Israeli scientists have discovered a previously unknown cognitive mechanism that allows bats to move through expansive environments, furthering our understanding of how mammalian memory supports navigation, according to a groundbreaking study published Thursday. 

The study in Science is part of a larger research project involving bat models that focuses on the neural bases for social cognition and spatial navigation in mammals, Nachum Ulanovsky, a professor in the department of neurobiology at the Weizmann Institute of Science, in Israel, and the study's corresponding author, told The Academic Times. 

"You can use bats to answer questions that are difficult to answer otherwise," he said. "For example, in this particular study, where we asked, 'How are large spaces represented by the brain?' we used the fact that bats can cover very large distances very fast. They fly back and forth, and we get many repetitions over a very large space — something that wouldn't be possible with a rat or a mouse." 

Over the years, Ulanovsky's lab has explored cognitive representations of three-dimensional space and goal-based navigation, among other subjects, concentrating primarily on activity in the hippocampus, a region of the brain known to be closely connected to spatial memory. Within the hippocampus are neurons called place cells, which are activated when an animal is in a unique position in space, known as a place field. When the animal is in another position, a different neuron is activated. 

The discovery that monitoring the activity of place cells allows researchers to decode an animal's location in space was groundbreaking in neuroscience, ultimately earning part of the Nobel Prize in 2014. But studies of place cells are generally conducted in small environments, such as rat mazes, Ulanovsky said, leaving open the question of whether the same cognitive process is at play in larger, more naturalistic settings. 

"If an animal is flying outdoors for kilometers, then they'll need a huge number of neurons to cover the space," he said. "It comes out orders of magnitude out of scale; it'd be like a billion times more neurons than are in the entire brain. It's just not going to work, so there must be something else." 

The researchers conducted a large-scale, lab-based experiment involving a 200-meter-long tunnel, which the bats flew through while wearing tiny sensors that measured their brain activity. The animals' positions were measured with an array of localization antennas that provided more precise readings than the Global Positioning System. What the researchers found diverged from the classical understanding of one place cell being activated for each position in the animals' environment; rather, individual neurons were active in multiple locations. 

"Even more surprisingly, the place fields could have a very different size, so maybe neurons could have a place field a meter here and 20 meters there," he said. "That means there's a different resolution in different locations. That's a very unusual type of neural code that we found. Nothing like that, that we know of, has been found in any brain region of any animal. It's a totally new thing in the brain, as far as we know."

Computational analysis showed that this multiscale representation of large environments had "major advantages'' over the classical place code, including fewer decoding errors, according to the study's authors. In other words, the cognitive system discovered by Ulanovsky and his colleagues is more accurate than the system for smaller spaces — in some cases 100 times more accurate, he said. 

Further, this cognitive basis for navigating large spaces was observed in both wild-caught bats and lab-raised bats that had never been exposed to environments larger than their cage before being released in the tunnel — suggesting that the system isn't learned. 

"From day one, you see this multiscale code in lab-born bats that grew up in a room a few meters in size," Ulanovsky said. "So, it seems that this type of code is something very fundamental that does not require prior experience." 

Ulanovsky suspects the findings will also apply to other mammals, though his theory has yet to be tested in rodent or human models. "A prediction for the future is that once rats are tested in a big environment, we'll see similar things in rodents," he said. 

The research may also have implications for robotic navigation systems, which have "taken what we know about small environments and extrapolated it out for autonomous cars," he said. "But if our [cognitive] representation of large spaces actually looks very different, maybe we have to rethink things." 

"This is the real deal for large environments," he continued. "This project demonstrates something that I personally believe in, which is going with the natural behavior of the animal. When we think about the neural basis for navigation, we need to think about how it works in the real world."

In an ongoing project, the researchers in Ulanovsky's lab have turned their attention to other subregions of the hippocampus as they relate to moving through large spaces. The team is also analyzing the brain circuitry of multiple bats navigating the tunnel at the same time. 

The study, "Multiscale representation of very large environments in the hippocampus of flying bats," published May 27 in Science, was authored by Tamir Eliav, Shir R. Maimon, Gily Ginosar, Liora Las and Nachum Ulanovsky, Weizmann Institute of Science; Jonathan Aljadeff, Weizmann Institute of Science and University of California, San Diego; and Misha Tsodyks, Weizmann Institute of Science and the Institute for Advanced Study.