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Attention and Rivalry Suppression
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The role of attention has been suggested as selecting relevant information to the current objective, thereby enabling the visual system to overcome its limited capacity. On the other hand, there has not been a consensus on the role of rivalry suppression, where one of two different stimuli presented to different eyes becomes invisible. In the current paper, we propose that rivalry suppression serves the same goal as attention. Specifically, we argue that rivalry suppression helps the visual system to carry potentially necessary information without conscious effort and reduce processing loads. In this paper, we elaborate on several important parallels between attention and suppression. First, attended and suppressed information can be considered as indicating the opposite sides of consciousness. Second, unattended information can be invisible much like suppressed information. Third, the neural mechanisms underlying both attention and rivalry suppression have been suggested to be located in the same area, the frontal-parietal cortex. Fourth, the effects of attention and suppression are manifested more in higher visual processing areas and their effect sizes are similar. Finally, attention can bring suppressed information back to the conscious level, if necessary. We conclude that both attention and rivalry suppression reduce the burden on the visual system but in contrasting ways, one selecting only relevant information to the current goal and the other carrying information without conscious effort.

Attention , Suppression , and Binocular Rivalry
  • Introduction

    Our visual world is filled with events and objects that are constantly changing. Although phenomenological perception of a scene we experience is often vivid and seamless, our visual system often fails to notice what changes happened (Rensink, 2002; Simons & Ambinder, 2005). Likewise, the representation of a visual scene is sparse(Intraub, 1997) as evidenced by poor transsaccadic memory (Irwin, 1991), and visual working memory can store up to only four objects (Cowan, 2001; Luck & Vogel; 1997).

    Such limited capacity forces the visual system to develop strategies to achieve an economical representation of a visual scene, and attention has been considered as one of the most prominent processes traditionally. Attention only selects relevant information among multiple visual stimuli to meet one’s current objective. In this paper, we suggest that suppression serves the same goal as attention, to achieve an economical representation. We define suppression as placing visual stimuli outside of awareness despite their physical presence, resulting in an experience akin to actual physical absence of these stimuli. Suppression differs from complete removal of the stimuli, however, because suppressed stimuli—although invisible— still can influence later processing in various ways (Merikle, Smilek, & Eastwood, 2001). In this paper, we focus on rivalry suppression where one of two different stimuli presented to different eyes becomes invisible. Rivalry suppression differs from attentional suppression because attention can both increase and decrease the effectiveness of rivalry suppression (Shin et al., 2009;Jung & Chong, 2014). Suppressing stimuli may be a means of reducing the mental effort required for conscious processing (Kahneman, 1973).1 Bolstering this idea, the visual system appears to store a vast amount of information without the observer’s awareness (Jiang, Song, & Rigas, 2005), and thus it saves mental effort compared to conscious storing of these information. In addition, suppression may reduce processing demands by decreasing the strength of stimuli (Blake, Tadin, Sobel, Raissian, & Chong, 2006).

    We propose that suppression, much like attention, plays an important role in achieving an efficient representation of a complex scene. While attention helps the visual system to achieve efficient processing by filtering out irrelevant information, suppression reaches the same goal by maintaining possibly necessary information without conscious effort and high processing demands.

    Despite the notion of attention and suppression having a common computational mechanism (Ling & Blake, 2012), one reason why these two processes have not been considered as serving a common purpose may be due to different perspectives in the two fields. The functional role of attention, which William James (1890) has defined as taking possession of one among multiple objects, has been considered as the selection of only the information that is relevant to a current goal. One prominent attention model, the biased competition model (Desimone & Duncan, 1995; Reynolds, Chelazzi, & Desimone, 1999), argues that attention resolves the competition that exists among multiple objects—from which, for further processing, the visual system must select only a proportion of —in a limited visual space. Where this selection occurs and how it helps the visual system to cope with complex environments have been the major questions in the field (Broadbent, 1982 vs. Deutsch & Deutsch, 1963).

    On the other hand, studies of suppression have not yet fully agreed on its purpose. For example, the role of binocular rivalry suppression is often suggested as resolving seemingly conflicting percepts (Blake & Logothetis, 2002). Another suggested role of rivalry suppression is helping one to maintain focus by placing blurred (out-of-focus) images outside of awareness (Arnold, Grove, & Wallis, 2007; Norman, Norman, & Bilotta; 2000). The suggested roles of suppression in other phenomena are even more diverse (see Box 1). No one, however, has yet interpreted suppression as a process to overcome our limited visual capacity, as attention has been understood. Among several other phenomena, we focus on suppression due to binocular rivalry in this paper (Kim & Blake, 2005). In rivalry suppression, a dominant stimulus suppresses another stimulus presented to the other eye, making it invisible (Blake, 1989). Rivalry does not require additional stimuli or physical alterations to the stimuli to change their visibility, unlike other types of suppression (Kim & Blake, 2005).

