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Kay K, Bonnen K, Denison RN, Arcaro MJ, Barack DL. Tasks and their role in visual neuroscience. Neuron 2023; 111:1697-1713. [PMID: 37040765 DOI: 10.1016/j.neuron.2023.03.022] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Revised: 03/13/2023] [Accepted: 03/15/2023] [Indexed: 04/13/2023]
Abstract
Vision is widely used as a model system to gain insights into how sensory inputs are processed and interpreted by the brain. Historically, careful quantification and control of visual stimuli have served as the backbone of visual neuroscience. There has been less emphasis, however, on how an observer's task influences the processing of sensory inputs. Motivated by diverse observations of task-dependent activity in the visual system, we propose a framework for thinking about tasks, their role in sensory processing, and how we might formally incorporate tasks into our models of vision.
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Affiliation(s)
- Kendrick Kay
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, USA.
| | - Kathryn Bonnen
- School of Optometry, Indiana University, Bloomington, IN 47405, USA
| | - Rachel N Denison
- Department of Psychological and Brain Sciences, Boston University, Boston, MA 02215, USA
| | - Mike J Arcaro
- Department of Psychology, University of Pennsylvania, Philadelphia, PA 19146, USA
| | - David L Barack
- Departments of Neuroscience and Philosophy, University of Pennsylvania, Philadelphia, PA 19146, USA
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2
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Grasso PA, Petrizzo I, Caponi C, Anobile G, Arrighi R. Visual P2p component responds to perceived numerosity. Front Hum Neurosci 2022; 16:1014703. [DOI: 10.3389/fnhum.2022.1014703] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 10/13/2022] [Indexed: 11/05/2022] Open
Abstract
Numerosity perception is a key ability for human and non-human species, probably mediated by dedicated brain mechanisms. Electrophysiological studies revealed the existence of both early and mid-latency components of the Electrophysiological (EEG) signal sensitive to numerosity changes. However, it is still unknown whether these components respond to physical or perceived variation in numerical attributes. We here tackled this point by recording electrophysiological signal while participants performed a numerosity adaptation task, a robust psychophysical method yielding changes in perceived numerosity judgments despite physical numerosity invariance. Behavioral measures confirmed that the test stimulus was consistently underestimated when presented after a high numerous adaptor while perceived as veridical when presented after a neutral adaptor. Congruently, EEG results revealed a potential at around 200 ms (P2p) which was reduced when the test stimulus was presented after the high numerous adaptor. This result was much prominent over the left posterior cluster of electrodes and correlated significantly with the amount of adaptation. No earlier modulations were retrievable when changes in numerosity were illusory while both early and mid-latency modulations occurred for physical changes. Taken together, our results reveal that mid-latency P2p mainly reflects perceived changes in numerical attributes, while earlier components are likely to be bounded to the physical characteristics of the stimuli. These results suggest that short-term plastic mechanisms induced by numerosity adaptation may involve a relatively late processing stage of the visual hierarchy likely engaging cortical areas beyond the primary visual cortex. Furthermore, these results also indicate mid-latency electrophysiological correlates as a signature of the internal representation of numerical information.
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Han C, Wang T, Yang Y, Wu Y, Li Y, Dai W, Zhang Y, Wang B, Yang G, Cao Z, Kang J, Wang G, Li L, Yu H, Yeh CI, Xing D. Multiple gamma rhythms carry distinct spatial frequency information in primary visual cortex. PLoS Biol 2021; 19:e3001466. [PMID: 34932558 PMCID: PMC8691622 DOI: 10.1371/journal.pbio.3001466] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Accepted: 11/03/2021] [Indexed: 12/26/2022] Open
Abstract
Gamma rhythms in many brain regions, including the primary visual cortex (V1), are thought to play a role in information processing. Here, we report a surprising finding of 3 narrowband gamma rhythms in V1 that processed distinct spatial frequency (SF) signals and had different neural origins. The low gamma (LG; 25 to 40 Hz) rhythm was generated at the V1 superficial layer and preferred a higher SF compared with spike activity, whereas both the medium gamma (MG; 40 to 65 Hz), generated at the cortical level, and the high gamma HG; (65 to 85 Hz), originated precortically, preferred lower SF information. Furthermore, compared with the rates of spike activity, the powers of the 3 gammas had better performance in discriminating the edge and surface of simple objects. These findings suggest that gamma rhythms reflect the neural dynamics of neural circuitries that process different SF information in the visual system, which may be crucial for multiplexing SF information and synchronizing different features of an object.
