Flexible contextual modulation of naturalistic texture perception in peripheral vision.
Ontology highlight
ABSTRACT:
SUBMITTER: Herrera-Esposito D
PROVIDER: S-EPMC7794279 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Identical sensory inputs can be perceived as markedly different when embedded in distinct contexts. Neural responses to simple stimuli are also modulated by context, but the contribution of this modulation to the processing of natural sensory input is unclear. We measured surround suppression, a quintessential contextual influence, in macaque primary visual cortex with natural images. We found that suppression strength varied substantially for different images. This variability was not well explained by existing descriptions of surround suppression, but it was predicted by Bayesian inference about statistical dependencies in images. In this framework, surround suppression was flexible: it was recruited when the image was inferred to contain redundancies and substantially reduced in strength otherwise. Thus, our results reveal a gating of a basic, widespread cortical computation by inference about the statistics of natural input.
| S-EPMC4624479 | biostudies-literature
Project description:Peripheral vision has different functional priorities for mammals than foveal vision. One of its roles is to monitor the environment while central vision is focused on the current task. Becoming distracted too easily would be counterproductive in this perspective, so the brain should react to behaviourally relevant changes. Gist processing is good for this purpose, and it is therefore not surprising that evidence from both functional brain imaging and behavioural research suggests a tendency to generalize and blend information in the periphery. This may be caused by the balance of perceptual influence in the periphery between bottom-up (i.e., sensory information) and top-down (i.e., prior or contextual information) processing channels. Here, we investigated this interaction behaviourally using a peripheral numerosity discrimination task with top-down and bottom-up manipulations. Participants compared numerosity between the left and right peripheries of a screen. Each periphery was divided into a centre and a surrounding area, only one of which was a task relevant target region. Our top-down task modulation was the instruction which area to attend - centre or surround. We varied the signal strength by altering the stimuli durations i.e., the amount of information presented/processed (as a combined bottom-up and recurrent top-down feedback factor). We found that numerosity perceived in target regions was affected by contextual information in neighbouring (but irrelevant) areas. This effect appeared as soon as stimulus duration allowed the task to be reliably performed and persisted even at the longest duration (1 s). We compared the pattern of results with an ideal-observer model and found a qualitative difference in the way centre and surround areas interacted perceptually in the periphery. When participants reported on the central area, the irrelevant surround would affect the response as a weighted combination - consistent with the idea of a receptive field focused in the target area to which irrelevant surround stimulation leaks in. When participants report on surround, we can best describe the response with a model in which occasionally the attention switches from task relevant surround to task irrelevant centre - consistent with a selection model of two competing streams of information. Overall our results show that the influence of spatial context in the periphery is mandatory but task dependent.
| S-EPMC8597708 | biostudies-literature
Project description:In biological vision, contextual modulation refers to the influence of a surround pattern on either the perception of, or the neural responses to, a target pattern. One studied form of contextual modulation deals with the effect of a surround texture on the perceived shape of a contour, in the context of the phenomenon known as the shape aftereffect. In the shape aftereffect, prolonged viewing, or adaptation to a particular contour's shape causes a shift in the perceived shape of a subsequently viewed contour. Shape aftereffects are suppressed when the adaptor contour is surrounded by a texture of similarly-shaped contours, a surprising result given that the surround contours are all potential adaptors. Here we determine the motion and temporal properties of this form of contextual modulation. We varied the relative motion directions, speeds and temporal phases between the central adaptor contour and the surround texture and measured for each manipulation the degree to which the shape aftereffect was suppressed. Results indicate that contextual modulation of shape processing is selective to motion direction, temporal frequency and temporal phase. These selectivities are consistent with one aim of vision being to segregate contours that define objects from those that form textured surfaces.