    To this day, attention and suppression have been studied separately because their effects on visual awareness act in opposite fashion; one improves the quality of perception (Carrasco, Ling, & Read, 2004) while the other degrades it (Ling & Blake, 2009). Here, we propose a new conceptual angle to rivalry suppression, targeting on its function as reducing the burden on the visual system. In support of this view, we will review various pieces of evidence that show similarities between attention and rivalry suppression. We first interpret attention and suppression as being related via consciousness. Phenomenally speaking, the effect of attention on unattended stimuli appears similar to that of suppression (Mack & Rock, 1998; Most, Scholl, Clifford, & Simons, 2005). Moreover, attentional selection and rivalry suppression share common neural correlates in terms of initiation (Carmel, Walsh, Lavie, & Rees, 2010; Yantis, Schwarzbach, Serences, Carlson, Steinmetz, Pekar, & Courtney, 2002), and their effects are more pronounced in higher visual areas than in early visual areas (Kastner & Ungerleider, 2000; Nguyen, Freeman, & Alais, 2003). Based on these similarities, we propose that attention and suppression serve a common purpose: reducing the burden on the visual system to cope with a complex scene.

    1Despite additional efforts needed for conscious processing, conscious processing is more advantageous in some area. For example, conscious processing can be more flexible than unconscious processing (i.e., it can utilize a strategy during a task, Cheesman & Merikle, 1986).

    Attentionand Suppression as the Two Sides of Consciousness

    While the relationship between attention and suppression has not been explicitly discussed, the connection of each to consciousness has been suggested independently. Attention has often been thought of as a gateway to consciousness (Posner, 1994) or a catalyst for verbal access to the contents of consciousness (Lamme, 2003). In support of this notion, different forms of attention correspond well to different levels of consciousness (Cohen, Cavanagh, Chun, & Nakayama, 2012; Marchetti, 2012, but see also Koch & Tsuchiya, 2007). It has also been suggested that consciousness and its counterpart unconsciousness should be investigated simultaneously (Crick & Koch, 1998). When suppression is regarded as a means of blocking stimuli from reaching consciousness, it reduces conscious perception. In contrast, attention enhances conscious perception. Therefore, attention and suppression may be linked to be manifestations of changes in consciousness, albeit in an opposite way (Figure 1).

    This relationship becomes evident when considering what happens to unattended information. Unattended information is subject to attentional suppression. Multiple stimuli compete for the limited capacity our visual system, especially when they are present within the same receptive field (Desimone & Duncun, 1995; Kastner, De Weerd, Desimone, & Ungerleider, 1998; Reynolds, Chelazzi, & Desimone, 1999). The visual system selects a behaviorally relevant subset of the stimuli in the visual field and suppresses the rest. The selected stimuli are preserved for the next stages of information processing, and the unselected—i.e., unattended—stimuli are ‘less’ processed compared to those that are neutral, where attention is not given to any of the items in a given visual field.

    Attentional suppression, much like rivalry suppression, even renders stimuli invisible. When attention is directed elsewhere, we hardly perceive what we are looking at; this is known as inattentional blindness (Mack & Rock, 1998; Most et al., 2005). Even salient events such as the appearance of new objects are not detected when attention is directed to a different location. Indeed, the cause of inattentional blindness has been suggested to be attentional suppression (Thakral & Slotnick, 2010). Such findings show that attentional suppression is able to bring the same end result as rivalry suppression: causing stimuli to be invisible.

    Such phenomenal similarity between attentional and rivalry suppression is also reflected in their interaction. Attention can influence the rate of dominance changes (Chong, Tadin, & Blake, 2005; Lack, 1978) and the initial dominance of the attended stimulus (Chong & Blake, 2006; Mitchell, Stoner, & Reynolds, 2004) 2 . Furthermore, without attention, the ERP and behavioral signatures demarcating perceptual changes disappear (Brascamp & Blake, 2012; Zhang, Jamison, Engel, He, & He, 2011). A recent study (Ling & Blake, 2012) suggests that attention and rivalry suppression operate via the same computational mechanism of normalization (Reynolds & Heeger, 2009).

    Attention and suppression change the perceptual quality of the visual stimuli in opposite ways. Attention enhances the perception of relevant items, making them consciously vivid. Meanwhile, attention filters out other irrelevant items. These unattended stimuli are less processed compared to neutral ones, and they are sometimes even rendered invisible. Similarly, suppression reduces the visibility of the stimuli to the unconscious level.

