Smooth versus Textured Surfaces: Feature-Based Category Selectivity in Human Visual Cortex

Modeling visual aesthetic perception: bridges between computed texture features and perceived beauty qualities in semantic experiments

The exploration of the potential relationship between computable low-level texture, such as features extracted from color and texture, and the perceived high-level aesthetic properties, such as warm or cold, soft or hard, has been a hot research topic of neuroaesthetics. First, the selection and clustering of aesthetic antonyms used to represent the aesthetic properties of visual texture are completed through two semantic differential experiments. Subsequently, 151 visual textures are rated according to the selected aesthetic antonyms by participants in a third semantic differential experiment. Third, 106 textural features are extracted using four different image analysis algorithms to describe the low-level characteristics of visual textures. Finally, the construction and evaluation of the visual aesthetic perception model based on multiple linear and nonlinear regression algorithms are discussed. We analyzed the frequency of each aesthetic antonym selected from 20 pairs of semantic antonyms, and the most frequently mentioned 8 pairs of semantic antonyms were selected as the core set for model building. The extracted low-level features are highly correlative. Of the correlation coefficients based on absolute values, 3383 are less than 0.75, accounting for 14.84% of the total. The correlation coefficients were larger than 0.5 accounts for 27.29% of the total. Through neighborhood component analysis, the top 10 low-level features are selected with lower correlation. The gap between low-level calculated features and high-level perceived aesthetic emotions can be bridged by a brain-inspired model of visual aesthetic perception.

Impact of Huntington's Disease on Mental Rotation Performance in Motor Pre-Symptomatic Individuals

BACKGROUND

Huntington's disease (HD) is a genetic disorder known for affecting motor control. Despite evidence for the impact of HD on visual cortico-striatal loops, evidence for impaired visual perception in early symptomatic HD patients is limited; much less is known about what happens during the HD prodrome.

OBJECTIVE

The goals of this study were to evaluate perceptual processing in motor pre-manifest HD gene-carriers (Pre-HDs) during a visual mental rotation task.

METHODS

To achieve this goal, 79 participants including 24 Pre-HD participants and 55 healthy matched controls were scanned using functional MRI as they performed a mental rotation task. Another group of 36 subjects including 15 pre-HDs and 21 healthy age/gender matched controls participated in a control behavioral test of judgment of line orientation outside the scanner.

RESULTS

We found that, although Pre-HDs (in this stage of disease) did not demonstrate slower response times, their response accuracy was lower than controls. On the fMRI task, controls showed a significant decrease in activity in the occipito-temporal (OT) visual network and increase in activity in the caudo-fronto-parietal (CFP) network with mental rotation load. Interestingly, the amount of mental rotation-related activity decrease in the OT network was reduced in Pre-HDs compared to controls while, the level of CFP response remained unchanged between the two groups. Comparing the link between the evoked BOLD activity within these networks and response accuracy (i.e., behavior), we found that the models fit to data from controls were less accurate in predicting response accuracy of Pre-HDs.

CONCLUSION

These findings provide some of the earliest functional evidence of impaired visual processing and altered neural processing underlying visual perceptual decision making during the HD prodrome.

Object shape and surface properties are jointly encoded in mid-level ventral visual cortex

Recognizing a myriad visual objects rapidly is a hallmark of the primate visual system. Traditional theories of object recognition have focused on how crucial form features, for example, the orientation of edges, may be extracted in early visual cortex and utilized to recognize objects. An alternative view argues that much of early and mid-level visual processing focuses on encoding surface characteristics, for example, texture. Neurophysiological evidence from primate area V4 supports a third alternative - the joint, but independent, encoding of form and texture - that would be advantageous for segmenting objects from the background in natural scenes and for object recognition that is independent of surface texture. Future studies that leverage deep convolutional network models, especially focusing on network failures to match biology and behavior, can advance our insights into how such a joint representation of form and surface properties might emerge in visual cortex.