Importance of the early visual cortex and the lateral occipito-temporal cortex for the self-hand specific perspective process

Theories of visual selective attention propose that top–down preparatory attention signals mediate the selection of task-relevant information in cluttered scenes. Neuroimaging and electrophysiology studies have provided correlative evidence for this hypothesis, finding increased activity in target-selective neural populations in visual cortex in the period between a search cue and target onset. In this study, we used online TMS to test whether preparatory neural activity in visual cortex is causally involved in naturalistic object detection. In two experiments, participants detected the presence of object categories (cars, people) in a diverse set of photographs of real-world scenes. TMS was applied over a region in posterior temporal cortex identified by fMRI as carrying category-specific preparatory activity patterns. Results showed that TMS applied over posterior temporal cortex before scene onset (−200 and −100 msec) impaired the detection of object categories in subsequently presented scenes, relative to vertex and early visual cortex stimulation. This effect was specific to category level detection and was related to the type of attentional template participants adopted, with the strongest effects observed in participants adopting category level templates. These results provide evidence for a causal role of preparatory attention in mediating the detection of objects in cluttered daily-life environments.

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Attending to What and Where: Background Connectivity Integrates Categorical and Spatial Attention

Journal of Cognitive Neuroscience ◽

10.1162/jocn_a_01284 ◽

2018 ◽

Vol 30 (9) ◽

pp. 1281-1297 ◽

Cited By ~ 8

Author(s):

Alexa Tompary ◽

Naseem Al-Aidroos ◽

Nicholas B. Turk-Browne

Keyword(s):

Visual Cortex ◽

Spatial Attention ◽

Temporal Cortex ◽

Relevant Information ◽

Neural Basis ◽

Attentional Modulation ◽

Temporal Correlations ◽

Visual Areas ◽

Early Visual Cortex ◽

Ventral Temporal Cortex

Top–down attention prioritizes the processing of goal-relevant information throughout visual cortex based on where that information is found in space and what it looks like. Whereas attentional goals often have both spatial and featural components, most research on the neural basis of attention has examined these components separately. Here we investigated how these attentional components are integrated by examining the attentional modulation of functional connectivity between visual areas with different selectivity. Specifically, we used fMRI to measure temporal correlations between spatially selective regions of early visual cortex and category-selective regions in ventral temporal cortex while participants performed a task that benefitted from both spatial and categorical attention. We found that categorical attention modulated the connectivity of category-selective areas, but only with retinotopic areas that coded for the spatially attended location. Similarly, spatial attention modulated the connectivity of retinotopic areas only with the areas coding for the attended category. This pattern of results suggests that attentional modulation of connectivity is driven both by spatial selection and featural biases. Combined with exploratory analyses of frontoparietal areas that track these changes in connectivity among visual areas, this study begins to shed light on how different components of attention are integrated in support of more complex behavioral goals.

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Perceptual Learning of Simple Stimuli Modifies Stimulus Representations in Posterior Inferior Temporal Cortex

Journal of Cognitive Neuroscience ◽

10.1162/jocn_a_00641 ◽

2014 ◽

Vol 26 (10) ◽

pp. 2187-2200 ◽

Cited By ~ 16

Author(s):

Hamed Zivari Adab ◽

Ivo D. Popivanov ◽

Wim Vanduffel ◽

Rufin Vogels

Keyword(s):

Visual Cortex ◽

Perceptual Learning ◽

Single Unit ◽

Brain Plasticity ◽

Temporal Cortex ◽

Adult Brain ◽

Orientation Discrimination ◽

Area V4 ◽

Early Visual Cortex ◽

Visual Cortical

Practicing simple visual detection and discrimination tasks improves performance, a signature of adult brain plasticity. The neural mechanisms that underlie these changes in performance are still unclear. Previously, we reported that practice in discriminating the orientation of noisy gratings (coarse orientation discrimination) increased the ability of single neurons in the early visual area V4 to discriminate the trained stimuli. Here, we ask whether practice in this task also changes the stimulus tuning properties of later visual cortical areas, despite the use of simple grating stimuli. To identify candidate areas, we used fMRI to map activations to noisy gratings in trained rhesus monkeys, revealing a region in the posterior inferior temporal (PIT) cortex. Subsequent single unit recordings in PIT showed that the degree of orientation selectivity was similar to that of area V4 and that the PIT neurons discriminated the trained orientations better than the untrained orientations. Unlike in previous single unit studies of perceptual learning in early visual cortex, more PIT neurons preferred trained compared with untrained orientations. The effects of training on the responses to the grating stimuli were also present when the animals were performing a difficult orthogonal task in which the grating stimuli were task-irrelevant, suggesting that the training effect does not need attention to be expressed. The PIT neurons could support orientation discrimination at low signal-to-noise levels. These findings suggest that extensive practice in discriminating simple grating stimuli not only affects early visual cortex but also changes the stimulus tuning of a late visual cortical area.