    2Note that attentional suppression plays a more active role than rivalry suppression. Meng & Tong (2004) found that observers showed much weaker attentional control over rivalry alternations than Necker cube alternations.

    Neural Correlates of Attention and Suppression: The Fronto-Parietal Network

    The commonalities between attention and suppression are also reflected in their neural correlates. The fronto-parietal network is important for attention. Specifically, the network is implicated in orienting attention (Buschman & Millner, 2007; Corbetta & Shulman, 2002; Nobre, 2001). When spatial attention shifts from one visual field to another, the superior parietal cortex shows transient neural activities (Yantis et al., 2002). Duncan (2006) also suggests that activities biased by attention arise from the frontal and parietal cortices. The same network appears to be responsible for various types of attention, regardless of whether they are feature-based (Shulman, 2002) or location-based (Corbetta, 1998).

    The fronto-parietal network has also been implicated in triggering state changes in rivalry. Reviews of recent brain-imaging studies (Rees, Kreiman, & Koch, 2002; Sterzer, Kleinschmidt, & Rees, 2009) have viewed the role of fronto-parietal network as initiating perceptual changes in bi-stable figures (but see also Knapen, Brascamp, Pearson, van Ee, & Blake, 2011). Moreover, activities in the right fronto-parietal region were correlated with perceptual transitions in rivalry (Lumer, Friston, & Rees, 1998). Consistent with this finding, rTMS over the right superior parietal cortex reduced dominance durations in rivalry (Carmel et al., 2010), implying that rTMS interfered with maintaining the current state of rivalry.

    The parietal cortex appears to initiate shifts of attention (Yantis et al., 2002) and perceptual alternation during rivalry (Carmel et al., 2010). This initiation in turn flows down to content-specific visual areas to modulate the amount of attention and suppression. In both humans (Ruff, Blankenburg, Bjoertomt, Bestmann, Freeman, Haynes, ... & Driver, 2006) and monkeys (Moore & Armstrong, 2003), activities in the early visual cortex were directly influenced by electrical stimulation to the frontal eye fields.

    Hierarchical Representation of Attention and Suppression

    Attention and suppression initiated from the parietal cortex are hierarchically reflected in visual areas. More specifically, both effects are observed over multiple stages of visual processing with stronger effects towards higher visual areas. We argue that both attention and suppression have greater effects in higher visual areas in order to cope with increased complexity of information (Felleman & Van Essen, 1991; Ungerleider & Mishkin, 1982).

    Attentional selection occurs at multiple stages of visual information processing. Attentional effects are observed as early as LGN (O’Connor, Fukui, Pinsk, & Kastner, 2002), consistent with the early selection models of attention (Broadbent, 1982). The effects, however, are more pronounced for successive visual areas along the hierarchy (Kastner, De Weerd, Desimone, & Ungerleider, 1998; Schwartz, Vuilleumier, Hutton, Maravita, Dolan, & Driver, 2005).

    The locus of visual selection depends on the perceptual load imposed on the visual system (Lavie, 1995; 2000; Lavie & Cox, 1997; Lavie & Tsal, 1994). More precisely, the extent to which a perceptual task consumes available resources determines how much task-irrelevant, unselected stimuli will be processed. With a high perceptual load, there is not enough capacity to process irrelevant stimuli and selection appears to occur at an early stage. In contrast, when the perceptual load is low, task-irrelevant stimuli will receive enough attentional resources to be processed, in accordance with the late-selection model (Deutsch & Deutsch, 1963). The selection is modulated more by the task load at higher visual areas compared to early visual areas (Schwartz et al., 2005), implying that the complexity of information affects later visual processing more.

    Suppression also achieves its goal over multiple stages of visual processing, and the effects become augmented in higher areas. The visibility of an adaptor during rivalry modulated the amount of spiral motion aftereffects (Wiesenfelder & Blake, 1990), whereas it did not affect the aftereffects of linear motion (Lehmkuhle & Fox, 1975, but see also Blake et al., 2006). Because linear motion is mostly processed in early visual areas (Movshon & Newsome, 1992) and spiral motion is mostly processed in higher visual areas such as MST (Duffy & Wurtz, 1991), these results suggest that the depth of suppression becomes larger along the dorsal stream. This trend was confirmed using plaid-pattern-induced motion aftereffects (Van Der Zwan, Wenderoth, & Alais, 1993). Motion aftereffects were reduced with the plaid pattern but not with a component grating as an adaptor.