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Affiliation(s)
- Chuanliang Han
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Tian Wang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Yi Yang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Yujie Wu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Yang Li
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Weifeng Dai
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Yange Zhang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Bin Wang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Guanzhong Yang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Ziqi Cao
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Jian Kang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
| | - Gang Wang
- Beijing Institute of Basic Medical Sciences, Beijing, China
| | - Liang Li
- Beijing Institute of Basic Medical Sciences, Beijing, China
| | - Hongbo Yu
- Vision Research Laboratory, Center for Brain Science Research and School of Life Sciences, Fudan University, Shanghai, China
| | - Chun-I Yeh
- Department of Psychology, National Taiwan University, Taipei, Taiwan, China
| | - Dajun Xing
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China
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4
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Jigo M, Heeger DJ, Carrasco M. An image-computable model of how endogenous and exogenous attention differentially alter visual perception. Proc Natl Acad Sci U S A 2021; 118:e2106436118. [PMID: 34389680 PMCID: PMC8379934 DOI: 10.1073/pnas.2106436118] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Attention alters perception across the visual field. Typically, endogenous (voluntary) and exogenous (involuntary) attention similarly improve performance in many visual tasks, but they have differential effects in some tasks. Extant models of visual attention assume that the effects of these two types of attention are identical and consequently do not explain differences between them. Here, we develop a model of spatial resolution and attention that distinguishes between endogenous and exogenous attention. We focus on texture-based segmentation as a model system because it has revealed a clear dissociation between both attention types. For a texture for which performance peaks at parafoveal locations, endogenous attention improves performance across eccentricity, whereas exogenous attention improves performance where the resolution is low (peripheral locations) but impairs it where the resolution is high (foveal locations) for the scale of the texture. Our model emulates sensory encoding to segment figures from their background and predict behavioral performance. To explain attentional effects, endogenous and exogenous attention require separate operating regimes across visual detail (spatial frequency). Our model reproduces behavioral performance across several experiments and simultaneously resolves three unexplained phenomena: 1) the parafoveal advantage in segmentation, 2) the uniform improvements across eccentricity by endogenous attention, and 3) the peripheral improvements and foveal impairments by exogenous attention. Overall, we unveil a computational dissociation between each attention type and provide a generalizable framework for predicting their effects on perception across the visual field.
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Affiliation(s)
- Michael Jigo
- Center for Neural Science, New York University, New York, NY 10003;
| | - David J Heeger
- Center for Neural Science, New York University, New York, NY 10003
- Department of Psychology, New York University, New York, NY 10003
| | - Marisa Carrasco
- Center for Neural Science, New York University, New York, NY 10003
- Department of Psychology, New York University, New York, NY 10003
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5
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Abstract
Selectivity for many basic properties of visual stimuli, such as orientation, is thought to be organized at the scale of cortical columns, making it difficult or impossible to measure directly with noninvasive human neuroscience measurement. However, computational analyses of neuroimaging data have shown that selectivity for orientation can be recovered by considering the pattern of response across a region of cortex. This suggests that computational analyses can reveal representation encoded at a finer spatial scale than is implied by the spatial resolution limits of measurement techniques. This potentially opens up the possibility to study a much wider range of neural phenomena that are otherwise inaccessible through noninvasive measurement. However, as we review in this article, a large body of evidence suggests an alternative hypothesis to this superresolution account: that orientation information is available at the spatial scale of cortical maps and thus easily measurable at the spatial resolution of standard techniques. In fact, a population model shows that this orientation information need not even come from single-unit selectivity for orientation tuning, but instead can result from population selectivity for spatial frequency. Thus, a categorical error of interpretation can result whereby orientation selectivity can be confused with spatial frequency selectivity. This is similarly problematic for the interpretation of results from numerous studies of more complex representations and cognitive functions that have built upon the computational techniques used to reveal stimulus orientation. We suggest in this review that these interpretational ambiguities can be avoided by treating computational analyses as models of the neural processes that give rise to measurement. Building upon the modeling tradition in vision science using considerations of whether population models meet a set of core criteria is important for creating the foundation for a cumulative and replicable approach to making valid inferences from human neuroscience measurements. Expected final online publication date for the Annual Review of Vision Science, Volume 7 is September 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
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Affiliation(s)
- Justin L Gardner
- Department of Psychology, Stanford University, Stanford, California 94305, USA;
| | - Elisha P Merriam
- Laboratory of Brain and Cognition, National Institute of Mental Health, National Institutes of Health, Bethesda, Maryland 20892, USA;
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Dong X, Dong J, Chantler MJ. Perceptual Texture Similarity Estimation: An Evaluation of Computational Features. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 2021; 43:2429-2448. [PMID: 31944946 DOI: 10.1109/tpami.2020.2964533] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Estimation of texture similarity is fundamental to many material recognition tasks. This study uses fine-grained human perceptual similarity ground-truth to provide a comprehensive evaluation of 51 texture feature sets. We conduct two types of evaluation and both show that these features do not estimate similarity well when compared against human agreement rates, but that performances are improved when the features are combined using a Random Forest. Using a simple two-stage statistical model we show that few of the features capture long-range aperiodic relationships. We perform two psychophysical experiments which indicate that long-range interactions do provide humans with important cues for estimating texture similarity. This motivates an extension of the study to include Convolutional Neural Networks (CNNs) as they enable arbitrary features of large spatial extent to be learnt. Our conclusions derived from the use of two pre-trained CNNs are: that the large spatial extent exploited by the networks' top convolutional and first fully-connected layers, together with the use of large numbers of filters, confers significant advantage for estimation of perceptual texture similarity.