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Attending to what and where: Background connectivity integrates categorical and spatial attention

10.1101/199190 ◽

2017 ◽

Cited By ~ 1

Author(s):

Alexa Tompary ◽

Naseem Al-Aidroos ◽

Nicholas B. Turk-Browne

Keyword(s):

Visual Cortex ◽

Spatial Attention ◽

Temporal Cortex ◽

Relevant Information ◽

Neural Basis ◽

Attentional Modulation ◽

Temporal Correlations ◽

Visual Areas ◽

Early Visual Cortex ◽

Ventral Temporal Cortex

AbstractTop-down attention prioritizes the processing of goal-relevant information throughout visual cortex, based on where that information is found in space and what it looks like. Whereas attentional goals often have both spatial and featural components, most research on the neural basis of attention has examined these components separately. This may reflect the fact that attention is typically studied in individual visual areas that preferentially code for either spatial locations or particular features. Here we investigated how these attentional components are integrated by examining the attentional modulation of functional connectivity between visual areas with different selectivity. Specifically, we used fMRI to measure temporal correlations between spatially-selective regions of early visual cortex and category-selective regions in ventral temporal cortex while participants performed a task that benefitted from both spatial and categorical attention. We found that categorical attention modulated the connectivity of category-selective areas, but only with retinotopic areas that coded for the spatially attended location. The reverse was not true, however, with spatial attention modulating the connectivity of retinotopic areas with category-selective areas coding for both attended and unattended features. This pattern of results suggests that attentional modulation of connectivity is dominated by spatial selection, which in turn gates featural biases. Combined with exploratory analyses of frontoparietal areas that track these changes in connectivity among visual areas, this study begins to shed light on how different components of attention are integrated in support of more complex behavioral goals.

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Feature-coding transitions to conjunction-coding with progression through human visual cortex

Journal of Neurophysiology ◽

10.1152/jn.00503.2017 ◽

2017 ◽

Vol 118 (6) ◽

pp. 3194-3214 ◽

Cited By ~ 3

Author(s):

Rosemary A. Cowell ◽

Krystal R. Leger ◽

John T. Serences

Keyword(s):

Visual Cortex ◽

Visual Processing ◽

Temporal Cortex ◽

Complex Stimulus ◽

Imaging Data ◽

Neuronal Responses ◽

Human Visual Cortex ◽

Early Visual Cortex ◽

Parietal Cortices ◽

Object Level

Identifying an object and distinguishing it from similar items depends upon the ability to perceive its component parts as conjoined into a cohesive whole, but the brain mechanisms underlying this ability remain elusive. The ventral visual processing pathway in primates is organized hierarchically: Neuronal responses in early stages are sensitive to the manipulation of simple visual features, whereas neuronal responses in subsequent stages are tuned to increasingly complex stimulus attributes. It is widely assumed that feature-coding dominates in early visual cortex whereas later visual regions employ conjunction-coding in which object representations are different from the sum of their simple feature parts. However, no study in humans has demonstrated that putative object-level codes in higher visual cortex cannot be accounted for by feature-coding and that putative feature codes in regions prior to ventral temporal cortex are not equally well characterized as object-level codes. Thus the existence of a transition from feature- to conjunction-coding in human visual cortex remains unconfirmed, and if a transition does occur its location remains unknown. By employing multivariate analysis of functional imaging data, we measure both feature-coding and conjunction-coding directly, using the same set of visual stimuli, and pit them against each other to reveal the relative dominance of one vs. the other throughout cortex. Our results reveal a transition from feature-coding in early visual cortex to conjunction-coding in both inferior temporal and posterior parietal cortices. This novel method enables the use of experimentally controlled stimulus features to investigate population-level feature and conjunction codes throughout human cortex. NEW & NOTEWORTHY We use a novel analysis of neuroimaging data to assess representations throughout visual cortex, revealing a transition from feature-coding to conjunction-coding along both ventral and dorsal pathways. Occipital cortex contains more information about spatial frequency and contour than about conjunctions of those features, whereas inferotemporal and parietal cortices contain conjunction coding sites in which there is more information about the whole stimulus than its component parts.