    In the ventral stream, the ERP amplitudes of suppressed stimuli were not reduced in early visual areas (Riggs & Whittle, 1967, but see also Zhang et al., 2011), whereas in higher areas the depth of suppression was larger even to a level corresponding to the physical removal of stimuli (Moradi, Koch, & Shimojo, 2005). Nguyen et al. (2003) investigated the depth of suppression depending on the complexity of stimuli and found that probe detection became progressively more difficult as the complexity of a suppressed stimulus increased. In addition, more neurons in higher visual areas showed the pattern of activities that was correlated with percept changes in rivalry (Leopold & Logothetis, 1996). Again, these results suggest that the depth of suppression becomes deeper in higher areas.

    In summary, the effects of attention, originated from the higher information processing stages (Hochstein & Ahissar, 2002), are stronger in higher visual areas (Kastner et al., 1998; Schwartz, 2005) and are observed in multiple stages of visual processing (Broadbent, 1958; Deutsch & Deutsch, 1963; Treisman, 1960). Similarly, the effects of suppression become stronger towards higher areas (Nguyen et al., 2003) and occur in multiple stages of visual processing as well (Blake & Logothetis, 2002; Tong, Meng, & Blake, 2006). In addition, the magnitudes of the two effects are also observed to be in comparable ranges across multiple studies (see Box 2).

    3Please note that this examination is not a thorough investigation of the literature by any means. We simply wanted to check the magnitude of both effects in relatively well-matched studies


    Early researchers have only noted the similarity between attention and binocular rivalry as aspects of the visual selection mechanism (William James, 1890; von Helmholtz, 1924). Here, we review recent experimental evidence of various similarities and make a connection between attention and rivalry suppression via consciousness. The connection is further supported by the similar fates of unattended information and suppressed information: both attention and rivalry suppression can render stimuli invisible and they even interact, indicating that they are based on the common mechanism (normalization). The neural correlates of attention and suppression also share the same origin: the fronto-parietal network. Finally, both effects become more pronounced in higher visual areas to serve the same purpose of increasing selection efficiency given more complex stimuli.

    Despite these similarities, attention and suppression have not been proposed to serve a common goal in the visual system. Recent studies suggest, however, that suppression as well as attention work in order to achieve an economical representation of a complex scene. More specifically, the visual system uses suppression to retain possibly necessary information without conscious effort, as invisible items can still contribute to the visual working memory (Soto, Mäntylä, & Silvanto, 2011). Moreover, a transient signal in the suppressed eye—an indicator of a new and potentially important input—usually breaks suppression (Blake, Westendorf, & Fox, 1990). Attention may bring the suppressed information back to consciousness. Although invisible high-level stimuli such as faces do not usually produce aftereffects (Moradi et al., 2005), they can if they are attended (Shin, Stolte, & Chong, 2009). In addition, it has been proposed that visual features could be unconsciously bound (Lin & He, 2009), although the binding is fragile unlike the conscious one. Therefore, it is plausible that invisible features under suppression are weakly bound and promptly used when attended.

    We propose that both attention and suppression operate to overcome the limited capacity of the visual system: attention selects relevant information and suppression keeps potentially relevant (currently irrelevant) information without additional costs. As the visual system processes more complex information in higher areas, the burden of retaining the information increases because more refined and complex representation is required. Thus, attention helps the visual system to reduce the burden by augmenting its effects and suppression is able to do the similar job by increasing the depth of suppression.

