scholarly journals Transformation from independent to integrative coding of multi-object arrangements in human visual cortex

2017 ◽  
Author(s):  
Daniel Kaiser ◽  
Marius V. Peelen
Keyword(s):  
Visual Cortex ◽  
Visual System ◽  
Activity Patterns ◽  
Spatial Arrangement ◽  
Living Room ◽  
Natural Scenes ◽  
Response Patterns ◽  
Object Representations ◽  
Individual Object ◽  
Object Coding

AbstractTo optimize processing, the human visual system utilizes regularities present in naturalistic visual input. One of these regularities is the relative position of objects in a scene (e.g., a sofa in front of a television), with behavioral research showing that regularly positioned objects are easier to perceive and to remember. Here we use fMRI to test how positional regularities are encoded in the visual system. Participants viewed pairs of objects that formed minimalistic two-object scenes (e.g., a “living room” consisting of a sofa and television) presented in their regularly experienced spatial arrangement or in an irregular arrangement (with interchanged positions). Additionally, single objects were presented centrally and in isolation. Multi-voxel activity patterns evoked by the object pairs were modeled as the average of the response patterns evoked by the two single objects forming the pair. In two experiments, this approximation in object-selective cortex was significantly less accurate for the regularly than the irregularly positioned pairs, indicating integration of individual object representations. More detailed analysis revealed a transition from independent to integrative coding along the posterior-anterior axis of the visual cortex, with the independent component (but not the integrative component) being almost perfectly predicted by object selectivity across the visual hierarchy. These results reveal a transitional stage between individual object and multi-object coding in visual cortex, providing a possible neural correlate of efficient processing of regularly positioned objects in natural scenes.

Ultrafast Object Detection in Naturalistic Vision Relies on Ultrafast Distractor Suppression

2019 ◽  
Vol 31 (10) ◽  
pp. 1563-1572 ◽  
Author(s):  
Clayton Hickey ◽  
Daniele Pollicino ◽  
Giacomo Bertazzoli ◽  
Ludwig Barbaro
Keyword(s):  
Visual Cortex ◽  
Spatial Attention ◽  
Brain Activity ◽  
Natural Scenes ◽  
Search Efficiency ◽  
Object Representations ◽  
Target Presence ◽  
Object Categories ◽  
Frontal Brain ◽  
Scene Information

People are quicker to detect examples of real-world object categories in natural scenes than is predicted by classic attention theories. One explanation for this puzzle suggests that experience renders the visual system sensitive to midlevel features diagnosing target presence. These are detected without the need for spatial attention, much as occurs for targets defined by low-level features like color or orientation. The alternative is that naturalistic search relies on spatial attention but is highly efficient because global scene information can be used to quickly reject nontarget objects and locations. Here, we use ERPs to differentiate between these possibilities. Results show that hallmark evidence of ultrafast target detection in frontal brain activity is preceded by an index of spatially specific distractor suppression in visual cortex. Naturalistic search for heterogenous targets therefore appears to rely on spatial operations that act on neural object representations, as predicted by classic attention theory. People appear able to rapidly reject nontarget objects and locations, consistent with the idea that global scene information is used to constrain naturalistic search and increase search efficiency.

scholarly journals Orientation tuning depends on spatial frequency in mouse visual cortex

2016 ◽  
Author(s):  
Inbal Ayzenshtat ◽  
Jesse Jackson ◽  
Rafael Yuste
Keyword(s):  
Visual Cortex ◽  
Spatial Frequency ◽  
Visual System ◽  
Primary Visual Cortex ◽  
Receptive Fields ◽  
Orientation Selectivity ◽  
Natural Scenes ◽  
Response Properties ◽  
Layer 2 ◽  
Mouse Visual Cortex

