A new study used eye-tracking technology to show that kids’ attention wandered all over a computer screen while they were trying to complete a task — even when adults quickly figured out they could do the task more efficiently by focusing on particular objects.

But that tendency to have a wandering eye helped 4- and 5-year-olds when the task unexpectedly changed — and they noticed important things on the screen that adults were not paying attention to.

“The ability of adults to focus their attention is usually very helpful in everyday life,” said Vladimir Sloutsky, co-author of the study and professor of psychology at The Ohio State University.

“But sometimes it helps to see the world more as a kid and to notice things that may not seem that important or relevant at the time.”

Sloutsky conducted the research with Nathaniel Blanco, a postdoctoral researcher, and Brandon Turner, professor, both in psychology at Ohio State. The study was published online recently in the Journal of Experimental Child Psychology.

The study involved 30 4- and 5-year-old children and 38 adults who participated in a lab, where they were fitted with eye trackers that could tell where they looked on a computer screen.

They were then shown colorful images of creatures that had seven identifiable features, including a head, tail and antennae.

Participants were told there were two types of creatures, called Flurps and Jalets, and that they had to figure out which ones were which.

One feature was always different on the two types of creatures — for example, the Jalets may have a blue tail and the Flurps an orange tail. In addition, the children and adults were told that most (but not all) of the Flurps had a certain type of feature, such as pink antennae.

One of the features was never mentioned in the instructions and it did not differ between the types of creatures. This was what the researchers called the “irrelevant feature.”

After training, participants were shown a series of images of the creatures on the computer screen and were told to indicate which type of creature each one was.

During the first part of the experiment, adults quickly learned which feature always determined whether the creature was a Flurp or Jalet, and the eye-tracker showed that they then concentrated nearly all of their attention on that feature.

Children were slower to learn which feature was most important in determining which creature was which — and the eye-tracker showed they continued to look at all the features of the two creatures, even the ones that were not relevant.

“The kids were not as efficient as adults at learning quickly,” Sloutsky said. “They kept looking around even when they didn’t need to.”

But halfway through the experiment, the researchers made an unannounced switch: The irrelevant feature — the body part that previously had no bearing on what type of creature it was — became the feature that would determine whether it was a Flurp or a Jalet. This feature, which had been the same for both creatures before the switch, was now different for each.

After the switch, the adults were more oblivious to the importance of the new feature than the children were. Instead, they were relying on the previously learned less-important features.

Children, on the other hand, had been paying attention to everything, so they noticed more swiftly that the rules had changed.

“The adults were suffering from learned inattention,” Sloutsky said. “They weren’t paying attention to features that weren’t important during the first part of the experiment, so they missed when those features did become important.”

Sloutsky said the brains of 4- and 5-year-olds aren’t mature enough to focus attention in the way adults do. That fact may help them learn more as they explore the world.

And adults certainly have the ability to distribute their attention broadly like the children did in this study — but they often choose selective attention because it is helpful in achieving efficiency, he said.

The lesson for adults, though, is to realize that selective attention, while increasing the efficiency of learning and performance, can also lead to a learning trap in some situations, Sloutsky said.

“When you know something really well or a solution to a problem seems obvious, it may help to broaden your attention, to look for clues that may not seem relevant at first — to think like a kid again.”

The study was supported by grants from the National Institutes of Health.

The high cost of powering an underwater camera for a long time, by tethering it to a research vessel or sending a ship to recharge its batteries, is a steep challenge preventing widespread undersea exploration.

MIT researchers have taken a major step to overcome this problem by developing a battery-free, wireless underwater camera that is about 100,000 times more energy-efficient than other undersea cameras. The device takes color photos, even in dark underwater environments, and transmits image data wirelessly through the water.

The autonomous camera is powered by sound. It converts mechanical energy from sound waves traveling through water into electrical energy that powers its imaging and communications equipment. After capturing and encoding image data, the camera also uses sound waves to transmit data to a receiver that reconstructs the image.