  • 1. Arnold D. H., Grove P. M., Wallis T. S. 2007 Staying focused: A functional account of perceptual suppression during binocular rivalry. [Journal of Vision] Vol.7 P.1-8 google doi
  • 2. Blake R. 1989 A neural theory of binocular rivalry. [Psychological Review] Vol.96 P.145-167 google doi
  • 3. Blake R., Camisa J. 1978 Is binocular vision always monocular? [Science] Vol.200 P.1497-1499 google doi
  • 4. Blake R., Camisa J. 1979 On the inhibitory nature of binocular rivalry suppression. [Journal of Experimental Psychology: Human Perception and Performance] Vol.5 P.315-323 google doi
  • 5. Blake R., Fox R. 1974 Binocular rivalry suppression: Insensitive to spatial frequency and orientation change. [Vision research] Vol.14 P.687-692 google doi
  • 6. Blake R., Logothetis N. K. 2002 Visual competition. [Nature Reviews Neuroscience] Vol.3 P.13-21 google doi
  • 7. Blake R., Tadin D., Sobel K. V., Raissian T. A., Chong S. C. 2006 Strength of early visual adaptation depends on visual awareness. [Proceedings of the National Academy of Sciences] Vol.103 P.4783-4788 google doi
  • 8. Blake R., Westendorf D., Fox R. 1990 Temporal perturbations of binocular rivalry. [Attention, Perception & Psychophysics] Vol.48 P.593-602 google doi
  • 9. Brascamp J. W., Blake R. 2012 Inattention abolishes binocular rivalry:Perceptual evidence. [Psychological Science] Vol.23 P.1159-1167 google
  • 10. Broadbent D. E. 1958 Perception and communication. google
  • 11. Broadbent D. E. 1982 Task combination and selective intake of information. [Acta Psychologica] Vol.50 P.253-290 google doi
  • 12. Buschman T. J., Millner E. K. 2007 Top-down versus bottom-up control of attention in the prefrontal and posterior parietal cortices. [Science] Vol.30 P.1860-1862 google doi
  • 13. Carmel D., Walsh V., Lavie N., Rees G. 2010 Right parietal TMS shortens dominance durations in binocular rivalry. [Current Biology] Vol.20 P.R799-R800 google doi
  • 14. Carrasco M., Ling S., Read S. 2004 Attention alters appearance. [Nature Neuroscience] Vol.7 P.308-313 google doi
  • 15. Cavanaugh J. R., Bair W., Movshon J. A. 2002 Selectivity and spatial distribution of signals from the receptive field surround in macaque V1 neurons [Journal of Neurophysiology] Vol.88 P.2547-2556 google doi
  • 16. Cheesman J., Merikle P. M. 1986 Distinguishing conscious from unconscious perceptual processes. [Cannadian Journal of Psychology] Vol.40 P.343-367 google doi
  • 17. Chica A. B., Lasaponara S., Chanes L., Valero-Cabre A., Doricchi F., Lupianez J., Bartolomeo P. 2011 Spatial attention and conscious perception: The role of endogenous and exogenous orienting. [Attention, Perception, & Psychophysics] Vol.73 P.1065-1081 google doi
  • 18. Chong S. C., Blake R. 2006 Exogenous attention and endogenous attention influence initial dominance in binocular rivalry. [Vision Research] Vol.46 P.1794-1803 google doi
  • 19. Chong S. C., Tadin D., Blake R. 2005 Endogenous attention prolongs dominance durations in binocular rivalry. [Journal of Vision] Vol.5 P.1004-1012 google doi
  • 20. Cohen M. A., Cavanagh P., Chun M. M., Nakayama K. 2012 The attentional requirements of consciousness. [Trends in Cognitive Sciences] Vol.16 P.411-417 google doi
  • 21. Collyer S. C., Bevan W. 1970 Objective measurement of dominance control in binocular rivalry. [Attention, Perception & Psychophysics] Vol.8 P.437-439 google doi
  • 22. Corbetta M. 1998 Frontoparietal cortical networks for directing attention and the eye to visual locations: Identical, independent, or overlapping neural systems? [Proceedings of the National Academy of Sciences] Vol.95 P.831-838 google
  • 23. Corbetta M., Shulman G. L. 2002 [Nature Reviews Neuroscience] Vol.3 P.201-215
  • 24. Cowan N. 2001 The magical number 4 in short-term memory: A reconsideration of mental storage capacity. [Behavioral and Brain Sciences] Vol.24 P.87-114 google doi
  • 25. Crick F., Koch C. 1998 Consciousness and neuroscience. [Cerebral Cortex] Vol.8 P.97-107 google doi
  • 26. Desimone R., Duncan J. 1995 Neural mechanisms of selective visual attention. [Annual Review of Neuroscience] Vol.18 P.193-222 google doi
  • 27. Deutsch J. A., Deutsch D. 1963 Attention: Some theoretical considerations. [Psychological Review] Vol.70 P.80-90 google doi