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7
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Resolving the Spatial Profile of Figure Enhancement in Human V1 through Population Receptive Field Modeling. J Neurosci 2020; 40:3292-3303. [PMID: 32139585 DOI: 10.1523/jneurosci.2377-19.2020] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2019] [Revised: 02/18/2020] [Accepted: 02/20/2020] [Indexed: 11/21/2022] Open
Abstract
The detection and segmentation of meaningful figures from their background is one of the primary functions of vision. While work in nonhuman primates has implicated early visual mechanisms in this figure-ground modulation, neuroimaging in humans has instead largely ascribed the processing of figures and objects to higher stages of the visual hierarchy. Here, we used high-field fMRI at 7 Tesla to measure BOLD responses to task-irrelevant orientation-defined figures in human early visual cortex (N = 6, four females). We used a novel population receptive field mapping-based approach to resolve the spatial profiles of two constituent mechanisms of figure-ground modulation: a local boundary response, and a further enhancement spanning the full extent of the figure region that is driven by global differences in features. Reconstructing the distinct spatial profiles of these effects reveals that figure enhancement modulates responses in human early visual cortex in a manner consistent with a mechanism of automatic, contextually driven feedback from higher visual areas.SIGNIFICANCE STATEMENT A core function of the visual system is to parse complex 2D input into meaningful figures. We do so constantly and seamlessly, both by processing information about visible edges and by analyzing large-scale differences between figure and background. While influential neurophysiology work has characterized an intriguing mechanism that enhances V1 responses to perceptual figures, we have a poor understanding of how the early visual system contributes to figure-ground processing in humans. Here, we use advanced computational analysis methods and high-field human fMRI data to resolve the distinct spatial profiles of local edge and global figure enhancement in the early visual system (V1 and LGN); the latter is distinct and consistent with a mechanism of automatic, stimulus-driven feedback from higher-level visual areas.
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8
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Second-order visual sensitivity in the aging population. Aging Clin Exp Res 2019; 31:705-716. [PMID: 30168100 DOI: 10.1007/s40520-018-1018-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2018] [Accepted: 07/31/2018] [Indexed: 10/28/2022]
Abstract
Most visual and cognitive functions are affected by aging over the lifespan. In this study, our aim was to investigate the loss in sensitivity to different classes of second-order stimuli-a class of stimuli supposed to be mainly processed in extrastriate cortex-in the aging population. These stimuli will then allow one to identify specific cortical deficit independently of visibility losses in upstream parts of the visual pathway. For this purpose, we measured the sensitivity to first-order stimuli and second-order stimuli: orientation-modulated, motion-modulated or contrast-modulated as a function of spatial frequency in 50 aged participants. Overall, we observed a sensitivity loss for all classes of stimuli, but this loss differentially affects the three classes of second-order stimuli tested. It involves all modulation spatial frequencies in the case of motion modulation, but just high modulation spatial frequencies in the case of contrast- and orientation modulations. These observations imply that aging selectively affects the sensitivity to second-order stimuli depending on their type. Since there is evidence that these different second-order stimuli are processed in different regions of extrastriate cortex, this result may suggest that some visual cortical areas are more susceptible to aging effects than others.
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9
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Victor JD, Rizvi SM, Conte MM. Image segmentation driven by elements of form. Vision Res 2019; 159:21-34. [PMID: 30611696 DOI: 10.1016/j.visres.2018.12.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2018] [Revised: 11/30/2018] [Accepted: 12/04/2018] [Indexed: 11/27/2022]
Abstract
While luminance, contrast, orientation, and terminators are well-established features that are extracted in early visual processing and support the parsing of an image into its component regions, the role of more complex features, such as closure and convexity, is less clear. A main barrier in understanding the roles of such features is that manipulating their occurrence typically entails changes in the occurrence of more elementary features as well. To address this problem, we developed a set of synthetic visual textures, constructed by replacing the binary coloring of standard maximum-entropy textures with tokens (tiles) containing curved or angled elements. The tokens were designed so that there were no discontinuities at their edges, and so that changing the correlation structure of the underlying binary texture changed the shapes that were produced. The resulting textures were then used in psychophysical studies, demonstrating that the resulting feature differences sufficed to drive segmentation. However, in contrast to previous findings for lower-level features, sensitivities to increases and decreases of feature occurrence were unequal. Moreover, the texture-segregation response depended on the kind of token (curved vs. angular, filled-in vs. outlined), and not just on the correlation structure. Analysis of this dependence indicated that simple closed contours and convex elements suffice to drive image segmentation, in the absence of changes in lower-level cues.
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Affiliation(s)
- Jonathan D Victor
- Feil Family Brain and Mind Research Institute, Weill Cornell Medical College, 1300 York Avenue, New York, NY 10065, United States.
| | - Syed M Rizvi
- Feil Family Brain and Mind Research Institute, Weill Cornell Medical College, 1300 York Avenue, New York, NY 10065, United States
| | - Mary M Conte
- Feil Family Brain and Mind Research Institute, Weill Cornell Medical College, 1300 York Avenue, New York, NY 10065, United States
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10
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Abstract
Endogenous and exogenous visuospatial attention both alter spatial resolution, but they operate via distinct mechanisms. In texture segmentation tasks, exogenous attention inflexibly increases resolution even when detrimental for the task at hand and does so by modulating second-order processing. Endogenous attention is more flexible and modulates resolution to benefit performance according to task demands, but it is unknown whether it also operates at the second-order level. To answer this question, we measured performance on a second-order texture segmentation task while independently manipulating endogenous and exogenous attention. Observers discriminated a second-order texture target at several eccentricities. We found that endogenous attention improved performance uniformly across eccentricity, suggesting a flexible mechanism that can increase or decrease resolution based on task demands. In contrast, exogenous attention improved performance in the periphery but impaired it at central retinal locations, consistent with an inflexible resolution enhancement. Our results reveal that endogenous and exogenous attention both alter spatial resolution by differentially modulating second-order processing.
