Yanbo Lian, Simon Williams, Andrew S. Alexander, Michael E. Hasselmo, Anthony N. Burkitt. Learning the Vector Coding of Egocentric Boundary Cells from Visual Data. Journal of Neuroscience 12 July 2023, 43 (28) 5180-5190; DOI: 10.1523/JNEUROSCI.1071-22.2023

Abstract
“The use of spatial maps to navigate through the world requires a complex ongoing transformation of egocentric views of the environment into position within the allocentric map. Recent research has discovered neurons in retrosplenial cortex and other structures that could mediate the transformation from egocentric views to allocentric views. These egocentric boundary cells respond to the egocentric direction and distance of barriers relative to an animal’s point of view. This egocentric coding based on the visual features of barriers would seem to require complex dynamics of cortical interactions. However, computational models presented here show that egocentric boundary cells can be generated with a remarkably simple synaptic learning rule that forms a sparse representation of visual input as an animal explores the environment. Simulation of this simple sparse synaptic modification generates a population of egocentric boundary cells with distributions of direction and distance coding that strikingly resemble those observed within the retrosplenial cortex. Furthermore, some egocentric boundary cells learnt by the model can still function in new environments without retraining. This provides a framework for understanding the properties of neuronal populations in the retrosplenial cortex that may be essential for interfacing egocentric sensory information with allocentric spatial maps of the world formed by neurons in downstream areas, including the grid cells in entorhinal cortex and place cells in the hippocampus.”

SIGNIFICANCE STATEMENT

“The computational model presented here demonstrates that the recently discovered egocentric boundary cells in retrosplenial cortex can be generated with a remarkably simple synaptic learning rule that forms a sparse representation of visual input as an animal explores the environment. Additionally, our model generates a population of egocentric boundary cells with distributions of direction and distance coding that strikingly resemble those observed within the retrosplenial cortex. This transformation between sensory input and egocentric representation in the navigational system could have implications for the way in which egocentric and allocentric representations interface in other brain areas.”

Yanbo Lian, Simon Williams, Andrew S. Alexander, Michael E. Hasselmo, Anthony N. Burkitt. Learning the Vector Coding of Egocentric Boundary Cells from Visual Data. Journal of Neuroscience 12 July 2023, 43 (28) 5180-5190; DOI: 10.1523/JNEUROSCI.1071-22.2023