Search results for '*Visual Cortex' (try it on Scholar)

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  1. [deleted]Marianne Maertens, Stefan Pollmann, Michael Hanke, Toralf Mildner & Harald E. Möller (2008). Retinotopic Activation in Response to Subjective Contours in Primary Visual Cortex. Frontiers in Human Neuroscience 2:1-7.score: 240.0
    Objects in our visual environment are arranged in depth and hence there is a considerable amount of overlap and occlusion in the image they generate on the retina. In order to properly segment the image into fi gure and background, boundary interpolation is required even across large distances. Here we study the cortical mechanisms involved in collinear contour interpolation using fMRI. Human observers were asked to discriminate the curvature of interpolated boundaries in Kanizsa fi gures and in control confi gurations, (...)
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  2. Rufin Vogels (2010). Mechanisms of Visual Perceptual Learning in Macaque Visual Cortex. Topics in Cognitive Science 2 (2):239-250.score: 240.0
    The neural mechanisms underlying behavioral improvement in the detection or discrimination of visual stimuli following learning are still ill understood. Studies in nonhuman primates have shown relatively small and, across studies, variable effects of fine discrimination learning in primary visual cortex when tested outside the context of the learned task. At later stages, such as extrastriate area V4, extensive practice in fine discrimination produces more consistent effects upon responses and neural tuning. In V1 and V4, the effects of learning (...)
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  3. [deleted]Erhan Genc, Johanna Bergmann, Frank Tong, Randolph Blake, Wolf Singer & Axel Kohler (2011). Callosal Connections of Primary Visual Cortex Predict the Spatial Spreading of Binocular Rivalry Across the Visual Hemifields. Frontiers in Human Neuroscience 5.score: 240.0
    In binocular rivalry, presentation of different images to the separate eyes leads to conscious perception alternating between the two possible interpretations every few seconds. During perceptual transitions, a stimulus emerging into dominance can spread in a wave-like manner across the visual field. These traveling waves of rivalry dominance have been successfully related to the cortical magnification properties and functional activity of early visual areas, including the primary visual cortex (V1). Curiously however, these traveling waves undergo a delay when passing (...)
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  4. [deleted]Lawrence Gregory Appelbaum, Mario Liotti, Rick Perez, Sarabeth Fox & Marty G. Woldorff (2009). The Temporal Dynamics of Implicit Processing of Non-Letter, Letter, and Word-Forms in the Human Visual Cortex. Frontiers in Human Neuroscience 3.score: 234.0
    The decoding of visually presented line segments into letters, and letters into words, is critical to fluent reading abilities. Here we investigate the temporal dynamics of visual orthographic processes, focusing specifically on right hemisphere contributions and interactions between the hemispheres involved in the implicit processing of visually presented words, consonants, false fonts, and symbolic strings. High-density EEG was recorded while participants detected infrequent, simple, perceptual targets (dot strings) embedded amongst a of character strings. Beginning at 130ms, orthographic and non-orthographic stimuli (...)
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  5. Victor A. F. Lamme, H. Landman Super, P. R. R. Roelfsema & H. Spekreijse (2000). The Role of Primary Visual Cortex (V1) in Visual Awareness. Vision Research 40 (10):1507-21.score: 210.0
  6. Frank Tong (2003). Primary Visual Cortex and Visual Awareness. Nature Reviews Neuroscience 4 (3):219-229.score: 210.0
  7. Gijs J. Brouwer, Raymond van Ee & Jens Schwarzbach (2005). Activation in Visual Cortex Correlates with the Awareness of Stereoscopic Depth. Journal of Neuroscience 25 (45):10403-10413.score: 210.0
  8. Juha Silvanto & Geraint Rees (2011). What Does Neural Plasticity Tell Us About Role of Primary Visual Cortex (V1) in Visual Awareness? Frontiers in Psychology 2.score: 192.0
    The complete loss of visual awareness resulting from a lesion to the primary visual cortex (V1) suggests that this region is indispensable for conscious visual perception. There are however a number cases of conscious perception in the absence of V1 which appear to challenge this conclusion. These include reports of patients with bilateral V1 lesions sustained at an early age whose conscious vision has spontaneously recovered, as well as stroke patients who have recovered some conscious vision with the help (...)