| S-EPMC5322363 | biostudies-literature
Project description:The perception of motion is considered critical for performing everyday tasks, such as locomotion and driving, and relies on different levels of visual processing. However, it is unclear whether healthy aging differentially affects motion processing at specific levels of processing, or whether performance at central and peripheral spatial eccentricities is altered to the same extent. The aim of this study was to explore the effects of aging on hierarchically different components of motion processing: the minimum displacement of dots to perceive motion (Dmin), the minimum contrast and speed to determine the direction of motion, spatial surround suppression of motion, global motion coherence (translational and radial), and biological motion. We measured motion perception in both central vision and at 15° eccentricity, comparing performance in 20 older (60-79 years) and 20 younger (19-34 years) adults. Older adults had significantly elevated thresholds, relative to younger adults, for motion contrast, speed, Dmin, and biological motion. The differences between younger and older participants were of similar magnitude in central and peripheral vision, except for surround suppression of motion, which was weaker in central vision for the older group, but stronger in the periphery. Our findings demonstrate that the effects of aging are not uniform across all motion tasks. Whereas the performance of some tasks in the periphery can be predicted from the results in central vision, the effects of age on surround suppression of motion shows markedly different characteristics between central and peripheral vision.
| S-EPMC7409591 | biostudies-literature
Project description:How important foveal, parafoveal, and peripheral vision are depends on the task. For object search and letter search in static images of real-world scenes, peripheral vision is crucial for efficient search guidance, whereas foveal vision is relatively unimportant. Extending this research, we used gaze-contingent Blindspots and Spotlights to investigate visual search in complex dynamic and static naturalistic scenes. In Experiment 1, we used dynamic scenes only, whereas in Experiments 2 and 3, we directly compared dynamic and static scenes. Each scene contained a static, contextually irrelevant target (i.e., a gray annulus). Scene motion was not predictive of target location. For dynamic scenes, the search-time results from all three experiments converge on the novel finding that neither foveal nor central vision was necessary to attain normal search proficiency. Since motion is known to attract attention and gaze, we explored whether guidance to the target was equally efficient in dynamic as compared to static scenes. We found that the very first saccade was guided by motion in the scene. This was not the case for subsequent saccades made during the scanning epoch, representing the actual search process. Thus, effects of task-irrelevant motion were fast-acting and short-lived. Furthermore, when motion was potentially present (Spotlights) or absent (Blindspots) in foveal or central vision only, we observed differences in verification times for dynamic and static scenes (Experiment 2). When using scenes with greater visual complexity and more motion (Experiment 3), however, the differences between dynamic and static scenes were much reduced.
| S-EPMC8802022 | biostudies-literature
Project description:Episodic memories are contextual experiences ordered in time. This is underpinned by associative binding between events within the same contexts. The role of prediction errors in declarative memory is well established but has not been investigated in the time dimension of complex episodic memories. Here we combine these two properties of episodic memory, extend them into the temporal domain and demonstrate that prediction errors in different naturalistic contexts lead to changes in the temporal ordering of event structures in them. The wrongly predicted older sequences were weakened despite their reactivation. Interestingly the newly encoded sequences with prediction errors, seen once, showed accuracy as high as control sequences which were viewed repeatedly without change. Drift-diffusion modelling revealed a lower decision threshold for the newer sequences than older sequences, reflected by their faster recall. Moreover, participants' adjustments to their decision threshold significantly correlated with their relative speed of sequence memory recall. These results suggest a temporally distinct and adaptive role for prediction errors in learning and reorganizing episodic temporal sequences.
| S-EPMC8196002 | biostudies-literature
Project description:Human observers can rapidly perceive complex real-world scenes. Grouping visual elements into meaningful units is an integral part of this process. Yet, so far, the neural underpinnings of perceptual grouping have only been studied with simple lab stimuli. We here uncover the neural mechanisms of one important perceptual grouping cue, local parallelism. Using a new, image-computable algorithm for detecting local symmetry in line drawings and photographs, we manipulated the local parallelism content of real-world scenes. We decoded scene categories from patterns of brain activity obtained via functional magnetic resonance imaging (fMRI) in 38 human observers while they viewed the manipulated scenes. Decoding was significantly more accurate for scenes containing strong local parallelism compared to weak local parallelism in the parahippocampal place area (PPA), indicating a central role of parallelism in scene perception. To investigate the origin of the parallelism signal we performed a model-based fMRI analysis of the public BOLD5000 dataset, looking for voxels whose activation time course matches that of the locally parallel content of the 4916 photographs viewed by the participants in the experiment. We found a strong relationship with average local symmetry in visual areas V1-4, PPA, and retrosplenial cortex (RSC). Notably, the parallelism-related signal peaked first in V4, suggesting V4 as the site for extracting paralleism from the visual input. We conclude that local parallelism is a perceptual grouping cue that influences neuronal activity throughout the visual hierarchy, presumably starting at V4. Parallelism plays a key role in the representation of scene categories in PPA.