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Affiliation(s)
- Michael Jigo
- Center for Neural Science, New York University, New York, NY, USA
| | - Marisa Carrasco
- Center for Neural Science and Department of Psychology, New York University, New York, NY, USA
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11
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Phase-Dependent Interactions in Visual Cortex to Combinations of First- and Second-Order Stimuli. J Neurosci 2017; 36:12328-12337. [PMID: 27927953 DOI: 10.1523/jneurosci.1350-16.2016] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2016] [Revised: 10/07/2016] [Accepted: 10/11/2016] [Indexed: 11/21/2022] Open
Abstract
A fundamental task of the visual system is to extract figure-ground boundaries between objects, which are often defined, not only by differences in luminance, but also by "second-order" contrast or texture differences. Responses of cortical neurons to both first- and second-order patterns have been studied extensively, but only for responses to either type of stimulus in isolation. Here, we examined responses of visual cortex neurons to the spatial relationship between superimposed periodic luminance modulation (LM) and contrast modulation (CM) stimuli, the contrasts of which were adjusted to give equated responses when presented alone. Extracellular single-unit recordings were made in area 18 of the cat, the neurons of which show responses to CM and LM stimuli very similar to those in primate area V2 (Li et al., 2014). Most neurons showed a significant dependence on the relative phase of the combined LM and CM patterns, with a clear overall optimal response when they were approximately phase aligned. The degree of this phase preference, and the contributions of suppressive and/or facilitatory interactions, varied considerably from one neuron to another. Such phase-dependent and phase-invariant responses were evident in both simple- and complex-type cells. These results place important constraints on any future model of the underlying neural circuitry for second-order responses. The diversity in the degree of phase dependence between LM and CM stimuli that we observed could help to disambiguate different kinds of boundaries in natural scenes. SIGNIFICANCE STATEMENT Many visual cortex neurons exhibit orientation-selective responses to boundaries defined by differences either in luminance or in texture contrast. Previous studies have examined responses to either type of boundary in isolation, but here we measured systematically responses of cortical neurons to the spatial relationship between superimposed periodic luminance-modulated (LM) and contrast-modulated (CM) stimuli with contrasts adjusted to give equated responses. We demonstrate that neuronal responses to these compound stimuli are highly dependent on the relative phase between the LM and CM components. Diversity in the degree of such phase dependence could help to disambiguate different kinds of boundaries in natural scenes, for example, those arising from surface reflectance changes or from illumination gradients such as shading or shadows.
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12
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Norman LJ, Heywood CA, Kentridge RW. Texture segmentation without human V4. VISUAL COGNITION 2017. [DOI: 10.1080/13506285.2017.1301612] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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13
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Abstract
How does visual attention affect spatial resolution? In texture-segmentation tasks, exogenous (involuntary) attention automatically increases resolution at the attended location, which improves performance where resolution is too low (at the periphery) but impairs performance where resolution is already too high (at central locations). Conversely, endogenous (voluntary) attention improves performance at all eccentricities, which suggests a more flexible mechanism. Here, using selective adaptation to spatial frequency, we investigated the mechanism by which endogenous attention benefits performance in resolution tasks. Participants detected a texture target that could appear at several eccentricities. Adapting to high or low spatial frequencies selectively affected performance in a manner consistent with changes in resolution. Moreover, adapting to high, but not low, frequencies mitigated the attentional benefit at central locations where resolution was too high; this shows that attention can improve performance by decreasing resolution. Altogether, our results indicate that endogenous attention benefits performance by modulating the contribution of high-frequency information in order to flexibly adjust spatial resolution according to task demands.
