Object Vector Cells are a type of neuron in the Endorhinal Cortext (EC). They were discovered in 2019. They are unique and have interesting properties compared to other neurons.
They seem to fire when an organism is at a specific distance and direction to an object. It doesnt matter where the objects are in the environment. You could move the object and when the organism is near the object again, those same object vector cells would fire. You can also completely switch out the environment and keep the same distance and direction to the object and those same cells would fire.
Vectors in math usually contain both a direction and distance (magnitude), just like these object vector cells. The difference is these object vector cells fire in relation to the organism and the objects.
The objects that object vector cells fire on are not for specific objects like “my computer”. Instead they will fire for a broad range of objects that are nearby the organism. Tests have shown that the objects can have different shapes (such as pointy or broad surfaces) , different sizes, different colors, different lengths, different textures, and different heights. So it seems to not matter at all what the object is.
I suspect that these object vector cells also fire in a similar fashion when the mind is running calculations internally and not moving, navigating some kind of conceptual space linking concepts together.
The EC is the main interface between the neocortex and the hippocampus. I suspect that the cells in the EC act as some kind of generalizer or convertor that takes features/data from the neocortex and convert the data into some other kind of lookup code that allows the hippocampus to quickly find relevant memories and other data for the neocortex to use. Another way to say it, I think that the EC cells are converting specific stimulus like “your 1995 Toyota Corolla” into generalized features or the skeleton of the object, which is the concept of car.