Disrupting Parietal Function Prolongs Dominance Durations in Binocular Rivalry

Zaretskaya, Natalia; Thielscher, Axel; Logothetis, Nikos K.; Bartels, Andreas

doi:10.1016/j.cub.2010.10.046

Cited by 112 publications

(158 citation statements)

References 37 publications

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“…6) is consistent with earlier neuroimaging (7-9), electrophysiological (11), TMS (13)(14)(15), and neuropsychological (16)(17)(18) findings suggesting that frontoparietal regions might initiate perceptual switching. To the extent that the attentional load might be larger during perceptual switching than maintenance, these results are also consistent with previous GC results on visual spatial attention (34).…”

Section: Top-down Vs Bottom-up Influences During Perceptual Switchinsupporting

confidence: 80%

“…Firstly, frontal and parietal brain regions seem to be involved in perceptual switching, as demonstrated by neuroimaging (7-11) (but see ref. 12) as well as transcranial magnetic stimulation (TMS) (13)(14)(15) and lesion (16)(17)(18) studies. Secondly, functional MRI (fMRI) activity patterns in visual regions, including the primary visual cortex (V1) and lateral geniculate nucleus (LGN), correlate with the content of fluctuating percepts, as reflected in both activity fluctuations of an entire brain region (19)(20)(21)(22)(23)(24) and the fine spatial patterns of activity within a region (25)(26)(27).…”

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confidence: 99%

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Brain mechanisms for simple perception and bistable perception

Wang

Arteaga

2013

Proc. Natl. Acad. Sci. U.S.A.

118

101

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When faced with ambiguous sensory inputs, subjective perception alternates between the different interpretations in a stochastic manner. Such multistable perception phenomena have intrigued scientists and laymen alike for over a century. Despite rigorous investigations, the underlying mechanisms of multistable perception remain elusive. Recent studies using multivariate pattern analysis revealed that activity patterns in posterior visual areas correlate with fluctuating percepts. However, increasing evidence suggests that vision-and perception at large-is an active inferential process involving hierarchical brain systems. We applied searchlight multivariate pattern analysis to functional magnetic resonance imaging signals across the human brain to decode perceptual content during bistable perception and simple unambiguous perception. Although perceptually reflective activity patterns during simple perception localized predominantly to posterior visual regions, bistable perception involved additionally many higher-order frontoparietal and temporal regions. Moreover, compared with simple perception, both top-down and bottom-up influences were dramatically enhanced during bistable perception. We further studied the intermittent presentation of ambiguous images-a condition that is known to elicit perceptual memory. Compared with continuous presentation, intermittent presentation recruited even more higher-order regions and was accompanied by further strengthened top-down influences but relatively weakened bottom-up influences. Taken together, these results strongly support an active top-down inferential process in perception.visual perception | fMRI | MVPA | Granger causality | ambiguous images T he problem of vision entails the constant interpretation of inherently ambiguous local components of a complex scene. In contrast to reduced visual stimuli routinely used in laboratory research such as Gabor patches and isolated faces, natural scenes contain many ambiguities caused by clutter, occlusion, shading, and the inherent complexity of natural objects (1, 2). Similarly, simple daily tasks, such as interpreting the handwriting of another individual, require a level of cognitive capability surmounting that of modern-day computers. The ease with which we are able to rapidly perform such tasks attests to the remarkable capacity of the human visual system, or alternatively, to the vast knowledge and templates stored in the human brain aiding in visual perception (3).Ambiguous images such as the Necker cube and Rubin facevase illusion provide a well-controlled experimental approach to studying the brain's processing when it is faced with ambiguities in sensory inputs. When multiple interpretations of the same sensory inputs are possible, subjective perception alternates between the different interpretations in a stochastic manner (for reviews, see refs. 2 and 4-6). In the case of ambiguous images containing two possible interpretations, this phenomenon is referred to as "bistable perception."Neuroscientific studies of bis...

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Section: Top-down Vs Bottom-up Influences During Perceptual Switchinsupporting

confidence: 80%

mentioning

confidence: 99%

Brain mechanisms for simple perception and bistable perception

Wang

Arteaga

2013

Proc. Natl. Acad. Sci. U.S.A.

118

101

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“…These picture sets also provide a valid contribution to a better understanding of the neural correlates of perceptual rivalry using ambiguous or bistable figures, such as Rubin's face/vase, the duck/rabbit picture, or the Necker cube (Bonneh, Pavlovskaya, Ring, & Soroker, 2004;Britz et al 2009;Kleinschmidt et al 1998;Long & Toppino, 2004;Lumer et al 1998;Zaretskaya et al 2010). In contrast to ambiguous figures that continuously, spontaneously, and unpredictably alternate between two mutually exclusive interpretations, our picture sets provide more control as to when the switch occurs.…”

Section: Discussionmentioning

confidence: 98%

“…These stimuli have been used to explore numerous perceptual phenomena, including binocular rivalry (Blake & Logothetis, 2002;Meng & Tong, 2004), the influence of cues on perception (Panichello, Cheung, & Bar, 2013, for an overview), the ability of children to switch between the two interpretations (Doherty & Wimmer, 2005;Gopnik & Rosati, 2001; M.C. Wimmer & Doherty, 2011), the brain areas associated with perceptual switches (Britz, Landis, & Michel, 2009;Kleinschmidt et al 1998;Lumer, Friston, & Rees, 1998;Zaretskaya, Thielscher, Logothetis, & Bartels, 2010), and perceptual hysteresis (Hock et al, 1993). Similarly, studies using picture sets that morph from one unique object (e.g., a rabbit) to another (e.g., a duck), with various levels of ambiguity in between, have shown that pictures are perceived categorically (i.e., as either a duck or a rabbit, but not as an alternate, third object representing the gradual merging of both; Hartendorp et al 2010;Newell & Bülthoff, 2002;Verstijnen & Wagemans, 2004).…”

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confidence: 99%

Assessing perceptual change with an ambiguous figures task: Normative data for 40 standard picture sets

et al. 2015

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In many research domains, researchers have employed gradually morphing pictures to study perception under ambiguity. Despite their inherent utility, only a limited number of stimulus sets are available, and those sets vary substantially in quality and perceptual complexity. Here we present normative data for 40 morphing picture series. In all sets, line drawings of pictures of common objects are morphed over 15 iterations into a completely different object. Objects are either morphed from an animate to an inanimate object (or vice versa) or morphed within the animate and inanimate object categories. These pictures, together with the normative naming data presented here, will be of value for research on a diverse range of questions, from perceptual processing to decision making.

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“…Causally manipulating neural activity in these regions using transcranial magnetic stimulation (TMS) with continuous theta-burst stimulation decreases switch rate (Kanai et al 2010) showing that these areas play a causal role in generating perceptual switches. Moreover, applying TMS to a slightly more anterior part of parietal cortex has the opposite effect on switch rates in binocular rivalry (Carmel et al 2010;Zaretskaya et al 2010). Taken together this suggest a sophisticated model in with parietal (and perhaps prefrontal) cortices play a complex causal role in generating top-down signals that ultimately resolve perceptual competition in ventral visual cortex (Kanai et al 2011).…”

Section: Access To Consciousnessmentioning

confidence: 87%