These Trippy Images Were Designed By AI For Over stimulating Monkey Neurons

"When this tool was provided, the cells began to increase their firing rate beyond the levels we have seen before, even with preset normal images to obtain the highest firing rates," explains co-first author Carlos Ponce. , then a postdoctoral fellow in the lab of lead author Margaret Livingstone at Harvard Medical School and now a faculty member at the University of Washington in St. Louis.

"What began to emerge during each experiment were images that remembered shapes in the world but were not real objects in the world," he says. "We were seeing something that was more like the language that cells use among themselves."

Researchers have known that neurons in the visual cortex of primate brains respond to complex images, such as faces, and that most neurons are quite selective in their image preference. Previous studies on neuronal preference used many natural images to see what images caused the neurons to fire more. However, this approach is limited by the fact that not all possible images can be presented to understand what exactly stimulates the cell best.

The XDREAM algorithm uses the firing speed of a neuron to guide the evolution of a novel synthetic image. It goes through a series of images over the course of minutes, mutates them, combines them and then shows a new series of images. At first, the images looked like noises, but gradually they became shapes that resembled faces or something recognizable in the animal's surroundings, such as the food hopper in the room of animals or familiar people wearing surgical gowns. The algorithm was developed by Will Xiao in Gabriel Kreiman's lab at Children's Hospital and tested on real neurons at Harvard Medical School.

"The great advantage of this approach is that it allows the neuron to build its own favorite images from scratch, using a tool that is not limited by much, that can create anything in the world or even things that do not exist in the world. , "says Ponce.

"In this way, we have developed a super stimulus that drives the cell better than any natural stimulus we can guess," says Livingstone. "This approach allows you to use artificial intelligence to discover what triggers neurons the most, it's a totally impartial way of asking the cell what it really wants, what would trigger it the most."

By: Preeti Narula

Content: https://www.sciencedaily.com/releases/2019/05/190502161207.htm