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  9. Yang Xu, Christopher D'Lauro, John A. Pyles, Robert E. Kass & Michael J. Tarr (2013). Fine-Grained Temporal Coding of Visually-Similar Categories in the Ventral Visual Pathway and Prefrontal Cortex. Frontiers in Psychology 4.score: 192.0
    Humans are remarkably proficient at categorizing visually-similar objects. To better understand the cortical basis of this categorization process, we used magnetoencephalography (MEG) to record neural activity while participants learned--with feedback--to discriminate two highly-similar, novel visual categories. We hypothesized that although prefrontal regions would mediate early category learning, this role would diminish with increasing category familiarity and that regions within the ventral visual pathway would come to play a more prominent role in encoding category-relevant information as learning progressed. Early in learning (...)
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  10. [deleted]K. D. Singh J. B. Swettenham, S. D. Muthukumaraswamy (2013). BOLD Responses in Human Primary Visual Cortex Are Insensitive to Substantial Changes in Neural Activity. Frontiers in Human Neuroscience 7.score: 192.0
    The relationship between BOLD-fMRI (blood oxygenation level dependent-functional magnetic resonance imaging) and magnetoencephalography (MEG) metrics were explored using low-level visual stimuli known to elicit a rich variety of neural responses. Stimuli were either perceptually isoluminant red/green or luminance-modulated black/yellow square-wave gratings with spatial frequencies of 0.5, 3 and 6 cycles per degree. Neural responses were measured with BOLD-fMRI (3-tesla) and whole head MEG. For all stimuli, the BOLD response showed bilateral activation of early visual cortex that was greater in (...)
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  11. Tony Ro, Bruno Breitmeyer, Philip Burton, Neel S. Singhal & David Lane (2003). Feedback Contributions to Visual Awareness in Human Occipital Cortex. Current Biology 13 (12):1038-1041.score: 180.0
  12. Zhicheng Lin (2008). Unconscious Inference and Conscious Representation: Why Primary Visual Cortex (V1) is Directly Involved in Visual Awareness. Behavioral and Brain Sciences 31 (2):209-210.score: 180.0
    The extent to which visual processing can proceed in the visual hierarchy without awareness determines the magnitude of perceptual delay. Increasing data demonstrate that primary visual cortex (V1) is involved in consciousness, constraining the magnitude of visual delay. This makes it possible that visual delay is actually within the optimal lengths to allow sufficient computation; thus it might be unnecessary to compensate for visual delay.
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  13. Frank Sengpiel, Tobias Bonhoeffer, Tobe C. B. Freeman & Colin Blakemore (2001). On the Relationship Between Interocular Suppression in the Primary Visual Cortex and Binocular Rivalry. Brain and Mind 2 (1):39-54.score: 180.0
    Both classical psychophysical work and recentfunctional imaging studies have suggested acritical role for the primary visual cortex(V1) in resolving the perceptual ambiguitiesexperienced during binocular rivalry. Here weexamine, by means of single-cell recordings andoptical imaging of intrinsic signals, thespatial characteristics of suppression elicitedby rival stimuli in cat V1. We find that the interocular suppression field of V1 neuronsis centred on the same position in space and isslightly larger (by a factor of 1.3) than theminimum response field, measured through thesame eye. (...)