Because it doesn’t need a power source, the camera could run for weeks on end before retrieval, enabling scientists to search remote parts of the ocean for new species. It could also be used to capture images of ocean pollution or monitor the health and growth of fish raised in aquaculture farms.

“One of the most exciting applications of this camera for me personally is in the context of climate monitoring. We are building climate models, but we are missing data from over 95 percent of the ocean. This technology could help us build more accurate climate models and better understand how climate change impacts the underwater world,” says Fadel Adib, associate professor in the Department of Electrical Engineering and Computer Science and director of the Signal Kinetics group in the MIT Media Lab, and senior author of the paper.

Joining Adib on the paper are co-lead authors and Signal Kinetics group research assistants Sayed Saad Afzal, Waleed Akbar, and Osvy Rodriguez, as well as research scientist Unsoo Ha, and former group researchers Mario Doumet and Reza Ghaffarivardavagh. The paper is published in Nature Communications.

Going battery-free

To build a camera that could operate autonomously for long periods, the researchers needed a device that could harvest energy underwater on its own while consuming very little power.

The camera acquires energy using transducers made from piezoelectric materials that are placed around its exterior. Piezoelectric materials produce an electric signal when a mechanical force is applied to them. When a sound wave traveling through the water hits the transducers, they vibrate and convert that mechanical energy into electrical energy.

Those sound waves could come from any source, like a passing ship or marine life. The camera stores harvested energy until it has built up enough to power the electronics that take photos and communicate data.

To keep power consumption as a low as possible, the researchers used off-the-shelf, ultra-low-power imaging sensors. But these sensors only capture grayscale images. And since most underwater environments lack a light source, they needed to develop a low-power flash, too.

“We were trying to minimize the hardware as much as possible, and that creates new constraints on how to build the system, send information, and perform image reconstruction. It took a fair amount of creativity to figure out how to do this,” Adib says.

They solved both problems simultaneously using red, green, and blue LEDs. When the camera captures an image, it shines a red LED and then uses image sensors to take the photo. It repeats the same process with green and blue LEDs.

Even though the image looks black and white, the red, green, and blue colored light is reflected in the white part of each photo, Akbar explains. When the image data are combined in post-processing, the color image can be reconstructed.

“When we were kids in art class, we were taught that we could make all colors using three basic colors. The same rules follow for color images we see on our computers. We just need red, green, and blue — these three channels — to construct color images,” he says.

Sending data with sound

Once image data are captured, they are encoded as bits (1s and 0s) and sent to a receiver one bit at a time using a process called underwater backscatter. The receiver transmits sound waves through the water to the camera, which acts as a mirror to reflect those waves. The camera either reflects a wave back to the receiver or changes its mirror to an absorber so that it does not reflect back.

A hydrophone next to the transmitter senses if a signal is reflected back from the camera. If it receives a signal, that is a bit-1, and if there is no signal, that is a bit-0. The system uses this binary information to reconstruct and post-process the image.

“This whole process, since it just requires a single switch to convert the device from a nonreflective state to a reflective state, consumes five orders of magnitude less power than typical underwater communications systems,” Afzal says.

The researchers tested the camera in several underwater environments. In one, they captured color images of plastic bottles floating in a New Hampshire pond. They were also able to take such high-quality photos of an African starfish that tiny tubercles along its arms were clearly visible. The device was also effective at repeatedly imaging the underwater plant Aponogeton ulvaceus in a dark environment over the course of a week to monitor its growth.

Now that they have demonstrated a working prototype, the researchers plan to enhance the device so it is practical for deployment in real-world settings. They want to increase the camera’s memory so it could capture photos in real-time, stream images, or even shoot underwater video.

They also want to extend the camera’s range. They successfully transmitted data 40 meters from the receiver, but pushing that range wider would enable the camera to be used in more underwater settings.

This research is supported, in part, by the Office of Naval Research, the Sloan Research Fellowship, the National Science Foundation, the MIT Media Lab, and the Doherty Chair in Ocean Utilization.