  • 28. De Weerd P., Smith E., Greenberg P. 2006 Effects of selective attention on perceptual filling-in. [Journal of Cognitive Neuroscience] Vol.18 P.335-347 google doi
  • 29. Duffy C. J., Wurtz R. H. 1991 Sensitivity of MST neurons to optic flow stimuli. I. A continuum of response selectivity to large-field stimuli. [Journal of Neurophysiology] Vol.65 P.1329-1345 google
  • 30. Duncan J. 2006 EPS Mid-Career Award 2004: Brain mechanisms of attention. [The Quarterly Journal of Experimental Psychology] Vol.59 P.2-27 google doi
  • 31. Felleman D. J. Van Essen D. C. 1991 Distributed hierarchical processing in the primate cerebral cortex. [Cerebral Cortex] Vol.1 P.1-47 google doi
  • 32. Fox R., Check R. 1972 Independence between binocular rivalry suppression duration and magnitude of suppression. [Journal of experimental psychology] Vol.93 P.283-289 google doi
  • 33. Hochstein S., Ahissar M. 2002 View from the top: Hierarchies and reverse hierarchies in the visual system. [Neuron] Vol.36 P.791-804 google doi
  • 34. Intraub H. 1997 The representation of visual scenes. [Trends in Cognitive Sciences] Vol.1 P.217-222 google doi
  • 35. Irwin D. E. 1991 Information integration across saccadic eye movements. [Cognitive Psychology] Vol.23 P.420-456 google doi
  • 36. James W. 1890 The principles of psychology. google
  • 37. Jiang Y., Song J. H., Rigas A. 2005 High-capacity spatial contextual memory. [Psychonomic Bulletin & Review] Vol.12 P.524-529 google doi
  • 38. Jung Y. R., Chong S. C. 2014 Effects of attention on visible and invisible adapters. [Perception] Vol.43 P.549-568 google doi
  • 39. Kahneman D. 1973 Attention and effort. google
  • 40. Kastner S., De Weerd P., Desimone R., Ungerleider L. G. 1998 Mechanisms of directed attention in the human extrastriate cortex as revealed by functional MRI. [Science] Vol.282 P.108-111 google doi
  • 41. Kastner S., Ungerleider L. G. 2000 Mechanisms of visual attention in the human cortex. [Annual Review of Neuroscience] Vol.23 P.315-341 google doi
  • 42. Kim C. Y., Blake R. 2005 Psychophysical magic: Rendering the visible ‘invisible’. [Trends in Cognitive Sciences] Vol.9 P.381-388 google doi
  • 43. Knapen T., Brascamp J., Pearson J., van Ee R., Blake R. 2011 The role of frontal and parietal brain areas in bistable perception. [The Journal of Neuroscience] Vol.31 P.10293-10301 google doi
  • 44. Koch C., Tsuchiya N. 2007 Attention and consciousness: Two distinct brain processes. [Trends in Cognitive Sciences] Vol.11 P.16-22 google doi
  • 45. Koivisto M., Kainulainen P., Revonsuo A. 2009 The relationship between awareness and attention: evidence from ERP responses. [Neuropsychologia] Vol.47 P.2891-2899 google doi
  • 46. Lack L. C. 1978 Selective attention and the control of binocular rivalry. google
  • 47. Lamme V. A. F. 2003 Why visual attention and awareness are different. [Trends in Cognitive Sciences] Vol.7 P.12-18 google doi
  • 48. Lavie N. 1995 Perceptual load as a necessary condition for selective attention. [Journal of Experimental Psychology: Human Perception and Performance] Vol.21 P.451-468 google doi
  • 49. Lavie N. 2000 Selective attention and cognitive control: Dissociating attentional functions through different types of load. In S. Monsell & J. Driver (Eds.), Control of cognitive processes: Attention and performance XVIII P.175-194 google
  • 50. Lavie N., Cox S. 1997 On the efficiency of visual selective attention: Efficient visual search leads to inefficient distractor rejection. [Psychological Science] Vol.8 P.395-396 google doi
  • 51. Lavie N., Tsal Y. 1994 Perceptual load as a major determinant of the locus of selection in visual attention. [Attention, Perception & Psychophysics] Vol.56 P.183-197 google doi
  • 52. Lehmkuhle S. W., Fox R. 1975 Effect of binocular rivalry suppression on the motion aftereffect. [Vision Research] Vol.15 P.855-859 google doi
  • 53. Leopold D. A., Logothetis N. K. 1996 Activity changes in early visual cortex reflect monkeys’ percepts during binocular rivalry. [Nature] Vol.379 P.549-553 google doi
  • 54. Levi D. M. 2008 Crowding-An essential bottleneck for object recognition: A minireview. [Vision research] Vol.48 P.635-654 google doi
  • 55. Lin Z., He S. 2009 Seeing the invisible: the scope and limits of unconscious processing in binocular rivalry. [Progress in Neurobiology] Vol.87 P.195-211 google doi
