An eye prosthesis sends the brain not a photograph but a sparse pattern of bright dots — phosphenes. To make out a cup or keys in this flickering noise, a person has to move their head like a flashlight in the dark, piecing together the object's outline bit by bit. It's a slow process, like assembling a puzzle where most pieces have been thrown away.

A team of researchers tried to nudge the brain when it was truly focused on the search. Twenty-two participants donned a virtual reality headset with dry electrodes that picked up the brain's electrical activity (EEG). In front of them appeared a virtual table drawn with a sparse scattering of glowing dots. The task: find a given object as quickly as possible. After each attempt, a colored marker appeared on the screen: a green light if a special engagement index, the ratio of fast beta waves to the sum of slow alpha and theta, was high, and red if it was low. A second group saw the same markers but random, unrelated to brain activity.

Everyone improved: by the end of the session, participants found objects faster and more accurately. But the "smart" hint gave no advantage — neither in speed, nor errors, nor perceived workload. The brain learned on its own, simply getting used to the phosphene mosaic and developing its own scanning strategies. The variation between participants was huge: in some, engagement grew in sync with success; in others, it didn't.

The authors aren't giving up on the idea of a neuroadaptive assistant. They showed that EEG and prosthetic vision can be combined in a single wearable system. But one training session and a crude engagement index aren't enough. Perhaps a future assistant will need to tune a personal rhythm for each user, like tuning a musical instrument before a concert.