Rapid Processing of a Global Feature in the ON Visual Pathways of Behaving Monkeys

Jun Huang,Chunming Zhang,Yingshan Yang,Quan Zhou,Yifeng Zhou,Yan Yang,Ke Zhou,Xudong Zhao,Wu Zhou,Hong Zhu

doi:10.3389/fnins.2017.00474

Abstract

Visual objects are recognized by their features. Whereas, some features are based on simple components (i.e., local features, such as orientation of line segments), some features are based on the whole object (i.e., global features, such as an object having a hole in it). Over the past five decades, behavioral, physiological, anatomical, and computational studies have established a general model of vision, which starts from extracting local features in the lower visual pathways followed by a feature integration process that extracts global features in the higher visual pathways. This local-to-global model is successful in providing a unified account for a vast sets of perception experiments, but it fails to account for a set of experiments showing human visual systems' superior sensitivity to global features. Understanding the neural mechanisms underlying the “global-first” process will offer critical insights into new models of vision. The goal of the present study was to establish a non-human primate model of rapid processing of global features for elucidating the neural mechanisms underlying differential processing of global and local features. Monkeys were trained to make a saccade to a target in the black background, which was different from the distractors (white circle) in color (e.g., red circle target), local features (e.g., white square target), a global feature (e.g., white ring with a hole target) or their combinations (e.g., red square target). Contrary to the predictions of the prevailing local-to-global model, we found that (1) detecting a distinction or a change in the global feature was faster than detecting a distinction or a change in color or local features; (2) detecting a distinction in color was facilitated by a distinction in the global feature, but not in the local features; and (3) detecting the hole was interfered by the local features of the hole (e.g., white ring with a squared hole). These results suggest that monkey ON visual systems have a subsystem that is more sensitive to distinctions in the global feature than local features. They also provide the behavioral constraints for identifying the underlying neural substrates.

Highlights

Extensive investigations over the past five decades have led to a general model of visual information processing, which starts from extracting local features of the retinal images in the lower visual pathways followed by integrating the local features to extract global features in the higher visual pathways (Hubel, 1988)
Whether a visual object has a hole in it was used as a representative global feature and line segments were used as representative local features
Since the local features are believed to be extracted in the early visual pathways and the global features are extracted in the later visual pathways by integrating the local features (Figure 10A), it is predicted that detecting distinctions or a change in local features takes less time than detecting distinctions or a change in the global feature

Summary

Introduction

Extensive investigations over the past five decades have led to a general model of visual information processing, which starts from extracting local features of the retinal images in the lower visual pathways followed by integrating the local features to extract global features in the higher visual pathways (Hubel, 1988). Using a visual search paradigm, Treisman and Gelade (1980) found that primitive features, such as color or orientation of line segments are extracted effortlessly, and in parallel over the entire visual field, and registered in special modules of feature maps. They suggested that in a later stage, focal attention is required to recombine the separate features for object recognition. Over the past half century, the local-to-global theory of visual information processing has gained general acceptance and dominates the field of vision research

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