Contextual influences in V1 as a basis for pop out and asymmetry in visual search

Abstract

I use a model to show how simple, bottom-up, neural mechanisms in primary visual cortex can qualitatively explain the preattentive component of complex psychophysical phenomena of visual search for a target among distracters. Depending on the image features, the speed of search ranges from fast, when a target pops-out or is instantaneously detectable, to very slow, and it can be asymmetric with respect to switches between the target and distracter objects. It has been unclear which neural mechanisms or even cortical areas control the ease of search, and no physiological correlate has been found for search asymmetry. My model suggests that contextual influences in V1 play a significant role.

Figure 1

The model. (A) An input of intermediate contrast to the model. Each bar excites the principal model cells with the appropriate preferred locations and orientations. (B) The local principal (pyramidal) cells and interneurons are roughly reciprocally connected. Each pyramidal cell receives direct input from no more than one bar in the input in A. The pyramidal cells interact with each other (monosynaptically and disynaptically) via horizontal connections, and determine C—the output of the model, with the target’s z score indicated. The thicknesses of the bars are proportional to the temporal averages of pyramidal outputs.

Figure 2

Contextual influences on the center, vertical (target), bar. All visible bars have the same high input contrast except for the near and super-threshold target bar in E, as in the physiological experiments (7, 15). (A) No contextual stimulus. (B–D) Contextual stimuli are bars oriented parallel, orthogonal, or randomly to the target bar, respectively, as in physiological experiments (7). The ratio of the responses to the target bar in A, B, C, and D is 0.98:0.23:0.74:0.41. (E) A simulation of the experiment in ref. . A low contrast (center) target bar is aligned with high contrast contextual bars in a background of randomly oriented bars, leading to a response 70% higher than those to high contrast bars in B. All results are sensitive to input contrast levels.

Figure 3

Inputs and outputs for examples of visual search, with the target’s relative saliency z score indicated under the outputs. All visible bars have the same intermediate input contrast. (A) A vertical target bar among cross distracters is less salient than a target cross among bars in Fig. 1. The response S to the target is within the standard deviation from the average response to all image items. (B) Target ‘⌿’ among distracters ‘∤’. The horizontal bar in the target is the most salient in the image, and its S is 150% higher than the average of the image items. (C) Target ‘⌿’ among distracters ‘∤’ and ‘⍀’ . The target is actually less salient than average in this example.

Figure 4

Five typical examples of visual search asymmetry as simulated in the model (arranged in columns). The input stimuli are plotted, and the target saliency z scores are indicated below each of them. All input bars are of the same intermediate input contrast. The role of figure and ground is switched from the top to the bottom rows.

Figure 5

Three examples of how the model operates as a saliency network to highlight important or conspicuous locations in the image—smooth contours against background noise, or boundaries between simple or more complex texture regions.