  • 56. Ling S., Blake R. 2012 Normalization regulates competition for visual awareness. [Neuron] Vol.75 P.531-540 google doi
  • 57. Liu T., Abrams J., Carrasco M. 2009 Voluntary attention enhances contrast appearance. [Psychological Science] Vol.20 P.354-362 google doi
  • 58. Luck S. J., Vogel E. K. 1997 The capacity of visual working memory for features and conjunctions. [Nature] Vol.390 P.279-280 google doi
  • 59. Lumer E. D., Friston K. J., Rees G. 1998 Neural correlates of perceptual rivalry in the human brain. [Science] Vol.280 P.1930-1934 google doi
  • 60. Mack A., Rock I. 1998 Inattentional blindness. google
  • 61. Marchetti G. 2012 Against the view that consciousness and attention are fully dissociable. [Frontiers in Psychology] Vol.3 P.1-14 google doi
  • 62. Meng M., Tong F. 2004 Can attention selectively bias bistable perception? Differences between binocular rivalry and ambiguous figures. [Journal of Vision] Vol.4 P.539-551 google doi
  • 63. Merikle P. M., Smilek D., Eastwood J. D. 2001 Perception without awareness:Perspectives from cognitive psychology. [Cognition] Vol.79 P.115-134 google doi
  • 64. Mitchell J. F., Stoner G. R., Reynolds J. H. 2004 Object-based attention determines dominance in binocular rivalry. [Nature] Vol.429 P.410-413 google doi
  • 65. Montagna B., Carrasco M. 2006 Transient covert attention and the perceived rate of flicker. [Journal of Vision] Vol.6 P.955-965 google doi
  • 66. Moore T., Armstrong K. M. 2003 Selective gating of visual signals by microstimulation of frontal cortex. [Nature] Vol.421 P.370-373 google doi
  • 67. Moradi F., Koch C., Shimojo S. 2005 Face adaptation depends on seeing the face. [Neuron] Vol.45 P.169-175 google doi
  • 68. Most S. B., Scholl B. J., Clifford E. R., Simons D. J. 2005 What you see is what you set: Sustained inattentional blindness and the capture of awareness. [Psychological Review] Vol.112 P.217-242 google doi
  • 69. Movshon J. A., Newsome W. T. 1992 Neural foundation of visual motion perception. [Current Directions in Psychological Science] Vol.1 P.35-39 google doi
  • 70. Nguyen V. A., Freeman A. W., Alais D. 2003 Increasing depth of binocular rivalry suppression along two visual pathways. [Vision research] Vol.43 P.2003-2008 google doi
  • 71. Nobre A. C. 2001 Orienting attention to instants in time. [Neuropsychologia] Vol.39 P.1317-1328 google doi
  • 72. Norman H. F., Norman J. F., Bilotta J. 2000 The temporal course of suppression during binocular rivalry. [Perception] Vol.29 P.831-841 google doi
  • 73. O’Connor D. H., Fukui M. M., Pinsk M. A., Kastner S. 2002 Attention modulates responses in the human lateral geniculate nucleus. [Nature Neuroscience] Vol.5 P.1203-1209 google doi
  • 74. Pestilli F., Carrasco M. 2005 Attention enhances contrast sensitivity at cued and impairs it at uncued locations. [Vision research] Vol.45 P.1867-1875 google doi
  • 75. Posner M. I. 1994 Attention: The mechanisms of consciousness. [Proceedings of the National Academy of Sciences] Vol.91 P.7398-7403 google doi
  • 76. Rees G., Kreiman G., Koch C. 2002 Neural correlates of consciousness in humans. [Nature Reviews Neuroscience] Vol.3 P.261-270 google doi
  • 77. Rensink R. A. 2002 Change detection. [Annual Review of Psychology] Vol.53 P.245-277 google doi
  • 78. Reynolds J. H., Chelazzi L., Desimone R. 1999 Competitive mechanisms subserve attention in macaque areas V2 and V4. [The Journal of Neuroscience] Vol.19 P.1736-1753 google
  • 79. Reynolds J. H., Heeger D. J. 2009 The normalization model of attention. [Neuron] Vol.61 P.168-185 google doi
  • 80. Riggs L. A., Whittle P. 1967 Human occipital and retinal potentials evoked by subjectively faded visual stimuli. [Vision Research] Vol.7 P.441-451 google doi
  • 81. Ross J., Morrone M. C., Goldberg M. E., Burr D. C. 2001 Changes in visual perception at the time of saccades. [Trends in Neurosciences] Vol.18 P.497-529 google
  • 82. Ruff C. C., Blankenburg F., Bjoertomt O., Bestmann S., Freeman E., Haynes J. D., Driver J. 2006 Concurrent TMS-fMRI and psychophysics reveal frontal influences on human retinotopic visual cortex. [Current Biology] Vol.16 P.1479-1488 google doi