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Affiliation(s)
| | - Marisa Carrasco
- 1 Department of Psychology, New York University.,2 Center for Neural Science, New York University
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14
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Gao Y, Reynaud A, Tang Y, Feng L, Zhou Y, Hess RF. The amblyopic deficit for 2nd order processing: Generality and laterality. Vision Res 2015; 114:111-21. [DOI: 10.1016/j.visres.2014.10.020] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2014] [Revised: 09/30/2014] [Accepted: 10/03/2014] [Indexed: 10/24/2022]
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15
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Ajina S, Kennard C, Rees G, Bridge H. Motion area V5/MT+ response to global motion in the absence of V1 resembles early visual cortex. ACTA ACUST UNITED AC 2014; 138:164-78. [PMID: 25433915 PMCID: PMC4285193 DOI: 10.1093/brain/awu328] [Citation(s) in RCA: 62] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022]
Abstract
Motion area V5/MT+ shows a variety of characteristic visual responses, often linked to perception, which are heavily influenced by its rich connectivity with the primary visual cortex (V1). This human motion area also receives a number of inputs from other visual regions, including direct subcortical connections and callosal connections with the contralateral hemisphere. Little is currently known about such alternative inputs to V5/MT+ and how they may drive and influence its activity. Using functional magnetic resonance imaging, the response of human V5/MT+ to increasing the proportion of coherent motion was measured in seven patients with unilateral V1 damage acquired during adulthood, and a group of healthy age-matched controls. When V1 was damaged, the typical V5/MT+ response to increasing coherence was lost. Rather, V5/MT+ in patients showed a negative trend with coherence that was similar to coherence-related activity in V1 of healthy control subjects. This shift to a response-pattern more typical of early visual cortex suggests that in the absence of V1, V5/MT+ activity may be shaped by similar direct subcortical input. This is likely to reflect intact residual pathways rather than a change in connectivity, and has important implications for blindsight function. It also confirms predictions that V1 is critically involved in normal V5/MT+ global motion processing, consistent with a convergent model of V1 input to V5/MT+. Historically, most attempts to model cortical visual responses do not consider the contribution of direct subcortical inputs that may bypass striate cortex, such as input to V5/MT+. We have shown that the signal change driven by these non-striate pathways can be measured, and suggest that models of the intact visual system may benefit from considering their contribution.
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Affiliation(s)
- Sara Ajina
- 1 FMRIB Centre, University of Oxford, UK 2 Nuffield Department of Clinical Neurosciences, University of Oxford, UK
| | | | - Geraint Rees
- 3 Wellcome Trust Centre for Neuroimaging, University College London, UK 4 Institute of Cognitive Neuroscience, University College London, UK
| | - Holly Bridge
- 1 FMRIB Centre, University of Oxford, UK 2 Nuffield Department of Clinical Neurosciences, University of Oxford, UK
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16
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An X, Gong H, Yin J, Wang X, Pan Y, Zhang X, Lu Y, Yang Y, Toth Z, Schiessl I, McLoughlin N, Wang W. Orientation-cue invariant population responses to contrast-modulated and phase-reversed contour stimuli in macaque V1 and V2. PLoS One 2014; 9:e106753. [PMID: 25188576 PMCID: PMC4154761 DOI: 10.1371/journal.pone.0106753] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2014] [Accepted: 08/01/2014] [Indexed: 11/20/2022] Open
Abstract
Visual scenes can be readily decomposed into a variety of oriented components, the processing of which is vital for object segregation and recognition. In primate V1 and V2, most neurons have small spatio-temporal receptive fields responding selectively to oriented luminance contours (first order), while only a subgroup of neurons signal non-luminance defined contours (second order). So how is the orientation of second-order contours represented at the population level in macaque V1 and V2? Here we compared the population responses in macaque V1 and V2 to two types of second-order contour stimuli generated either by modulation of contrast or phase reversal with those to first-order contour stimuli. Using intrinsic signal optical imaging, we found that the orientation of second-order contour stimuli was represented invariantly in the orientation columns of both macaque V1 and V2. A physiologically constrained spatio-temporal energy model of V1 and V2 neuronal populations could reproduce all the recorded population responses. These findings suggest that, at the population level, the primate early visual system processes the orientation of second-order contours initially through a linear spatio-temporal filter mechanism. Our results of population responses to different second-order contour stimuli support the idea that the orientation maps in primate V1 and V2 can be described as a spatial-temporal energy map.
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Affiliation(s)
- Xu An
- Institute of Neuroscience, State Key Laboratory of Neuroscience and Key Laboratory of Primate Neurobiology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, P. R. China
- Key Laboratory of Brain Function and Diseases, School of Life Sciences, University of Science and Technology of China, Hefei, P. R. China
| | - Hongliang Gong
- Institute of Neuroscience, State Key Laboratory of Neuroscience and Key Laboratory of Primate Neurobiology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, P. R. China
| | - Jiapeng Yin
- Institute of Neuroscience, State Key Laboratory of Neuroscience and Key Laboratory of Primate Neurobiology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, P. R. China
| | - Xiaochun Wang