AbstractThe response properties of neurons to sensory stimuli have been used to identify their receptive fields and functionally map sensory systems. In primary visual cortex, most neurons are selective to a particular orientation and spatial frequency of the visual stimulus. Using two-photon calcium imaging of neuronal populations from the primary visual cortex of mice, we have characterized the response properties of neurons to various orientations and spatial frequencies. Surprisingly, we found that the orientation selectivity of neurons actually depends on the spatial frequency of the stimulus. This dependence can be easily explained if one assumed spatially asymmetric Gabor-type receptive fields. We propose that receptive fields of neurons in layer 2/3 of visual cortex are indeed spatially asymmetric, and that this asymmetry could be used effectively by the visual system to encode natural scenes.Significance StatementIn this manuscript we demonstrate that the orientation selectivity of neurons in primary visual cortex of mouse is highly dependent on the stimulus SF. This dependence is realized quantitatively in a decrease in the selectivity strength of cells in non-optimum SF, and more importantly, it is also evident qualitatively in a shift in the preferred orientation of cells in non-optimum SF. We show that a receptive-field model of a 2D asymmetric Gabor, rather than a symmetric one, can explain this surprising observation. Therefore, we propose that the receptive fields of neurons in layer 2/3 of mouse visual cortex are spatially asymmetric and this asymmetry could be used effectively by the visual system to encode natural scenes.Highlights–Orientation selectivity is dependent on spatial frequency.–Asymmetric Gabor model can explain this dependence.

scholarly journals The human visual system preserves the hierarchy of 2-dimensional pattern regularity

2021 ◽  
Author(s):  
Peter J. Kohler ◽  
Alasdair D. F. Clarke
Keyword(s):  
Visual Cortex ◽  
Visual System ◽  
Human Visual System ◽  
Posterior Probability ◽  
Brain Activity ◽  
Large Body ◽  
Natural Scenes ◽  
Brain Response ◽  
Lower Amplitude ◽  
Wallpaper Groups

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.

Mammalian Visual System Organization

2017 ◽  
Author(s):  
Farran Briggs
Keyword(s):  
Visual Cortex ◽  
Visual System ◽  
Visual Information ◽  
Contextual Information ◽  
Sensory Information ◽  
Visual Image ◽  
Brain Structures ◽  
Object Representations ◽  
System A ◽  
The Brain

Many mammals, including humans, rely primarily on vision to sense the environment. While a large proportion of the brain is devoted to vision in highly visual animals, there are not enough neurons in the visual system to support a neuron-per-object look-up table. Instead, visual animals evolved ways to rapidly and dynamically encode an enormous diversity of visual information using minimal numbers of neurons (merely hundreds of millions of neurons and billions of connections!). In the mammalian visual system, a visual image is essentially broken down into simple elements that are reconstructed through a series of processing stages, most of which occur beneath consciousness. Importantly, visual information processing is not simply a serial progression along the hierarchy of visual brain structures (e.g., retina to visual thalamus to primary visual cortex to secondary visual cortex, etc.). Instead, connections within and between visual brain structures exist in all possible directions: feedforward, feedback, and lateral. Additionally, many mammalian visual systems are organized into parallel channels, presumably to enable efficient processing of information about different and important features in the visual environment (e.g., color, motion). The overall operations of the mammalian visual system are to: (1) combine unique groups of feature detectors in order to generate object representations and (2) integrate visual sensory information with cognitive and contextual information from the rest of the brain. Together, these operations enable individuals to perceive, plan, and act within their environment.

scholarly journals Differential Representations of Perceived and Retrieved Visual Information in Hippocampus and Cortex

2018 ◽  
Vol 29 (10) ◽  
pp. 4452-4461 ◽  
Author(s):  
Sue-Hyun Lee ◽  
Dwight J Kravitz ◽  
Chris I Baker
Keyword(s):  
Visual Cortex ◽  
Visual Information ◽  
Response Patterns ◽  
Object Representations ◽  
Object Identity ◽  
Retrieval Process ◽  
Ultra High Field ◽  
Neural Populations ◽  
High Level ◽  
Cortical Representations