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fMRI Activity Patterns in Human LOC Carry Information about Object Exemplars within Category

Journal of Cognitive Neuroscience ◽

10.1162/jocn.2008.20019 ◽

2008 ◽

Vol 20 (2) ◽

pp. 356-370 ◽

Cited By ~ 117

Author(s):

Evelyn Eger ◽

John Ashburner ◽

John-Dylan Haynes ◽

Raymond J. Dolan ◽

Geraint Rees

Keyword(s):

Pattern Recognition ◽

Visual Cortex ◽

Activity Patterns ◽

Temporal Cortex ◽

Support Vector ◽

Specific Information ◽

Object Identity ◽

Stimulus Similarity ◽

Lateral Occipital Complex ◽

Early Visual Cortex

The lateral occipital complex (LOC) is a set of areas in the human occipito-temporal cortex responding to objects as opposed to low-level control stimuli. Conventional functional magnetic resonance imaging (fMRI) analysis methods based on regional averages could not detect signals discriminative of different types of objects in this region. Here, we examined fMRI signals using multivariate pattern recognition (support vector classification) to systematically explore the nature of object-related information available in fine-grained activity patterns in the LOC. Distributed fMRI signals from the LOC allowed for above-chance discrimination not only of the category but also of within-category exemplars of everyday man-made objects, and such exemplar-specific information generalized across changes in stimulus size and viewpoint, particularly in posterior subregions. Object identity could also be predicted from responses of the early visual cortex, even significantly across the changes in size and viewpoint used here. However, a dissociation was observed between these two regions of interest in the degree of discrimination for objects relative to size: In the early visual cortex, two different sizes of the same object were even better discriminated than two different objects (in accordance with measures of pixelwise stimulus similarity), whereas the opposite was true in the LOC. These findings provide the first evidence that direct evoked fMRI activity patterns in the LOC can be different for individual object exemplars (within a single category). We propose that pattern recognition methods as used here may provide an alternative approach to study mechanisms of neuronal representation based on aspects of the fMRI response independent of those assessed in adaptation paradigms.

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A Dynamic Causal Modeling Study on Category Effects: Bottom–Up or Top–Down Mediation?

Journal of Cognitive Neuroscience ◽

10.1162/089892903770007317 ◽

2003 ◽

Vol 15 (7) ◽

pp. 925-934 ◽

Cited By ~ 103

Author(s):

Andrea Mechelli ◽

Cathy J. Price ◽

Uta Noppeney ◽

Karl J. Friston

Keyword(s):

Visual Cortex ◽

Brain Connectivity ◽

Temporal Cortex ◽

Causal Modeling ◽

Equation Modeling ◽

Category Specificity ◽

Dynamic Causal Modeling ◽

Bottom Up ◽

Early Visual Cortex ◽

Category Effects

In this study, we combined functional magnetic resonance imaging (fMRI) and dynamic causal modeling (DCM) to investigate whether object category effects in the occipital and temporal cortex are mediated by inputs from early visual cortex or parietal regions. Resolving this issue may provide anatomical constraints on theories of category specificity— which make different assumptions about the underlying neurophysiology. The data were acquired by Ishai, Ungerleider, Martin, Schouten, and Haxby (1999, 2000) and provided by the National fMRI Data Center (http://www.fmridc.org). The original authors used a conventional analysis to estimate differential effects in the occipital and temporal cortex in response to pictures of chairs, faces, and houses. We extended this approach by estimating neuronal interactions that mediate category effects using DCM. DCM uses a Bayesian framework to estimate and make inferences about the influence that one region exerts over another and how this is affected by experimental changes. DCM differs from previous approaches to brain connectivity, such as multivariate autoregressive models and structural equation modeling, as it assumes that the observed hemodynamic responses are driven by experimental changes rather than endogenous noise. DCM therefore brings the analysis of brain connectivity much closer to the analysis of regionally specific effects usually applied to functional imaging data. We used DCM to estimate the influence that V3 and the superior/inferior parietal cortex exerted over category-responsive regions and how this was affected by the presentation of houses, faces, and chairs. We found that category effects in occipital and temporal cortex were mediated by inputs from early visual cortex. In contrast, the connectivity from the superior/inferior parietal area to the category-responsive areas was unaffected by the presentation of chairs, faces, or houses. These findings indicate that category effects in the occipital and temporal cortex can be mediated by bottom–up mechanisms—a finding that needs to be embraced by models of category specificity.