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  14. Hugh R. Wilson David F. Nichols, Lisa R. Betts (2010). Decoding of Faces and Face Components in Face-Sensitive Human Visual Cortex. Frontiers in Psychology 1.score: 180.0
    A great challenge to the field of visual neuroscience is to understand how faces are encoded and represented within the human brain. Here we show evidence from functional magnetic resonance imaging (fMRI) for spatially distributed processing of the whole face and its components in face-sensitive human visual cortex. We used multi-class linear pattern classifiers constructed with a leave-one-scan-out verification procedure to discriminate brain activation patterns elicited by whole faces, the internal features alone, and the external head outline alone. Furthermore, (...)
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  15. Tobias Bonhoeffer Frank Sengpiel, C. B. Freeman Tobe & Colin Blakemore (2001). On the Relationship Between Interocular Suppression in the Primary Visual Cortex and Binocular Rivalry. Brain and Mind 2 (1).score: 180.0
    Both classical psychophysical work and recentfunctional imaging studies have suggested acritical role for the primary visual cortex(V1) in resolving the perceptual ambiguitiesexperienced during binocular rivalry. Here weexamine, by means of single-cell recordings andoptical imaging of intrinsic signals, thespatial characteristics of suppression elicitedby rival stimuli in cat V1. We find that the interocular suppression field of V1 neuronsis centred on the same position in space and isslightly larger (by a factor of 1.3) than theminimum response field, measured through thesame eye. (...)
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  16. [deleted]Kevin A. Pelphrey, Juliana Lopez & James P. Morris (2009). Developmental Continuity and Change in Responses to Social and Nonsocial Categories in Human Extrastriate Visual Cortex. Frontiers in Human Neuroscience 3.score: 180.0
    It is well known that adult human extrastriate visual cortex contains areas that respond in a selective fashion to specific categories of visual stimuli. Three regions have been identified with particular regularity: the fusiform face area (FFA), which responds to faces more than to other objects; the parahippocampal place area (PPA), which responds selectively to images of houses, places, and visual scenes; and the extrastriate body area (EBA), which responds specifically to images of bodies and body parts. While the (...)
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  17. Josef Pfeuffer, High-Resolution 1H Chemical Shift Imaging in the Monkey Visual Cortex.score: 180.0
    Functionally distinct anatomic subdivisions of the brain can often be only a few millimeters in one or more dimensions. The study of metabolic differences in such structures by means of localized in vivo MR spectroscopy is therefore challenging, if not impossible. In fact, the spatial resolution of chemical shift imaging (CSI) in humans is typically in the range of centimeters. The aim of the present study was to optimize 1H CSI in monkeys and demonstrate the feasibility of high spatial resolutions (...)
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  18. Michael C. Schmid & Mark A. Augath, Visually Driven Activation in Macaque Areas V2 and V3 Without Input From the Primary Visual Cortex.score: 180.0
    Creating focal lesions in primary visual cortex (V1) provides an opportunity to study the role of extra-geniculo-striate pathways for activating extrastriate visual cortex. Previous studies have shown that more than 95% of neurons in macaque area V2 and V3 stop firing after reversibly cooling V1 [1,2,3]. However, no studies on long term recovery in areas V2, V3 following permanent V1 lesions have been reported in the macaque. Here we use macaque fMRI to study area V2, V3 activity patterns (...)