  • 83. Schwartz S., Vuilleumier P., Hutton C., Maravita A., Dolan R. J., Driver J. 2005 Attentional load and sensory competition in human vision: Modulation of fMRI responses by load at fixation during task-irrelevant stimulation in the peripheral visual field. [Cerebral Cortex] Vol.15 P.770-786 google doi
  • 84. Shimojo S., Nakayama K. 1990 Real world occlusion constraints and binocular rivalry. [Vision Research] Vol.30 P.69-80 google doi
  • 85. Shin K., Stolte M., Chong S. C. 2009 The effect of spatial attention on invisible stimuli. [Attention, Perception & Psychophysics] Vol.71 P.1507-1513 google doi
  • 86. Shulman G. L. 2002 Two attentional processes in the parietal lobe. [Cerebral Cortex] Vol.12 P.1124-1131 google doi
  • 87. Simmons D. J., Ambinder M. S. 2005 Change Blindness: Theory and Consequences. [Current Directions in Psychological Science] Vol.14 P.44-48 google doi
  • 88. Sohn W., Papathomas T. V., Blaser E., Vidnyanszky Z. 2004 Object-based cross-feature attentional modulation from color to motion. [Vision research] Vol.44 P.1437-1443 google doi
  • 89. Soto D., Mantyla T., Silvanto J. 2011 Working memory without consciousness. [Current Biology] Vol.21 P.R912-R913 google doi
  • 90. Spivey M. J., Spirn M. J. 2000 Selective visual attention modulates the direct tilt aftereffect. [Attention, Perception & Psychophysics] Vol.62 P.1525-1533 google doi
  • 91. Sterzer P., Kleinschmidt A., Rees G. 2009 The neural bases of multistable perception. [Trends in Cognitive Sciences] Vol.13 P.310-318 google doi
  • 92. Stuit S. M., Cass J., Paffen C. L., Alais D. 2009 Orientation-tuned suppression in binocular rivalry reveals general and specific components of rivalry suppression. [Journal of Vision] Vol.9 P.1-15 google doi
  • 93. Thakral P. P., Slotnick S. D. 2010 Attentional inhibition mediates inattentional blindness. [Consciousness and Cognition] Vol.19 P.636-643 google doi
  • 94. Tong F., Meng M., Blake R. 2006 Neural bases of binocular rivalry. [Trends in Cognitive Sciences] Vol.10 P.502-511 google doi
  • 95. Treisman A. M. 1960 Contextual cues in selective listening. [Quarterly Journal of Experimental Psychology] Vol.12 P.242-248 google doi
  • 96. Ungerleider L. G., Mishkin M. 1982 Two cortical visual systems. In D. J. Ingle, M. A. Goodale, & R. J. W. Mansfield (Eds.), Analysis of Visual Behavior P.549-586 google
  • 97. Van Der Zwan R., Wenderoth P., Alais D. 1993 Reduction of a pattern-induced motion aftereffect by binocular rivalry suggests the involvement of extrastriate mechanisms. [Visual Neuroscience] Vol.10 P.703-703 google doi
  • 98. von Helmholtz H. 1925 Treatise on Physiological Optics. google
  • 99. von Helmholtz H. 1925 Treatise on physiological optics (Vol. 3; J. P. C. Southall, Trans.). google
  • 100. Wales R., Fox R. 1970 Increment detection thresholds during binocular rivalry suppression. [Attention, Perception & Psychophysics] Vol.8 P.90-94 google doi
  • 101. Whitney D., Levi D. M. 2011 Visual crowding: A fundamental limit on conscious perception and object recognition. [Trends in Cognitive Sciences] Vol.15 P.160-168 google doi
  • 102. Wiesenfelder H., Blake R. 1990 The neural site of binocular rivalry relative to the analysis of motion in the human visual system. [The Journal of Neuroscience] Vol.10 P.3880-3888 google
  • 103. Wong E., Weisstein N. 1982 A new perceptual context-superiority effect: Line segments are more visible against a figure than against a ground. [Science] Vol.218 P.587-589 google doi
  • 104. Wyart V., Tallon-Baudry C. 2008 Neural dissociation between visual awareness and spatial attention. [The Journal of Neuroscience] Vol.28 P.2667-2679 google doi
  • 105. Yantis S., Schwarzbach J., Serences J. T., Carlson R. L., Steinmetz M. A., Pekar J. J., Courtney S. M. 2002 Transient neural activity in human parietal cortex during spatial attention shifts. [Nature Neuroscience] Vol.5 P.995-1002 google doi
  • 106. Zhang P., Jamison K., Engel S., He B., He S. 2011 Binocular rivalry requires visual attention. [Neuron] Vol.71 P.362-369 google doi
이미지 / 테이블
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  • [ Figure 1. ]  Perceptual quality of stimuli projected to the level of consciousness
    Perceptual quality of stimuli projected to the level of consciousness
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