- Institute of Neuroscience, State Key Laboratory of Neuroscience and Key Laboratory of Primate Neurobiology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, P. R. China
| | - Yanxia Pan
- Institute of Neuroscience, State Key Laboratory of Neuroscience and Key Laboratory of Primate Neurobiology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, P. R. China
| | - Xian Zhang
- Institute of Neuroscience, State Key Laboratory of Neuroscience and Key Laboratory of Primate Neurobiology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, P. R. China
- Key Laboratory of Brain Function and Diseases, School of Life Sciences, University of Science and Technology of China, Hefei, P. R. China
| | - Yiliang Lu
- Institute of Neuroscience, State Key Laboratory of Neuroscience and Key Laboratory of Primate Neurobiology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, P. R. China
| | - Yupeng Yang
- Key Laboratory of Brain Function and Diseases, School of Life Sciences, University of Science and Technology of China, Hefei, P. R. China
| | - Zoltan Toth
- Faculty of Life Science, University of Manchester, Manchester, United Kingdom
| | - Ingo Schiessl
- Faculty of Life Science, University of Manchester, Manchester, United Kingdom
| | - Niall McLoughlin
- Faculty of Life Science, University of Manchester, Manchester, United Kingdom
| | - Wei Wang
- Institute of Neuroscience, State Key Laboratory of Neuroscience and Key Laboratory of Primate Neurobiology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai, P. R. China
- * E-mail:
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Chen G, Hou F, Yan FF, Zhang P, Xi J, Zhou Y, Lu ZL, Huang CB. Noise provides new insights on contrast sensitivity function. PLoS One 2014; 9:e90579. [PMID: 24626135 PMCID: PMC3953123 DOI: 10.1371/journal.pone.0090579] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2013] [Accepted: 02/03/2014] [Indexed: 11/27/2022] Open
Abstract
Sensitivity to luminance difference, or contrast sensitivity, is critical for animals to survive in and interact with the external world. The contrast sensitivity function (CSF), which measures visual sensitivity to spatial patterns over a wide range of spatial frequencies, provides a comprehensive characterization of the visual system. Despite its popularity and significance in both basic research and clinical practice, it hasn’t been clear what determines the CSF and how the factors underlying the CSF change in different conditions. In the current study, we applied the external noise method and perceptual template model to a wide range of external noise and spatial frequency (SF) conditions, and evaluated how the various sources of observer inefficiency changed with SF and determined the limiting factors underlying the CSF. We found that only internal additive noise and template gain changed significantly with SF, while the transducer non-linearity and coefficient for multiplicative noise were constant. The 12-parameter model provided a very good account of all the data in the 200 tested conditions (86.5%, 86.2%, 89.5%, and 96.4% for the four subjects, respectively). Our results suggest a re-consideration of the popular spatial vision model that employs the CSF as the front-end filter and constant internal additive noise across spatial frequencies. The study will also be of interest to scientists and clinicians engaged in characterizing spatial vision deficits and/or developing rehabilitation methods to restore spatial vision in clinical populations.
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Affiliation(s)
- Ge Chen
- Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Fang Hou
- Center for Cognitive and Brain Sciences, Department of Psychology, Ohio State University, Columbus, Ohio, United States of America
| | - Fang-Fang Yan
- Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - Pan Zhang
- Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - Jie Xi
- Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
| | - Yifeng Zhou
- Key Laboratory of Brain Function and Diseases, Chinese Academy of Sciences, and School of Life Sciences, University of Science and Technology of China, Hefei, Anhui, China
| | - Zhong-Lin Lu
- Center for Cognitive and Brain Sciences, Department of Psychology, Ohio State University, Columbus, Ohio, United States of America
| | - Chang-Bing Huang
- Key Laboratory of Behavioral Science, Institute of Psychology, Chinese Academy of Sciences, Beijing, China
- * E-mail:
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18
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Westrick ZM, Landy MS. Pooling of first-order inputs in second-order vision. Vision Res 2013; 91:108-17. [PMID: 23994031 DOI: 10.1016/j.visres.2013.08.005] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2013] [Revised: 07/22/2013] [Accepted: 08/12/2013] [Indexed: 11/28/2022]
Abstract
The processing of texture patterns has been characterized by a model that first filters the image to isolate one texture component, then applies a rectifying nonlinearity that converts texture variation into intensity variation, and finally processes the resulting pattern with mechanisms similar to those used in processing luminance-defined images (spatial-frequency- and orientation-tuned filters). This model, known as FRF for filter rectify filter, has the appeal of explaining sensitivity to second-order patterns in terms of mechanisms known to exist for processing first-order patterns. This model implies an unexpected interaction between the first and second stages of filtering; if the first-stage filter consists of narrowband mechanisms tuned to detect the carrier texture, then sensitivity to high-frequency texture modulations should be much lower than is observed in humans. We propose that the human visual system must pool over first-order channels tuned to a wide range of spatial frequencies and orientations to achieve texture demodulation, and provide psychophysical evidence for pooling in a cross-carrier adaptation experiment and in an experiment that measures modulation contrast sensitivity at very low first-order contrast.
