Honeycomb maze reveals hippocampal role in navigation decisions

Researchers at the Sainsbury Wellcome Center at the University College London have discovered that the hippocampus creates vector-based representations to help animals make optimal navigation decisions.

Released today NatureResearchers report results that will greatly help Kaiba solve the problem Place cells Contribute flexibly navigation.. They are navigating to the goal, cell It represents an established representation of the animal’s current position, as well as information about the direction and distance to the goal. They used the honeycomb maze, an action device, to reveal this goal-oriented information. This divides the navigation to the goal into a series of binary selections.

The maze consists of 61 individually elevable platforms. On individual platforms, rats are given the choice of two adjacent platforms to move towards the goal, and to succeed, they must choose the one closest to the direction of the goal. The animal continues these iterative choices until the goal is achieved. Therefore, this task allows you to systematically analyze the navigational decisions that an animal makes regarding its progress to a goal. At each selection point, the place cell reports the direction and distance to the goal, as well as the animal’s current position.

“The Honeycomb Maze is very different from other behavioral tasks in neuroscience because it can be used to present animals with a set of platform choices for navigating towards a goal, which makes it repetitive during navigation. You can see the decisions you make, “Dr. JakeOrmond, Senior Researcher at O’Keefe Lab, Lead Author of Treatises.

Dr. Ormond and Professor John O’Keefe recorded from place cells while the rat participated in the Honeycomb Maze task. This is a class of neurons first discovered by Professor O’Keefe and collectively forms an internal representation of space. From these records, we were able to see how spatial representation is related to spatial effects in place cell activity.

The activity of subgroups of individual place cells was directed to unmarked locations called ConSinks, scattered around the maze and surrounding space, but concentrated near the goal. Create a vector field. At the place cell population level, the overall vector field points to the target position from every point on the maze and provides a signal that the animal can follow to reach the target.

“Looking at the firing rates of all cells, we found that the population fired most strongly when the animal was facing a target. Also, individual place cells have a preferred location named ConSinks. It turns out that these ConSinks were scattered all over. The environment, but overall, was the most crowded around the goal, “Dr. Ormond commented.

However, in addition, firing also provides information about other directions, ranking in terms of how good each is to reach the target when not directly approached. For example, going 45 degrees away from the target direction ranks better than 90 degrees away from the target direction. The presence of this signal answers the question of how animals can find their way to a target when the direct route is blocked.

If these population vector signals are useful for navigating to the target, they need to be changed in an appropriate way when the location of the target changes. And this is exactly what the experimenter found. After retraining the animals to find new goals, the vector field and ConSinks shifted towards the new goals and continued to approach them with more experience.

Equally important, when this hippocampal representation is used for navigation, there should be a good correlation between the ability of the animal to perform the task and the hippocampal representation in the target direction. In an error trial, Ormond and O’Keefe found that the hippocampal signal was not aimed at the goal, but in a different direction.

This study suggests that hippocampal place cells form vector-based representations to support navigation decisions. A vector is defined as having both direction and length, and a vector field provides a vector at each location in the environment. Importantly, the vector field points to the target only at the cell population level. The hippocampus plays a role in supporting navigation as a whole.

The next step for researchers is to investigate how ConSink’s position is determined by specific clues in the environment and path integration signals generated by the animal itself. They also plan to use behavioral tasks to explore other areas of the brain involved in spatial navigation, such as specific areas adjacent to the hippocampus and the entorhinal cortex containing grid cells. The paradigm is ideally suitable for analyzing the role of the hippocampus in animal models of Alzheimer’s disease, where failure of flexible navigation is one of the earliest signs of the disease.

Professor O’Keefe said, “We have long known that the hippocampus is essential for flexible navigation. This study is a major step in understanding how the hippocampus does this. Over the years, we hope to learn the differences in hippocampal space. The hippocampal cell type contributes to the construction of this vector-based representation, and also records from the cells at the location of ConSink during navigation. We believe that it will provide a powerful tool for analyzing defects in the Alzheimer’s mouse model. ”

Provided by Sainsbury Welcome Center