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  19. A. B. Bonds & E. J. DeBruyn (1985). Models of the Visual Cortex Edited by D. Rose and VG Dobson© 1985 John Wiley & Sons Ltd. In David Rose & Vernon Dobson (eds.), Models of the Visual Cortex. New York: John Wiley & Sons. 292.score: 180.0
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  20. Leon N. Cooper (1985). Models of the Visual Cortex Edited by D. Rose and VG Dobson© 1985 John Wiley & Sons Ltd. In David Rose & Vernon Dobson (eds.), Models of the Visual Cortex. New York: John Wiley & Sons. 164.score: 180.0
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  21. J. G. Daugman (1985). Models of the Visual Cortex Edited by D. Rose and VG Dobson© 1985 John Wiley & Sons Ltd. In David Rose & Vernon Dobson (eds.), Models of the Visual Cortex. New York: John Wiley & Sons. 96.score: 180.0
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  22. V. Dobson & D. Rose (1985). Application of an Explicit Procedure for Model Building in the Visual Cortex. In David Rose & Vernon Dobson (eds.), Models of the Visual Cortex. New York: John Wiley & Sons. 546--560.score: 180.0
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  23. Yves Fregnac (1985). Models of the Visual Cortex Edited by D. Rose and VG Dobson© 1985 John Wiley & Sons Ltd. In David Rose & Vernon Dobson (eds.), Models of the Visual Cortex. New York: John Wiley & Sons. 172.score: 180.0
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  24. M. A. Georgeson (1985). Models of the Visual Cortex Edited by D. Rose and VG Dobson© 1985 John Wiley & Sons Ltd. In David Rose & Vernon Dobson (eds.), Models of the Visual Cortex. New York: John Wiley & Sons. 223.score: 180.0
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  25. V. D. Glezer (1985). Spatial and Spatial Frequency Characteristics of Receptive Fields of the Visual Cortex and Piecewise Fourier Analysis. In David Rose & Vernon Dobson (eds.), Models of the Visual Cortex. New York: John Wiley & Sons. 265--272.score: 180.0
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  26. P. Gouras (1985). Parallel Processing of Color-Contrast Detectors in the Visual Cortex. In David Rose & Vernon Dobson (eds.), Models of the Visual Cortex. New York: John Wiley & Sons. 242.score: 180.0
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  27. P. Hammond (1985). Models of the Visual Cortex Edited by D. Rose and VG Dobson© 1985 John Wiley & Sons Ltd. In David Rose & Vernon Dobson (eds.), Models of the Visual Cortex. New York: John Wiley & Sons. 326.score: 180.0
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  28. G. Hartmann (1985). Hierarchical Contour Coding by the Visual Cortex. In David Rose & Vernon Dobson (eds.), Models of the Visual Cortex. New York: John Wiley & Sons. 137--145.score: 180.0
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  29. Shaul Hochstein & Hedva Spitzer (1985). One, Few, Infinity: Linear and Nonlinear Processing in the Visual Cortex. In David Rose & Vernon Dobson (eds.), Models of the Visual Cortex. New York: John Wiley & Sons. 341--350.score: 180.0
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  30. Christof Koch & Tomaso Poggio (1985). The Synaptic Veto Mechanism: Does It Underlie Direction and Orientation Selectivity in the Visual Cortex. In David Rose & Vernon Dobson (eds.), Models of the Visual Cortex. New York: John Wiley & Sons. 408--419.score: 180.0
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  31. Lamberto Maffei (1985). Models of the Visual Cortex Edited by D. Rose and VG Dobson© 1985 John Wiley & Sons Ltd. In David Rose & Vernon Dobson (eds.), Models of the Visual Cortex. New York: John Wiley & Sons. 334.score: 180.0
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  32. Dan E. Nielsen (1985). Models of the Visual Cortex Edited by D. Rose and VG Dobson© 1985 John Wiley & Sons Ltd. In David Rose & Vernon Dobson (eds.), Models of the Visual Cortex. New York: John Wiley & Sons. 374.score: 180.0
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  33. A. Peters (1985). Neuronal Composition and Circuitry of Rat Visual Cortex. In David Rose & Vernon Dobson (eds.), Models of the Visual Cortex. New York: John Wiley & Sons. 492--503.score: 180.0
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  34. Adam Murdin Sillito (1985). Inhibitory Circuits and Orientation Selectivity in the Visual Cortex. In David Rose & Vernon Dobson (eds.), Models of the Visual Cortex. New York: John Wiley & Sons.score: 180.0
