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Visual stimulus features that elicit activity in object-vector cells
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DOI：10.1038/s42003-021-02727-5.png)
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Abstract
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Object-vector (OV) cells are cells in the medial entorhinal cortex (MEC) that track an animal's distance and direction to objects in the environment. Their firing fields are defined by vectorial relationships to free-standing 3-dimensional (3D) objects of a variety of identities and shapes. However, the natural world contains a panorama of objects, ranging from discrete 3D items to flat two-dimensional (2D) surfaces, and it remains unclear what are the most fundamental features of objects that drive vectorial responses. Here we address this question by systematically changing features of experimental objects. Using an algorithm that robustly identifies OV firing fields, we show that the cells respond to a variety of 2D surfaces, with visual contrast as the most basic visual feature to elicit neural responses. The findings suggest that OV cells use plain visual features as vectorial anchoring points, allowing vector-guided navigation to proceed in environments with few free-standing landmarks. In order to understand more about which object features are the most influential when driving vectorial responses, Andersson et al. use an algorithm to reliably examine object-vector (OV) cells in mice. Their findings suggest that OV cells use visual features as anchoring points, allowing vector-guided navigation to proceed with reference to a wide range of visual landmarks.
Keywords:
SPATIAL REPRESENTATION
GRID CELLS
HIPPOCAMPUS
MAP
PARVALBUMIN
NAVIGATION
DIRECTION
SPACE
MODEL
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