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A Self-Supervised Deep Neural Network for Image Completion Resembles Early Visual Cortex fMRI Activity Patterns for Occluded Scenes

10.1101/2020.03.24.005132 ◽

2020 ◽

Author(s):

Michele Svanera ◽

Andrew T Morgan ◽

Lucy S Petro ◽

Lars Muckli

Keyword(s):

Information Processing ◽

Visual Cortex ◽

Visual Information ◽

Computational Models ◽

Temporal Cortex ◽

Fmri Data ◽

Image Completion ◽

Hierarchical Processing ◽

Early Visual Cortex ◽

Brain Data

The promise of artificial intelligence in understanding biological vision relies on the comparison of computational models with brain data with the goal of capturing functional principles of visual information processing. Convolutional neural networks (CNN) have successfully matched the transformations in hierarchical processing occurring along the brain's feedforward visual pathway extending into ventral temporal cortex. However, we are still to learn if CNNs can successfully describe feedback processes in early visual cortex. Here, we investigated similarities between human early visual cortex and a CNN with encoder/decoder architecture, trained with self-supervised learning to fill occlusions and reconstruct an unseen image. Using Representational Similarity Analysis (RSA), we compared 3T fMRI data from a non-stimulated patch of early visual cortex in human participants viewing partially occluded images, with the different CNN layer activations from the same images. Results show that our self-supervised image-completion network outperforms a classical object-recognition supervised network (VGG16) in terms of similarity to fMRI data. This provides additional evidence that optimal models of the visual system might come from less feedforward architectures trained with less supervision. We also find that CNN decoder pathway activations are more similar to brain processing compared to encoder activations, suggesting an integration of mid- and low/middle-level features in early visual cortex. Challenging an AI model and the human brain to solve the same task offers a valuable way to compare CNNs with brain data and helps to constrain our understanding of information processing such as neuronal predictive coding.

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Representation of Color, Form, and their Conjunction across the Human Ventral Visual Pathway

10.1101/2020.08.28.272815 ◽

2020 ◽

Author(s):

JohnMark Taylor ◽

Yaoda Xu

Keyword(s):

Visual Cortex ◽

Temporal Cortex ◽

Visual Pathway ◽

Significant Feature ◽

Form Processing ◽

Neuroscience Research ◽

Ventral Visual Pathway ◽

Early Visual Cortex ◽

Form Feature ◽

Interactive Coding

AbstractDespite decades of neuroscience research, our understanding of the relationship between color and form processing in the primate ventral visual pathway remains incomplete. Using fMRI multivoxel pattern analysis, this study examined the coding of color with both a simple form feature (orientation) and a mid-level form feature (curvature) in human early visual areas V1 to V4, posterior and central color regions, and shape areas in ventral and lateral occipito-temporal cortex. With the exception of the central color region (which showed color but not form decoding), successful color and form decoding was found in all other regions examined, even for color and shape regions showing univariate sensitivity to one feature. That said, all regions exhibited significant feature decoding biases, with decoding from color and shape regions largely consistent with their univariate preferences. Color and form are thus represented in neither a completely distributed nor a completely modular manner, but a biased distributed manner. Interestingly, coding of one feature in a brain region was always tolerant to changes in the other feature, indicating relative independence of color and form coding throughout the ventral visual cortex. Although evidence for interactive coding of color and form also existed, the effect was weak and only existed for color and orientation conjunctions in early visual cortex. No evidence for interactive coding of color and curvature was found. The predominant relationship between color and form coding in the human brain appears to be one of anatomical coexistence (in a biased distributed manner), but representational independence.

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Feature-coding transitions to conjunction-coding with progression through human visual cortex

10.1101/085381 ◽

2016 ◽

Author(s):

Rosemary A. Cowell ◽

John T. Serences

Keyword(s):

Visual Cortex ◽

Visual Processing ◽

Temporal Cortex ◽

Population Level ◽

Complex Stimulus ◽

Imaging Data ◽

Neuronal Responses ◽

Early Visual Cortex ◽

Stimulus Features ◽

Object Level

Identifying an object and distinguishing it from similar items depends upon the ability to perceive its component parts as conjoined into a cohesive whole, but the brain mechanisms underlying this ability remain elusive. The ventral visual processing pathway in primates is organized hierarchically: Neuronal responses in its early stages are sensitive to the manipulation of simple visual features whereas neuronal responses in subsequent stages are tuned to increasingly complex stimulus attributes. It is widely assumed that feature-coding dominates in early visual cortex whereas later visual regions employ conjunction-coding in which object representations are different from the sum of their simple-feature parts. However, no study has demonstrated that putative object-level codes in higher visual cortex cannot be accounted for by feature-coding and that putative feature-codes in regions prior to ventral temporal cortex are not equally well characterized as object-level codes. Thus the existence of a transition from feature- to conjunction-coding in visual cortex remains unconfirmed, and, if a transition does occur, its location remains unknown. By employing multivariate analysis of human functional imaging data, we measure both feature-coding and conjunction-coding directly, using the same set of visual stimuli, and pit them against each other to reveal the relative dominance of one versus the other throughout cortex. We provide the first demonstration of a transition from feature-coding in early visual cortex to conjunction-coding in both inferior temporal and posterior parietal cortices. This novel method enables the use of experimentally controlled stimulus features to investigate population-level feature- and conjunction-codes throughout human cortex.

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