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  35. W. Singer (1985). Activity-Dependent Self-Organization of the Mammalian Visual Cortex. In David Rose & Vernon Dobson (eds.), Models of the Visual Cortex. New York: John Wiley & Sons. 123--136.score: 180.0
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  36. N. V. Swindale (1985). Models of the Visual Cortex Edited by D. Rose and VG Dobson© 1985 John Wiley & Sons Ltd. In David Rose & Vernon Dobson (eds.), Models of the Visual Cortex. New York: John Wiley & Sons. 452.score: 180.0
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  37. Suzannah Bliss Tieman & Helmut Vb Hirsch (1985). Models of the Visual Cortex Edited by D. Rose and VG Dobson© 1985 John Wiley & Sons Ltd. In David Rose & Vernon Dobson (eds.), Models of the Visual Cortex. New York: John Wiley & Sons.score: 180.0
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  38. Keisuke Toyama (1985). Neuronal Circuitry in the Cat Visual Cortex Studied by Cross-Correlation Analysis. In David Rose & Vernon Dobson (eds.), Models of the Visual Cortex. New York: John Wiley & Sons.score: 180.0
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  39. [deleted]Kalanit Grill-Spector Golijeh Golarai, Alina Liberman, Jennifer M. D. Yoon (2009). Differential Development of the Ventral Visual Cortex Extends Through Adolescence. Frontiers in Human Neuroscience 3.score: 168.0
    The ventral temporal cortex (VTC) in humans includes functionally defined regions that preferentially respond to objects, faces, and places. Recent developmental studies suggest that the face selective region in the fusiform gyrus (‘fusiform face area’, FFA) undergoes a prolonged development involving substantial increases in its volume after age 7 years. However, the endpoint of this development is not known. Here we used functional magnetic resonance imaging (fMRI) to examine the development of face-, object- and place-selective regions in the VTC (...)
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  40. K. G. Thompson & Jeffrey D. Schall (2000). Antecedents and Correlates of Visual Detectoin and Awareness in Macaque Prefrontal Cortex. Vision Research 40 (10):1523-38.score: 168.0
  41. Geraint Rees, E. Wojciulik, Karen Clarke, Masud Husain, Christopher D. Frith & Julia Driver (2000). Unconscious Activation of Visual Cortex in the Damaged Right Hemisphere of a Parietal Patient with Extinction. Brain 123 (8):1624-1633.score: 162.0
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  42. Alyssa A. Brewer & Brian Barton (2014). Visual Cortex in Aging and Alzheimer's Disease: Changes in Visual Field Maps and Population Receptive Fields. Frontiers in Psychology 5.score: 162.0
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  43. [deleted]Kai J. Miller, Dora Hermes, Christopher J. Honey, Mohit Sharma, Rajesh P. N. Rao, Marcel Den Nijs, Eberhard E. Fetz, Terrence J. Sejnowski, Adam O. Hebb, Jeffrey G. Ojemann, Scott Makeig & Eric C. Leuthardt (2010). Dynamic Modulation of Local Population Activity by Rhythm Phase in Human Occipital Cortex During a Visual Search Task. Frontiers in Human Neuroscience 4:197.score: 162.0
    Brain rhythms are more than just passive phenomena in visual cortex. For the first time, we show that the physiology underlying brain rhythms actively suppresses and releases cortical areas on a second-to-second basis during visual processing. Furthermore, their influence is specific at the scale of individual gyri. We quantified the interaction between broadband spectral change and brain rhythms on a second-to-second basis in electrocorticographic (ECoG) measurement of brain surface potentials in five human subjects during a visual search task. Comparison (...)
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  44. Petra Stoerig & E. Barth (2001). Low-Level Phenomenal Vision Despite Unilateral Destruction of Primary Visual Cortex. Consciousness and Cognition 10 (4):574-587.score: 156.0
    GY, an extensively studied human hemianope, is aware of salient visual events in his cortically blind field but does not call this ''vision.'' To learn whether he has low-level conscious visual sensations or whether instead he has gained conscious knowledge about, or access to, visual information that does not produce a conscious phenomenal sensation, we attempted to image process a stimulus s presented to the impaired field so that when the transformed stimulus T(s) was presented to the normal hemifield it (...)