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19
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Kay KN, Winawer J, Rokem A, Mezer A, Wandell BA. A two-stage cascade model of BOLD responses in human visual cortex. PLoS Comput Biol 2013; 9:e1003079. [PMID: 23737741 PMCID: PMC3667759 DOI: 10.1371/journal.pcbi.1003079] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2012] [Accepted: 04/18/2013] [Indexed: 12/03/2022] Open
Abstract
Visual neuroscientists have discovered fundamental properties of neural representation through careful analysis of responses to controlled stimuli. Typically, different properties are studied and modeled separately. To integrate our knowledge, it is necessary to build general models that begin with an input image and predict responses to a wide range of stimuli. In this study, we develop a model that accepts an arbitrary band-pass grayscale image as input and predicts blood oxygenation level dependent (BOLD) responses in early visual cortex as output. The model has a cascade architecture, consisting of two stages of linear and nonlinear operations. The first stage involves well-established computations—local oriented filters and divisive normalization—whereas the second stage involves novel computations—compressive spatial summation (a form of normalization) and a variance-like nonlinearity that generates selectivity for second-order contrast. The parameters of the model, which are estimated from BOLD data, vary systematically across visual field maps: compared to primary visual cortex, extrastriate maps generally have larger receptive field size, stronger levels of normalization, and increased selectivity for second-order contrast. Our results provide insight into how stimuli are encoded and transformed in successive stages of visual processing. Much has been learned about how stimuli are represented in the visual system from measuring responses to carefully designed stimuli. Typically, different studies focus on different types of stimuli. Making sense of the large array of findings requires integrated models that explain responses to a wide range of stimuli. In this study, we measure functional magnetic resonance imaging (fMRI) responses in early visual cortex to a wide range of band-pass filtered images, and construct a computational model that takes the stimuli as input and predicts the fMRI responses as output. The model has a cascade architecture, consisting of two stages of linear and nonlinear operations. A novel component of the model is a nonlinear operation that generates selectivity for second-order contrast, that is, variations in contrast-energy across the visual field. We find that this nonlinearity is stronger in extrastriate areas V2 and V3 than in primary visual cortex V1. Our results provide insight into how stimuli are encoded and transformed in the visual system.
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Affiliation(s)
- Kendrick N Kay
- Department of Psychology, Stanford University, Stanford, California, USA.
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20
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Kay KN, Winawer J, Mezer A, Wandell BA. Compressive spatial summation in human visual cortex. J Neurophysiol 2013; 110:481-94. [PMID: 23615546 DOI: 10.1152/jn.00105.2013] [Citation(s) in RCA: 184] [Impact Index Per Article: 16.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
Neurons within a small (a few cubic millimeters) region of visual cortex respond to stimuli within a restricted region of the visual field. Previous studies have characterized the population response of such neurons using a model that sums contrast linearly across the visual field. In this study, we tested linear spatial summation of population responses using blood oxygenation level-dependent (BOLD) functional MRI. We measured BOLD responses to a systematic set of contrast patterns and discovered systematic deviation from linearity: the data are more accurately explained by a model in which a compressive static nonlinearity is applied after linear spatial summation. We found that the nonlinearity is present in early visual areas (e.g., V1, V2) and grows more pronounced in relatively anterior extrastriate areas (e.g., LO-2, VO-2). We then analyzed the effect of compressive spatial summation in terms of changes in the position and size of a viewed object. Compressive spatial summation is consistent with tolerance to changes in position and size, an important characteristic of object representation.
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Affiliation(s)
- Kendrick N Kay
- Department of Psychology, Stanford University, Stanford, CA, USA.
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21
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Westrick ZM, Henry CA, Landy MS. Inconsistent channel bandwidth estimates suggest winner-take-all nonlinearity in second-order vision. Vision Res 2013; 81:58-68. [PMID: 23416867 DOI: 10.1016/j.visres.2013.01.010] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2012] [Revised: 01/23/2013] [Accepted: 01/29/2013] [Indexed: 10/27/2022]
Abstract
The processing of texture patterns has been characterized by a model that postulates a first-stage linear filter to highlight a component texture, a pointwise rectification stage to convert contrast for the highlighted texture into mean response strength, followed by a second-stage linear filter to detect the texture-defined pattern. We estimated the spatial-frequency bandwidth of the second-stage filter mediating orientation discrimination of orientation-modulated second-order gratings by measuring threshold elevation in the presence of filtered noise added to the modulation signal. This experiment yielded no evidence for frequency tuning. A second experiment, in which subjects had to detect similar second-order gratings while judging their modulation frequency, produced bandwidth estimates of 1-1.5 octaves, similar to estimated bandwidths of first-order channels. We propose that an additional dominant-response-selection nonlinearity can account for these apparently contradictory results.
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22
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Barbot A, Landy MS, Carrasco M. Differential effects of exogenous and endogenous attention on second-order texture contrast sensitivity. J Vis 2012; 12:6. [PMID: 22895879 DOI: 10.1167/12/8/6] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
Abstract
The visual system can use a rich variety of contours to segment visual scenes into distinct perceptually coherent regions. However, successfully segmenting an image is a computationally expensive process. Previously we have shown that exogenous attention--the more automatic, stimulus-driven component of spatial attention--helps extract contours by enhancing contrast sensitivity for second-order, texture-defined patterns at the attended location, while reducing sensitivity at unattended locations, relative to a neutral condition. Interestingly, the effects of exogenous attention depended on the second-order spatial frequency of the stimulus. At parafoveal locations, attention enhanced second-order contrast sensitivity to relatively high, but not to low second-order spatial frequencies. In the present study we investigated whether endogenous attention-the more voluntary, conceptually-driven component of spatial attention--affects second-order contrast sensitivity, and if so, whether its effects are similar to those of exogenous attention. To that end, we compared the effects of exogenous and endogenous attention on the sensitivity to second-order, orientation-defined, texture patterns of either high or low second-order spatial frequencies. The results show that, like exogenous attention, endogenous attention enhances second-order contrast sensitivity at the attended location and reduces it at unattended locations. However, whereas the effects of exogenous attention are a function of the second-order spatial frequency content, endogenous attention affected second-order contrast sensitivity independent of the second-order spatial frequency content. This finding supports the notion that both exogenous and endogenous attention can affect second-order contrast sensitivity, but that endogenous attention is more flexible, benefitting performance under different conditions.
