Abstract

Mechanisms of explicit object recognition are often difficult to investigate and require stimuli with controlled features whose expression can be manipulated in a precise quantitative fashion. Here, we developed a novel method (called “Dots”), for generating visual stimuli, which is based on the progressive deformation of a regular lattice of dots, driven by local contour information from images of objects. By applying progressively larger deformation to the lattice, the latter conveys progressively more information about the target object. Stimuli generated with the presented method enable a precise control of object-related information content while preserving low-level image statistics, globally, and affecting them only little, locally. We show that such stimuli are useful for investigating object recognition under a naturalistic setting – free visual exploration – enabling a clear dissociation between object detection and explicit recognition. Using the introduced stimuli, we show that top-down modulation induced by previous exposure to target objects can greatly influence perceptual decisions, lowering perceptual thresholds not only for object recognition but also for object detection (visual hysteresis). Visual hysteresis is target-specific, its expression and magnitude depending on the identity of individual objects. Relying on the particular features of dot stimuli and on eye-tracking measurements, we further demonstrate that top-down processes guide visual exploration, controlling how visual information is integrated by successive fixations. Prior knowledge about objects can guide saccades/fixations to sample locations that are supposed to be highly informative, even when the actual information is missing from those locations in the stimulus. The duration of individual fixations is modulated by the novelty and difficulty of the stimulus, likely reflecting cognitive demand.

Highlights

  • The investigation of object recognition in the human visual system is a challenging problem and often requires visual paradigms able to manipulate various features of the stimulus in order to increase or decrease the ability of human subjects to detect, categorize, or precisely identify a target object

  • Visual stimuli are generated by the controlled deformation of a lattice of dots that is driven by a single feature of the original image: local contour density

  • The method creates a map of points of interest (POI) to compute local information content around each pixel in the source image

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Summary

Introduction

The investigation of object recognition in the human visual system is a challenging problem and often requires visual paradigms able to manipulate various features of the stimulus in order to increase or decrease the ability of human subjects to detect, categorize, or precisely identify a target object. Example techniques include image degradation [1], degradation based on Gaussian filters [2], morphing [3], manipulation of contrast either directly [4] or using controlled agglomerations of pixels [5] Many of these methods do not preserve lowlevel features of the stimulus such as contrast, global luminance, or distribution of spatial frequencies. Tjan et al [8] manipulated signal-to-noise ratio (SNR) by mixing the image with pink-noise but keeping the mean luminance and the root mean squared (RMS) contrast constant Another powerful technique is random image structure evolution (RISE), which manipulates the phase spectrum (via a continuous transformation from original to some other phase spectrum of choice, such as a random phase spectrum) in such a way that the global luminance, the contrast and the distribution of spatial frequencies are preserved [7,9,10,11]

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