Facing a Regular World: How Spatial Object Structure Shapes Visual Processing

Information redundancy across spatial scales modulates early visual cortical processing

Visual images contain redundant information across spatial scales where low spatial frequency contrast is informative towards the location and likely content of high spatial frequency detail. Previous research suggests that the visual system makes use of those redundancies to facilitate efficient processing. In this framework, a fast, initial analysis of low-spatial frequency (LSF) information guides the slower and later processing of high spatial frequency (HSF) detail. Here, we used multivariate classification as well as time-frequency analysis of MEG responses to the viewing of intact and phase scrambled images of human faces to demonstrate that the availability of redundant LSF information, as found in broadband intact images, correlates with a reduction in HSF representational dominance in both early and higher-level visual areas as well as a reduction of gamma-band power in early visual cortex. Our results indicate that the cross spatial frequency information redundancy that can be found in all natural images might be a driving factor in the efficient integration of fine image details.

Rapid contextualization of fragmented scene information in the human visual system

Real-world environments are extremely rich in visual information. At any given moment in time, only a fraction of this information is available to the eyes and the brain, rendering naturalistic vision a collection of incomplete snapshots. Previous research suggests that in order to successfully contextualize this fragmented information, the visual system sorts inputs according to spatial schemata, that is knowledge about the typical composition of the visual world. Here, we used a large set of 840 different natural scene fragments to investigate whether this sorting mechanism can operate across the diverse visual environments encountered during real-world vision. We recorded brain activity using electroencephalography (EEG) while participants viewed incomplete scene fragments at fixation. Using representational similarity analysis on the EEG data, we tracked the fragments' cortical representations across time. We found that the fragments' typical vertical location within the environment (top or bottom) predicted their cortical representations, indexing a sorting of information according to spatial schemata. The fragments' cortical representations were most strongly organized by their vertical location at around 200 ​ms after image onset, suggesting rapid perceptual sorting of information according to spatial schemata. In control analyses, we show that this sorting is flexible with respect to visual features: it is neither explained by commonalities between visually similar indoor and outdoor scenes, nor by the feature organization emerging from a deep neural network trained on scene categorization. Demonstrating such a flexible sorting across a wide range of visually diverse scenes suggests a contextualization mechanism suitable for complex and variable real-world environments.

Artificial Intelligence and Polyp Detection

PURPOSE OF REVIEW

This review highlights the history, recent advances, and ongoing challenges of artificial intelligence (AI) technology in colonic polyp detection.

RECENT FINDINGS

Hand-crafted AI algorithms have recently given way to convolutional neural networks with the ability to detect polyps in real-time. The first randomized controlled trial comparing an AI system to standard colonoscopy found a 9% increase in adenoma detection rate, but the improvement was restricted to polyps smaller than 10 mm and the results need validation. As this field rapidly evolves, important issues to consider include standardization of outcomes, dataset availability, real-world applications, and regulatory approval.

SUMMARY

AI has shown great potential for improving colonic polyp detection while requiring minimal training for endoscopists. The question of when AI will enter endoscopic practice depends on whether the technology can be integrated into existing hardware and an assessment of its added value for patient care.

Typical visual-field locations enhance processing in object-selective channels of human occipital cortex

Natural environments consist of multiple objects, many of which repeatedly occupy similar locations within a scene. For example, hats are seen on people’s heads, while shoes are most often seen close to the ground. Such positional regularities bias the distribution of objects across the visual field: hats are more often encountered in the upper visual field, while shoes are more often encountered in the lower visual field. Here we tested the hypothesis that typical visual field locations of objects facilitate cortical processing. We recorded functional MRI while participants viewed images of objects that were associated with upper or lower visual field locations. Using multivariate classification, we show that object information can be more successfully decoded from response patterns in object-selective lateral occipital cortex (LO) when the objects are presented in their typical location (e.g., shoe in the lower visual field) than when they are presented in an atypical location (e.g., shoe in the upper visual field). In a functional connectivity analysis, we relate this benefit to increased coupling between LO and early visual cortex, suggesting that typical object positioning facilitates information propagation across the visual hierarchy. Together these results suggest that object representations in occipital visual cortex are tuned to the structure of natural environments. This tuning may support object perception in spatially structured environments.

NEW & NOTEWORTHY In the real world, objects appear in predictable spatial locations. Hats, commonly appearing on people’s heads, often fall into the upper visual field. Shoes, mostly appearing on people’s feet, often fall into the lower visual field. Here we used functional MRI to demonstrate that such regularities facilitate cortical processing: Objects encountered in their typical locations are coded more efficiently, which may allow us to effortlessly recognize objects in natural environments.

Typical visual-field locations facilitate access to awareness for everyday objects

In real-world vision, humans are constantly confronted with complex environments that contain a multitude of objects. These environments are spatially structured, so that objects have different likelihoods of appearing in specific parts of the visual space. Our massive experience with such positional regularities prompts the hypothesis that the processing of individual objects varies in efficiency across the visual field: when objects are encountered in their typical locations (e.g., we are used to seeing lamps in the upper visual field and carpets in the lower visual field), they should be more efficiently perceived than when they are encountered in atypical locations (e.g., a lamp in the lower visual field and a carpet in the upper visual field). Here, we provide evidence for this hypothesis by showing that typical positioning facilitates an object's access to awareness. In two continuous flash suppression experiments, objects more efficiently overcame inter-ocular suppression when they were presented in visual-field locations that matched their typical locations in the environment, as compared to non-typical locations. This finding suggests that through extensive experience the visual system has adapted to the statistics of the environment. This adaptation may be particularly useful for rapid object individuation in natural scenes.