Computational neuroscientists at Carnegie Mellon University have developed a computational model that provides insight into the function of the brain’s visual cortex and the information processing that enables people to perceive contours and surfaces, and understand what they see in the world around them.

The model employs an algorithm that analyzes the myriad patterns that compose natural scenes and statistically characterizes those patterns to determine which patterns are most likely associated with each other.