Spatiotemporal Isosensitivity Fields in the Human Visual System

Perception ◽  
1986 ◽  
Vol 15 (4) ◽  
pp. 467-472 ◽  
Author(s):  
Bill Jenkins

The human visual system is capable of detecting correlations, manifested perceptually as global pattern, in mathematically constrained dynamic textures. This ability has given rise to speculation that correlative mechanisms in the human visual system exist and that they have a neural basis similar to the orientationally selective structures discovered in area 17 of the mammalian visual cortex. The limits to the detection of correlation were mapped, spatially and temporally, by means of a psychophysical technique. Evidence is presented that, at least in the spatial domain, the correlation mechanism may be served by a population of such neural units.

2016 ◽  
Vol 23 (5) ◽  
pp. 529-541 ◽  
Author(s):  
Sara Ajina ◽  
Holly Bridge

Damage to the primary visual cortex removes the major input from the eyes to the brain, causing significant visual loss as patients are unable to perceive the side of the world contralateral to the damage. Some patients, however, retain the ability to detect visual information within this blind region; this is known as blindsight. By studying the visual pathways that underlie this residual vision in patients, we can uncover additional aspects of the human visual system that likely contribute to normal visual function but cannot be revealed under physiological conditions. In this review, we discuss the residual abilities and neural activity that have been described in blindsight and the implications of these findings for understanding the intact system.


2013 ◽  
Vol 798-799 ◽  
pp. 785-789
Author(s):  
Na Na Zhang ◽  
Jia Fa Mao ◽  
Jing Yin ◽  
Xiao Fang Yang

This paper proposes the estimation method for the maximum payload on spatial domain, concentrates on digital watermarking payload in the spatial domain image, on the constraint of perceptual invisibility research, the influence under the factors in Human Visual System. The maximum payload is influenced by the factors which include the size of image, the brightness masking, contrast masking and texture masking of the image. with such as noise visibility function visual model, gets the just noticeable different value to calculate the payload of the image, finally we get the watermarking payload, test and verify it with Matlab simulation experiments.


2021 ◽  
Author(s):  
Peter J. Kohler ◽  
Alasdair D. F. Clarke

AbstractSymmetries are present at many scales in images of natural scenes. A large body of literature has demonstrated contributions of symmetry to numerous domains of visual perception. The four fundamental symmetries, reflection, rotation, translation and glide reflection, can be combined in exactly 17 distinct ways. These wallpaper groups represent the complete set of symmetries in 2D images and have recently found use in the vision science community as an ideal stimulus set for studying the perception of symmetries in textures. The goal of the current study is to provide a more comprehensive description of responses to symmetry in the human visual system, by collecting both brain imaging (Steady-State Visual Evoked Potentials measured using high-density EEG) and behavioral (symmetry detection thresholds) data using the entire set of wallpaper groups. This allows us to probe the hierarchy of complexity among wallpaper groups, in which simpler groups are subgroups of more complex ones. We find that this hierarchy is preserved almost perfectly in both behavior and brain activity: A multi-level Bayesian GLM indicates that for most of the 63 subgroup relationships, subgroups produce lower amplitude responses in visual cortex (posterior probability: > 0.95 for 56 of 63) and require longer presentation durations to be reliably detected (posterior probability: > 0.95 for 49 of 63). This systematic pattern is seen only in visual cortex and only in components of the brain response known to be symmetric-specific. Our results show that representations of symmetries in the human brain are precise and rich in detail, and that this precision is reflected in behavior. These findings expand our understanding of symmetry perception, and open up new avenues for research on how fine-grained representations of regular textures contribute to natural vision.


Author(s):  
Yaghoub Pourasad

<p>Identify objects based on modeling the human visual system, as an effective method in intelligent identification, has attracted the attention of many researchers. Although the machines have high computational speed but are very weak as compared to humans in terms of diagnosis. Experience has shown that in many areas of image processing, algorithms that have biological backing had more simplicity and better performance. The human visual system, first select the main parts of the image which is provided by the visual featured model, then pays to object recognition which is a hierarchical operations according to this, HMAX model is also provided. HMAX object recognition model from the group of hierarchical models without feedback that its structure and parameters selected based on biological characteristics of the visual cortex. This model is a hierarchical model neural network with four layers, is composed of alternating layers that are simple and complex. Due to the high complexity of the human visual system is virtually impossible to replicate it. For each of the above, separate models have been proposed but in the human visual system, this operation is performed seamlessly, thus, by combining the principles of these models is expected to be closer to the human visual system and obtain a higher recognition rate. In this paper, we introduce an architecture to classify images based on a combination of previous work is based on the basic operation of the visual cortex. According to the results presented, the proposed model compared with the main HMAX model has a much higher recognition rate. Simulations was performed on the database of Caltech101.</p>


