Scientists model brain structure to help computers recognize objects

July 15, 2017

Simple features, such as particular edges of the image in a specific orientation, are extracted at the first cortical processing stage, called the primary visual cortex, or V1. Then subsequent cortical processing stages, V2, V4, etc., extract progressively more complex features, culminating in the inferotemporal cortex where that essential "viewpoint invariant object identification" is thought to occur. But, most of the connections in the human brain do not project up the cortical hierarchy, as might be expected from gross neuroanatomy, but rather connect neurons located at the same hierarchical level, called lateral connections, and also project down the cortical hierarchy to lower processing levels.

In the recently published work, the team modeled lateral interactions between cortical edge detectors to determine if such connections could explain the difficulty and time course of human contour perception. This research thus combined high-performance computer simulations of cortical circuits, using a National Science Foundation funded neural simulation toolbox, called PetaVision, developed by LANL researchers, along with "speed-of-sight" psychophysical measurements of human contour perception. The psychophysical measurements refer to an experimental technique that neuroscientists use to study mechanisms of cortical processing, using the open-source Psychtoolbox software as an advanced starting point.

"Our research represented the first example of a large-scale cortical model being used to account for both the overall accuracy, as well as the processing time, of human subjects performing a challenging visual-perception task," said Kenyon.

Source: DOE/Los Alamos National Laboratory

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