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Affiliation(s)
- Antoine Barbot
- Department of Psychology, New York University, New York, NY, USA.
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23
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Wang HX, Heeger DJ, Landy MS. Responses to second-order texture modulations undergo surround suppression. Vision Res 2012; 62:192-200. [PMID: 22811987 DOI: 10.1016/j.visres.2012.03.008] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
First-order (contrast) surround suppression has been well characterized both psychophysically and physiologically,but relatively little is known as to whether the perception of second-order visual stimuli exhibits analogous center–surround interactions. Second-order surround suppression was characterized by requiring subjects to detect second-order modulation in stimuli presented alone or embedded in a surround.Both contrast- (CM) and orientation-modulated (OM) stimuli were used. For most subjects and both OM and CM stimuli, second-order surrounds caused thresholds to be higher, indicative of second-order suppression. For CM stimuli, suppression was orientation-specific, i.e., higher thresholds for parallel than for orthogonal surrounds. However, the evidence for orientation specificity of suppression for OM stimuli was weaker. These results suggest that normalization, leading to surround suppression, operates at multiple stages in cortical processing.
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Affiliation(s)
- Helena X Wang
- Center for Neural Science, New York University, New York, NY 10003, United States.
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24
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McDonald JS, Mannion DJ, Clifford CWG. Gain control in the response of human visual cortex to plaids. J Neurophysiol 2012; 107:2570-80. [PMID: 22378166 DOI: 10.1152/jn.00616.2011] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022] Open
Abstract
A recent intrinsic signal optical imaging study in tree shrew showed, surprisingly, that the population response of V1 to plaid patterns comprising grating components of equal contrast is predicted by the average of the responses to the individual components (MacEvoy SP, Tucker TR, Fitzpatrick D. Nat Neurosci 12: 637-645, 2009). This prompted us to compare responses to plaids and gratings in human visual cortex as a function of contrast and orientation. We found that the functional MRI (fMRI) blood oxygenation level-dependent (BOLD) responses of areas V1-V3 to a plaid comprising superposed grating components of equal contrast are significantly higher than the responses to a single component. Furthermore, the orientation response profile of a plaid is poorly predicted from a linear combination of the responses to its components. Together, these results indicate that the model of MacEvoy et al. (2009) cannot, without modification, account for the fMRI BOLD response to plaids in human visual cortex.
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Affiliation(s)
- J Scott McDonald
- School of Psychology, The University of New South Wales, Sydney, Australia
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25
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Increased phase synchronization during continuous face integration measured simultaneously with EEG and fMRI. Clin Neurophysiol 2012; 123:1536-48. [PMID: 22305306 DOI: 10.1016/j.clinph.2011.12.019] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2011] [Revised: 10/30/2011] [Accepted: 12/21/2011] [Indexed: 11/22/2022]
Abstract
OBJECTIVE Gamma zero-lag phase synchronization has been measured in the animal brain during visual binding. Human scalp EEG studies used a phase locking factor (trial-to-trial phase-shift consistency) or gamma amplitude to measure binding but did not analyze common-phase signals so far. This study introduces a method to identify networks oscillating with near zero-lag phase synchronization in human subjects. METHODS We presented unpredictably moving face parts (NOFACE) which - during some periods - produced a complete schematic face (FACE). The amount of zero-lag phase synchronization was measured using global field synchronization (GFS). GFS provides global information on the amount of instantaneous coincidences in specific frequencies throughout the brain. RESULTS Gamma GFS was increased during the FACE condition. To localize the underlying areas, we correlated gamma GFS with simultaneously recorded BOLD responses. Positive correlates comprised the bilateral middle fusiform gyrus and the left precuneus. CONCLUSIONS These areas may form a network of areas transiently synchronized during face integration, including face-specific as well as binding-specific regions and regions for visual processing in general. SIGNIFICANCE Thus, the amount of zero-lag phase synchronization between remote regions of the human visual system can be measured with simultaneously acquired EEG/fMRI.
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26
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Graham NV. Beyond multiple pattern analyzers modeled as linear filters (as classical V1 simple cells): useful additions of the last 25 years. Vision Res 2011; 51:1397-430. [PMID: 21329718 DOI: 10.1016/j.visres.2011.02.007] [Citation(s) in RCA: 57] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/03/2010] [Revised: 02/07/2011] [Accepted: 02/09/2011] [Indexed: 11/28/2022]
Abstract
This review briefly discusses processes that have been suggested in the last 25 years as important to the intermediate stages of visual processing of patterns. Five categories of processes are presented: (1) Higher-order processes including FRF structures; (2) Divisive contrast nonlinearities including contrast normalization; (3) Subtractive contrast nonlinearities including contrast comparison; (4) Non-classical receptive fields (surround suppression, cross-orientation inhibition); (5) Contour integration.
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Affiliation(s)
- Norma V Graham
- Department of Psychology, Columbia University, NY, NY 10027, USA.
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