| S-EPMC8782314 | biostudies-literature
Project description:Scene context is known to facilitate object recognition in both machines and humans, suggesting that the underlying representations may be similar. Alternatively, they may be qualitatively different since the training experience of machines and humans are strikingly different. Machines are typically trained on images containing objects and their context, whereas humans frequently experience scenes without objects (such as highways without cars). If these context representations are indeed different, machine vision algorithms will be improved on augmenting them with human context representations, provided these expectations can be measured and are systematic. Here, we developed a paradigm to measure human contextual expectations. We asked human subjects to indicate the scale, location and likelihood at which cars or people might occur in scenes without these objects. This yielded highly systematic expectations that we could then accurately predict using scene features. This allowed us to predict human expectations on novel scenes without requiring explicit measurements. Next we augmented decisions made by deep neural networks with these predicted human expectations and obtained substantial gains in accuracy for detecting cars and people (1-3%) as well as on detecting associated objects (3-20%). In contrast, augmenting deep network decisions with other conventional computer vision features yielded far smaller gains. Taken together, our results show that augmenting deep neural networks with human-derived contextual expectations improves their performance, suggesting that contextual representations are qualitatively different in humans and deep neural networks.
| S-EPMC6375915 | biostudies-literature
Project description:Texture synthesis models are important tools for understanding visual processing. In particular, statistical approaches based on neurally relevant features have been instrumental in understanding aspects of visual perception and of neural coding. New deep learning-based approaches further improve the quality of synthetic textures. Yet, it is still unclear why deep texture synthesis performs so well, and applications of this new framework to probe visual perception are scarce. Here, we show that distributions of deep convolutional neural network (CNN) activations of a texture are well described by elliptical distributions and therefore, following optimal transport theory, constraining their mean and covariance is sufficient to generate new texture samples. Then, we propose the natural geodesics (i.e. the shortest path between two points) arising with the optimal transport metric to interpolate between arbitrary textures. Compared to other CNN-based approaches, our interpolation method appears to match more closely the geometry of texture perception, and our mathematical framework is better suited to study its statistical nature. We apply our method by measuring the perceptual scale associated to the interpolation parameter in human observers, and the neural sensitivity of different areas of visual cortex in macaque monkeys.
| S-EPMC9681139 | biostudies-literature
Project description:Perception is context dependent. For example, the perceived orientation of a bar changes depending on the presence of oriented bars around it. Contextual effects have also been demonstrated for more complex judgements, such as facial attractiveness or expression, although it remains unclear how these contextual facial effects depend on the types of faces surrounding the target face. To examine this, we measured the perceived age (a quantifiable measure) of a target face in the presence of differently aged faces in the surround. Using a unique database of standardized passport photos, participants were asked to estimate the age of a target face which was viewed either on its own or surrounded by two different identity flanker faces. The flanker faces were either both younger or both older than the target face, with different age offsets between flankers and targets of ±5, ±10, ±15, ±20 years. We find that when a target face is surrounded by younger faces, it systematically appears younger than when viewed on its own, and when it is surrounded by older faces, it systematically appears older than when viewed on its own. Surprisingly, we find that the magnitude of the flanker effects on perceived age of the target is asymmetric with younger flankers having a greater influence than older flankers, a result that may reflect the participants' own-age bias, since all participants were young. This result holds irrespective of gender or race of the faces and is consistent with averaging.
| S-EPMC7813243 | biostudies-literature