Near optimal hierarchical encoding of types

Tuning in scene-preferring cortex for mid-level visual features gives rise to selectivity across multiple levels of stimulus complexity

10.1101/2021.09.24.461733 ◽

2021 ◽

Author(s):

Shi Pui Donald Li ◽

Michael F. Bonner

Keyword(s):

Real World ◽

Computational Models ◽

Visual Stream ◽

Computational Theory ◽

Low Level ◽

Multiple Levels ◽

High Level ◽

Hierarchical Encoding ◽

Natural Statistics ◽

High Throughput Experiments

The scene-preferring portion of the human ventral visual stream, known as the parahippocampal place area (PPA), responds to scenes and landmark objects, which tend to be large in real-world size, fixed in location, and inanimate. However, the PPA also exhibits preferences for low-level contour statistics, including rectilinearity and cardinal orientations, that are not directly predicted by theories of scene- and landmark-selectivity. It is unknown whether these divergent findings of both low- and high-level selectivity in the PPA can be explained by a unified computational theory. To address this issue, we fit hierarchical computational models of mid-level tuning to the image-evoked fMRI responses of the PPA, and we performed a series of high-throughput experiments on these models. Our findings show that hierarchical encoding models of the PPA exhibit emergent selectivity across multiple levels of complexity, giving rise to high-level preferences along dimensions of real-world size, fixedness, and naturalness/animacy as well as low-level preferences for rectilinear shapes and cardinal orientations. These results reconcile disparate theories of PPA function in a unified model of mid-level visual representation, and they demonstrate how multifaceted selectivity profiles naturally emerge from the hierarchical computations of visual cortex and the natural statistics of images.

Download Full-text

Change in Evaluation Mode Can Cause a Cheerleader Effect

Frontiers in Psychology ◽

10.3389/fpsyg.2021.607448 ◽

2021 ◽

Vol 12 ◽

Author(s):

Claude Messner ◽

Mattia Carnelli ◽

Patrick Stefan Hähener

Keyword(s):

Social Media ◽

Visual Information ◽

Visual Memory ◽

Target Face ◽

Contrast Effects ◽

Evaluation Mode ◽

Standard Of Comparison ◽

Low Levels ◽

Hierarchical Encoding ◽

Practical Implications

The cheerleader effect describes the phenomenon whereby faces are perceived as being more attractive when flanked by other faces than when they are perceived in isolation. At least four theories predict the cheerleader effect. Two visual memory processes could cause a cheerleader effect. First, visual information will sometimes be averaged in the visual memory: the averaging of faces could increase the perceived attractiveness of all the faces flanked by other faces. Second, information will often be combined into a higher-order concept. This hierarchical encoding suggests that information processing causes faces to appear more attractive when flanked by highly attractive faces. Two further explanations posit that comparison processes cause the cheerleader effect. While contrast effects predict that a difference between the target face and the flanking faces causes the cheerleader effect due to comparison processes, a change in the evaluation mode, which alters the standard of comparison between joint and separate evaluation of faces, could be sufficient for producing a cheerleader effect. This leads to the prediction that even when there is no contrast between the attractiveness of the target face and the flanking faces, a cheerleader effect could occur. The results of one experiment support this prediction. The findings of this study have practical implications, such as for individuals who post selfies on social media. An individual’s face will appear more attractive in a selfie taken with people of low attractiveness than in a selfie without other people, even when all the faces have equally low levels of attractiveness.

Download Full-text