A highlight from The brain cells that help animals navigate in 3D

Nature Podcast
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Getting from a to be is a complex process knowing where you are and figuring out where you're going requires many different types of brain so much of what we know about navigation and a neurological level has come from studies in rats watching which neurons lights up as an animal moves about space but there was a drawback to this as many of these studies have been done into d. Looking at a rat scurrying over a flat surface but as we know the world is a three d place and has its ups and downs. Of course different. Animals have different degrees of three-dimensionality in their movements. Are animals that fly or swim like bats or fish. Dolphins whale et cetera. And they really move strictly in three dimensional space. This is not enough ski from the weizman institute of science in israel this week in nature. He and his colleagues have paper out looking at how one particular group of neurons fire in three d. space to help an animal workout where it is specifically neck has been looking at grid cells which are pretty well understood in the two d. world grid cells are neurons which are activated whenever the animal. Rats usually traverse one of multiple locations in the room. And you could be activated in one location or a second location. Third location or fork location. And if you look at how are these locations arranging space. It turns out that the form hexagonal lattice much like a honeycomb so specific grid cells fire in multiple specific places in space forming this regular repeating hexagonal pattern. All that is which is thought to help an animal judge distances and know where it is. But what happens when you go from two d to three d. What would the pattern of grid cell. Firing look like would it be lots of hexagonal layers one on top of the other making an overall three d. hexagonal structure. Well this has been a long standing question in neuroscience and knock on wanted to find out and in fact the were theoretical predictions of what one might expect to get and this situation because this hexagonal lattice on a two dimensional surface. It's the best packing of circles on a plane. What we're after is to see whether these beautiful geometry exists also in three dimensional space and to answer this question we took sort of the most extreme three dimensional navigator among mammals. Which is the bat now has been using bats egyptian fruit bats specifically in his research for some time now and in this work encourage them to fly around a large room as he recorded wherein when the grid cells fired what we've done is we've placed between six and eleven little fears on which they can land and get a little bit of bananas and there were different heights all around the perimeter of the room but this one cartoon to fly through three dimensional space and we recorded the neural activity by using this wireless electrophysiology system that we've developed this neuro logger that allows to record neurons from the brain and store the data onboard the animals so by logging wearing three d space the bat screwed cells fight knock home and his colleagues could look to see what sort of pattern the activity took in the room. Did they find the hexagonal lattice pattern. So well defined into the short answer that we didn't find it didn't find even a single neuron that significantly and convincingly showed a hexagonal lattice so they didn't find the pattern that had been theorized. It's what we expected to get and will look for more than two years and you know. This research took many years in part because it took a several years to realize that we are sort of looking and look at look out not finding this. Okay now we need to re compute our very so to speak and rethink relic you for but after a lot of head-scratching in some complex mathematical modeling. That seem found that while there may not be this regular repeating pattern. That was expected to the good cells. Wasn't random either. What we looked at is a local distances between nearby fine field nearby greenfield's so each one of them can ask who are the three years neighboring spheres. I can look at those three distances. And then look at the next field those we nearest distance distances and we found that many of those sales there was a fixed distance or characteristic local distance between nearby fields instead of being a very ordered overall states with a perfect hexagonal lettuce. The team found a semi ordered organization. There were pockets of local order. Where the location. That neurons fired was close to others and these locations were always separated by a fixed distance. But of course this begs the question. Why is there one pattern for grid cells firing in two d. but another in three d. Well knock him suggests that they're actually part of the same system and it's the fixed distances between where the grid cells fire. That's the key what our results argue is that the exile structure is the secondary property. But what's more fundamental is. Actually the nearby fields have fixed distances from each other. And if you have that then in two dimensions you automatically get a second a lot in three dimensions. You'd get this order thing so it's sort of it puts the emphasis so to speak not on exceptional in into dimensions but on the fixed distances into dimensions so after a long time wondering it seems that is now. Have a better insight into how grit cells fire in three d. space but of course this is just one animal. The bat and one particular experimental setup another paper out today in nature neuroscience looked at rats able to climb in a three d. environment and showed a different pattern of activity although also not hexagonal pattern. So there's still lots to learn about how all this works. Regardless malcolm says that his finding might mean researchers will have to have a bit of a rethink when it comes to working out the mechanisms of how navigation works a lot of weight has been placed on a hexagonal system for good selectivity. That may differ from what's really happening so it will require quite some work to produce a model that on the one hand is consistent with the perfect beautiful exciting allowed. This is in two the but on the other hand can produce this semi organized or locally organized fields in three d. so this is a major challenge for the field and challenges

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