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  45. Stephen Grossberg (2003). Linking Visual Cortex to Visual Perception: An Alternative to the Gestalt Bubble. Behavioral and Brain Sciences 26 (4):412-413.score: 156.0
    Lehar's lively discussion builds on a critique of neural models of vision that is incorrect in its general and specific claims. He espouses a Gestalt perceptual approach rather than one consistent with the “objective neurophysiological state of the visual system” (target article, Abstract). Contemporary vision models realize his perceptual goals and also quantitatively explain neurophysiological and anatomical data.
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  46. Luiz Carlos L. Silveira (2004). Parallel Visual Pathways From the Retina to the Visual Cortex – How Do They Fit? Behavioral and Brain Sciences 27 (1):50-51.score: 156.0
    Which roles are played by subcortical pathways in models of cortical streams for visual processing? Through their thalamic relays, magnocellular (M) and parvocellular (P) projecting ganglion cells send complementary signals to V1, where their outputs are combined in several different ways. The synergic role of M and P cells in vision can be understood by estimating cell response entropy in all domains of interest.
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  47. Annie Wai Yiu Chan (2013). Functional Organization and Visual Representations of Human Ventral Lateral Prefrontal Cortex. Frontiers in Psychology 4.score: 156.0
    Recent neuroimaging studies in both human and non-human primates have identified face selective activation in the ventral lateral prefrontal cortex even in the absence of working memory demands. Further, research has suggested that this face-selective response is largely driven by the presence of the eyes. However, the nature and origin of visual category responses in the ventral lateral prefrontal cortex remain unclear. Further, in a broader sense, how do these findings relate to our current understandings of lateral prefrontal (...)
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  48. [deleted]David Mattijs Arnoldussen, Jeroen Goossens & Albert Van Den Berg (2013). Differential Responses in Dorsal Visual Cortex to Motion and Disparity Depth Cues. Frontiers in Human Neuroscience 7:815.score: 156.0
    We investigated how interactions between monocular motion parallax and binocular cues to depth vary in human motion areas for wide-field visual motion stimuli (110x100 degrees). We used fMRI with an extensive 2x3x2 factorial blocked design in which we combined two types of self-motion (translation and translation + rotation), with three categories of motion inflicted by the degree of noise (self-motion, distorted self-motion and multiple object-motion), and two different view modes of the flow patterns (stereo and synoptic viewing). Interactions between view (...)
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  49. [deleted]Sharon Gilaie-Dotan, Juha Silvanto, Dietrich S. Schwarzkopf & Geraint Rees (2010). Investigating Representations of Facial Identity in Human Ventral Visual Cortex with Transcranial Magnetic Stimulation. Frontiers in Human Neuroscience 4:50.score: 156.0
    The occipital face area (OFA) is face-selective. This enhanced activation to faces could reflect either generic face and shape-related processing or high-level conceptual processing of identity. Here we examined these two possibilities using a state-dependent transcranial magnetic stimulation (TMS) paradigm. The lateral occipital (LO) cortex which is activated non-selectively by various types of objects served as a control site. We localized OFA and LO on a per-participant basis using functional MRI. We then examined whether TMS applied to either of (...)
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  50. [deleted]Thomas Miconi & Rufin Vanrullen (2010). The Gamma Slideshow: Object-Based Perceptual Cycles in a Model of the Visual Cortex. Frontiers in Human Neuroscience 4:205-205.score: 156.0
    While recent studies have shed light on the mechanisms that generate gamma (>40Hz) oscillations, the functional role of these oscillations (if any) is still debated. Here we suggest that the purported mechanism of gamma oscillations (feedback inhibition from local interneurons), coupled with lateral connections implementing “Gestalt” principles of object integration, naturally leads to a decomposition of the visual input into object-based “perceptual cycles”, in which neuron populations representing different objects within the scene will tend to fire at successive cycles of (...)
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