Abstract Memory retrieval is thought to depend on interactions between hippocampus and cortex, but the nature of representation in these regions and their relationship remains unclear. Here, we performed an ultra-high field fMRI (7T) experiment, comprising perception, learning and retrieval sessions. We observed a fundamental difference between representations in hippocampus and high-level visual cortex during perception and retrieval. First, while object-selective posterior fusiform cortex showed consistent responses that allowed us to decode object identity across both perception and retrieval one day after learning, object decoding in hippocampus was much stronger during retrieval than perception. Second, in visual cortex but not hippocampus, there was consistency in response patterns between perception and retrieval, suggesting that substantial neural populations are shared for both perception and retrieval. Finally, the decoding in hippocampus during retrieval was not observed when retrieval was tested on the same day as learning suggesting that the retrieval process itself is not sufficient to elicit decodable object representations. Collectively, these findings suggest that while cortical representations are stable between perception and retrieval, hippocampal representations are much stronger during retrieval, implying some form of reorganization of the representations between perception and retrieval.

scholarly journals Shape-independent object category responses revealed by MEG and fMRI decoding

2016 ◽  
Vol 115 (4) ◽  
pp. 2246-2250 ◽  
Author(s):  
Daniel Kaiser ◽  
Damiano C. Azzalini ◽  
Marius V. Peelen
Keyword(s):  
Visual Cortex ◽  
Activity Patterns ◽  
Stimulus Onset ◽  
The Body ◽  
The Other ◽  
Response Patterns ◽  
Body Parts ◽  
Object Category ◽  
High Level ◽  
Large Clusters

Neuroimaging research has identified category-specific neural response patterns to a limited set of object categories. For example, faces, bodies, and scenes evoke activity patterns in visual cortex that are uniquely traceable in space and time. It is currently debated whether these apparently categorical responses truly reflect selectivity for categories or instead reflect selectivity for category-associated shape properties. In the present study, we used a cross-classification approach on functional MRI (fMRI) and magnetoencephalographic (MEG) data to reveal both category-independent shape responses and shape-independent category responses. Participants viewed human body parts (hands and torsos) and pieces of clothing that were closely shape-matched to the body parts (gloves and shirts). Category-independent shape responses were revealed by training multivariate classifiers on discriminating shape within one category (e.g., hands versus torsos) and testing these classifiers on discriminating shape within the other category (e.g., gloves versus shirts). This analysis revealed significant decoding in large clusters in visual cortex (fMRI) starting from 90 ms after stimulus onset (MEG). Shape-independent category responses were revealed by training classifiers on discriminating object category (bodies and clothes) within one shape (e.g., hands versus gloves) and testing these classifiers on discriminating category within the other shape (e.g., torsos versus shirts). This analysis revealed significant decoding in bilateral occipitotemporal cortex (fMRI) and from 130 to 200 ms after stimulus onset (MEG). Together, these findings provide evidence for concurrent shape and category selectivity in high-level visual cortex, including category-level responses that are not fully explicable by two-dimensional shape properties.

scholarly journals Coherent natural scene structure facilitates the extraction of task-relevant object information in visual cortex

2020 ◽  
Author(s):  
Daniel Kaiser ◽  
Greta Häberle ◽  
Radoslaw M. Cichy
Keyword(s):  
Visual Cortex ◽  
Rural Environment ◽  
Natural Scenes ◽  
Natural Environments ◽  
Response Patterns ◽  
Scene Structure ◽  
Processing Pathways ◽  
Typical Composition ◽  
High Level ◽  
The Brain

AbstractLooking for objects within complex natural environments is a task everybody performs multiple times each day. In this study, we explore how the brain uses the typical composition of real-world environments to efficiently solve this task. We recorded fMRI activity while participants performed two different categorization tasks on natural scenes. In the object task, they indicated whether the scene contained a person or a car, while in the scene task, they indicated whether the scene depicted an urban or a rural environment. Critically, each scene was presented in an “intact” way, preserving its coherent structure, or in a “jumbled” way, with information swapped across quadrants. In both tasks, participants’ categorization was more accurate and faster for intact scenes. These behavioral benefits were accompanied by stronger responses to intact than to jumbled scenes across high-level visual cortex. To track the amount of object information in visual cortex, we correlated multivoxel response patterns during the two categorization tasks with response patterns evoked by people and cars in isolation. We found that object information in object- and body-selective cortex was enhanced when the object was embedded in an intact, rather than a jumbled scene. However, this enhancement was only found in the object task: When participants instead categorized the scenes, object information did not differ between intact and jumbled scenes. Together, these results indicate that coherent scene structure facilitates the extraction of object information in a task-dependent way, suggesting that interactions between the object and scene processing pathways adaptively support behavioral goals.