2016 ◽  
Vol 283 (1830) ◽  
pp. 20160383 ◽  
Author(s):  
Alexander A. Muryy ◽  
Roland W. Fleming ◽  
Andrew E. Welchman

Visually identifying glossy surfaces can be crucial for survival (e.g. ice patches on a road), yet estimating gloss is computationally challenging for both human and machine vision. Here, we demonstrate that human gloss perception exploits some surprisingly simple binocular fusion signals, which are likely available early in the visual cortex. In particular, we show that the unusual disparity gradients and vertical offsets produced by reflections create distinctive ‘proto-rivalrous’ (barely fusible) image regions that are a critical indicator of gloss. We find that manipulating the gradients and vertical components of binocular disparities yields predictable changes in material appearance. Removing or occluding proto-rivalrous signals makes surfaces look matte, while artificially adding such signals to images makes them appear glossy. This suggests that the human visual system has internalized the idiosyncratic binocular fusion characteristics of glossy surfaces, providing a straightforward means of estimating surface attributes using low-level image signals.


2018 ◽  
Author(s):  
Philip A. Kragel ◽  
Marianne Reddan ◽  
Kevin S. LaBar ◽  
Tor D. Wager

AbstractTheorists have suggested that emotions are canonical responses to situations ancestrally linked to survival. If so, then emotions may be afforded by features of the sensory environment. However, few computationally explicit models describe how combinations of stimulus features evoke different emotions. Here we develop a convolutional neural network that accurately decodes images into 11 distinct emotion categories. We validate the model using over 25,000 images and movies and show that image content is sufficient to predict the category and valence of human emotion ratings. In two fMRI studies, we demonstrate that patterns of human visual cortex activity encode emotion category-related model output and can decode multiple categories of emotional experience. These results suggest that rich, category-specific emotion representations are embedded within the human visual system.


2020 ◽  
Author(s):  
Gokulraj T. Prabhakaran ◽  
Khaldoon O. Al-Nosairy ◽  
Claus Tempelmann ◽  
Markus Wagner ◽  
Hagen Thieme ◽  
...  

AbstractfMRI studies in macular degeneration (MD) and retinitis pigmentosa (RP) demonstrated that responses in the lesion projection zones (LPZ) of V1 are task related, indicating significant limits of bottom-up visual system plasticity in MD and RP. In advanced glaucoma (GL), a prevalent eye disease and leading cause of blindness, the scope of visual system plasticity is currently unknown. We performed 3T fMRI in patients with extensive visual field defects due to GL (n=5), RP (n=2) and healthy controls (n=7; with simulated defects). Participants viewed contrast patterns drifting in 8 directions alternating with uniform gray and performed 3 tasks: (1) passive viewing (PV), (2) one-back task (OBT) and (3) fixation-dot task (FDT). During PV, they passively viewed the stimulus with central fixation, during OBT they reported the succession of the same two motion directions, and during FDT a change in the fixation color. In GL, LPZ responses of the early visual cortex (V1, V2 and V3) shifted from negative during PV to positive for OBT [p (corrected): V1(0.006); V2(0.04); V3(0.008)], while they were negative in the controls’ simulated LPZ for all stimulation conditions. For RP a similar pattern as for GL was observed. Consequently, activity in the de-afferented visual cortex in glaucoma is, similar to MD and RP, task-related. In conclusion, the lack of bottom-up plasticity appears to be a general feature of the human visual system. These insights are of importance for the development of treatment and rehabilitation schemes in glaucoma.HighlightsFunctional dynamics of early visual cortex LPZ depend on task demands in glaucomaBrain activity in deprived visual cortex suggests absence of large-scale remappingLimited scope of bottom-up plasticity is a general feature of human visual systemVisual system stability and plasticity is of relevance for therapeutic advances


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