer is required to simultaneously track multiple moving items among many. The ability of the observer is typically evaluated by the number of elements that can be tracked successfully (Pylyshyn,
Regardless of the models to explain how people track multiple objects, older observers are less efficient at tracking multiple objects (Trick et al.,
A number of questions remain, however, in regards to the perceptual-cognitive abilities of older observers. Some obvious questions are whether older observers’ capacity and learning rate differ from that of younger adults. Previous studies on divided attention with the useful field of view (UFOV) have shown that older adults could benefit from training (Ball et al.,
The purpose of the present study was therefore to address these questions directly with two experiments. The goal of the first experiment was to determine if older observers have lower limits in their capacity to track multiple moving objects when compared to young adults (Trick et al.,
In a MOT-type task where the dependent measure used was the maximum number of elements that could be tracked, Trick et al. (
Ten younger adults (mean age 27 years old, range: 22–34 years old) and 10 older adults (mean age 66 years old, range: 61–74 years old) participated in this study. All participants were naïve to the purpose of the experiment. All subjects had normal or corrected-to-normal vision (6/6 or better) with normal stereoacuity as measured by the Frisby test (40 s of arc or better) (Sasieni,
The 3D-MOT task was assessed using a fully immersive virtual environment: the Cave Automatic Virtual Environment (CAVE) system. The CAVE was an 8 × 8 × 8 feet room that includes three canvas walls (one frontal and two laterals) and an epoxy floor that all serve as surfaces for image projection (Faubert and Allard,
Before testing, participants were familiarized with the virtual environment and the stimulus. They were then asked to wear the stereoscopic goggles, which allowed them to perceive the 3D characteristics of the environment. Each participant sat at 177 cm from the central wall of the CAVE with eye height set at 160 cm from the ground. They were asked to stare at the fixation point, located straight ahead. Stimuli consisted of nine spheres projected into a virtual cube having transparent virtual light blue walls. The anterior side of the cube measured 42 ° of visual angle and was seen at 57 cm. The spheres followed a linear trajectory in the 3D virtual space but were bouncing on one another and on the walls when collisions occurred (see Figure
We used the 3D-MOT speed threshold protocol (Faubert and Sidebottom,
From the 10 older participants, only nine were included in the analysis. One could not perform the task even for three targets at very low speeds (e.g., 1 cm/s). This participant was considered as an outlier since he was the only one from 30 (including 20 in Experiment 2) that could not complete the task. A 2 × 2 split-plot ANOVA on log speed thresholds revealed a significant Age (between variable) × Number of targets (3 or 4, within variable) interaction,
Results show that older adults can successfully follow three and four targets, but at significantly lower speeds (Figure
In the second experiment we trained younger and older adults during five consecutive weeks on the 3D-MOT task to determine the performance progress for younger and older adults. Here we wanted to determine which of the three possible outcomes prevails for 3D-MOT: either (1) they have a slower learning rate than younger adults; (2) they still have equivalent learning functions; or (3) training can reverse some age-related impairment, in which case training should reduce the performance difference between both age groups.
Two new experimental groups participated in this experiment. One group was composed of 20 young observers (mean age 24 years old, range: 18–35 years old) and another consisted of 20 older observers (mean age 67 years old, range: 64–73 years old). All observers came to the lab once a week for five consecutive weeks. The same inclusion and exclusion criteria were used as for Experiment 1. Again, the older observers’ scores on the Mini-Mental State Examination were all within the normal range (range, 28–30/30; subject mean was 29/30) (Crum et al., Name of the game Electronic game device Number of hours per session Number of sessions per month
The same set-up, stimuli and procedure as in Experiment 1 were used. We used the three-target protocol and for every session, participants ran three blocks (three thresholds) for a total of a 30-min session per week.
A split-plot ANOVA on log speed thresholds comparing post-training condition (week 5) versus the initial scores (week 1) revealed a significant group effect,
Figure
In this paper, we assessed 3D-MOT for younger and older adults. In both experiments, we reported a significant age-related deficit, in which older adults obtained lower performance scores compared to younger adults. These results are generally consistent with previous MOT research showing reduced performance for older adults (Trick et al.,
In Experiment 2, results show that both younger and older adults obtained similar training gains from 3D-MOT. Their performance after 5 weeks of training was significantly improved; participants processed the 3D-MOT task successfully at faster speeds. Overall, younger adults show better performance than older adults but the lack of significant interaction shows similar training gains between groups. Figure
As expected, our results show that younger adults obtained better performance than older adults. An element that can contribute to higher performance in younger adults is their previous exposure to certain stimuli as found in video games (Sekuler et al.,
In the present study, our 3D-MOT task was conducted in a virtual reality environment soliciting information integration across a large visual field. Consistent with previous research using UFOV (Richards et al.,
Our findings can be summed into two main points. We show that perceptual-cognitive training for a complex dynamic multifocal attention motion task, such as 3D-MOT, can be trained and, more importantly, that the training benefit for older observers is of the same magnitude as that for younger healthy adults. Consequently, it would certainly be worthwhile to conduct future studies on the transferability of this training to real-life tasks, such as driving or other socially relevant tasks.
Isabelle Legault and Rémy Allard declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Jocelyn Faubert is the Chief Science Officer of CogniSens Inc., a company that has signed a licensing agreement for four technologies from the Université de Montréal and produces the NeuroTracker ™system, the commercial version of the 3D-MOT speed task.
This work was supported by NSERC and the NSERC-Essilor Industrial Research Chair.