scholarly journals Metabolic Activity Patterns in the Monkey Visual Cortex as Revealed by Spectral Analysis

1999 ◽  
Vol 19 (4) ◽  
pp. 401-416 ◽  
Author(s):  
Yannis Dalezios ◽  
Georgia G. Gregoriou ◽  
Helen E. Savaki
Keyword(s):  
Spectral Analysis ◽  
Visual Cortex ◽  
Metabolic Activity ◽  
Activity Patterns ◽  
Spatial Arrangement ◽  
Spectral Amplitude ◽  
Two Dimensional ◽  
Reaching Task ◽  
Area V2 ◽  
Monkey Visual Cortex

The metabolic activity pattern of the monkey visual cortex was mapped quantitatively with [14C]-2-deoxyglucose during the performance of a visually guided reaching task. After bandpass filtering of the reconstructed two-dimensional metabolic maps of areas V1 and V2, alternating bands of high and low metabolic activity were apparent in control and experimental hemispheres. The spatial arrangement of active bands was studied with two-dimensional spectral analysis, and bands were found to be more organized in the experimental monkey. In area V1 of the control monkey the spectral amplitude was spread over a wider range of directions and frequencies than in the experimental subject. The finding that layer IV is characterized by more complex spectra than layers I through III suggests the coexistence of more than one active columnar system in the geniculorecipient layer. In area V2, stripes running almost perpendicular to the V1/V2 border were found along with superimposed patches of enhanced metabolic activity. In the experimental hemispheres, the corresponding spectra were extremely sharp yielding a constant periodicity. It is suggested that the well-organized columnar arrangement within areas V1 and V2 of the experimental hemispheres emerges from the diffusely organized background network of activity patterns in the control state.

scholarly journals Superimposed gratings induce diverse response patterns of gamma oscillations in primary visual cortex

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Bin Wang ◽  
Chuanliang Han ◽  
Tian Wang ◽  
Weifeng Dai ◽  
Yang Li ◽  
...  
Keyword(s):  
Visual Cortex ◽  
Primary Visual Cortex ◽  
Field Potential ◽  
Gamma Oscillations ◽  
Neural Mechanisms ◽  
Model Parameters ◽  
Response Patterns ◽  
Region Difference ◽  
High Gamma ◽  
Spiking Activity

AbstractStimulus-dependence of gamma oscillations (GAMMA, 30–90 Hz) has not been fully understood, but it is important for revealing neural mechanisms and functions of GAMMA. Here, we recorded spiking activity (MUA) and the local field potential (LFP), driven by a variety of plaids (generated by two superimposed gratings orthogonal to each other and with different contrast combinations), in the primary visual cortex of anesthetized cats. We found two distinct narrow-band GAMMAs in the LFPs and a variety of response patterns to plaids. Similar to MUA, most response patterns showed that the second grating suppressed GAMMAs driven by the first one. However, there is only a weak site-by-site correlation between cross-orientation interactions in GAMMAs and those in MUAs. We developed a normalization model that could unify the response patterns of both GAMMAs and MUAs. Interestingly, compared with MUAs, the GAMMAs demonstrated a wider range of model parameters and more diverse response patterns to plaids. Further analysis revealed that normalization parameters for high GAMMA, but not those for low GAMMA, were significantly correlated with the discrepancy of spatial frequency between stimulus and sites’ preferences. Consistent with these findings, normalization parameters and diversity of high GAMMA exhibited a clear transition trend and region difference between area 17 to 18. Our results show that GAMMAs are also regulated in the form of normalization, but that the neural mechanisms for these normalizations might differ from those of spiking activity. Normalizations in different brain signals could be due to interactions of excitation and inhibitions at multiple stages in the visual system.

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