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Experimental task of Experiment 1. A referent stimulus was presented at the beginning of each trial, then pupil size was manipulated using a lowand high-load memory task. Feedback was given immediately after every response (or after a timeout) on the memory test. Judgment of the luminance level of the tester stimulus was done at the end of the trial.
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When the pupil dilates, the amount of light that falls onto the retina increases. However, in daily life, this does not make the world look brighter. Here we asked whether pupil size (resulting from active pupil movement) influences subjective brightness in the absence of indirect cues that, in daily life, support brightness constancy. We measured...
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... Experiment 1, participants indicated whether a tester stimulus was brighter or darker than a previously presented referent stimulus ( Figure 1). To manipulate pupil size, participants performed a visual-working-memory task in between the presentation of the referent and the tester stimuli; we varied the working-memory load, because previous studies have shown that the pupil dilates with increasing working-memory load (Kahneman & Beatty, 1966;Unsworth & Robison, 2015). ...
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... Materials, and Procedure. Each trial started with a fixation dot presented for 1500 ms ( Figure 1). Luminance referent: Next, a referent stimulus, an aqua-coloured ring, was displayed for 2000 ms. ...
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... found extremely decisive evidence for an effect of display colour on brightness judgments, BF 10 = 178565.872. As shown in Figure 10 (left panel), the sigmoid's midpoint in the blue condition (M x0 = 0.585, SD = 0.044) shifted to the left, compared to the one in the red condition (M x0 = 0.702, SD = 0.078). This indicates that the luminance of the tester stimulus was overestimated when pupils were small (in blue condition) compared to when pupils were large (in red condition). ...
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... again found strong evidence for an effect of display colour on brightness judgments, BF 10 = 24.748. As shown in Figure 10 (right panel), the sigmoid's midpoint in the blue condition (M x0 = 0.616, SD = 0.076) shifted to the left, compared to the one in the red condition (M x0 = 0.745, SD = 0.098). As in Experiment 2a, this indicates that the luminance of the tester stimulus was overestimated when pupils were small (in the blue condition) as compared to when pupils were large (in the red condition). ...
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... findings from all experiments are summarised in Figure 11. Most observations are in the upperright quadrant of the figure, meaning that in most cases an increase in pupil size was associated with a decrease in perceived brightness. ...
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... Experiment 1, we also found that pupil size during the tester stimulus was larger after incorrect responses than after correct responses, a difference that was larger than that induced by memory load. It was very likely that negative feedback or prediction error increased emotional arousal, thus Figure 11. Results summary. ...
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Virtual reality (VR) headsets with an integrated eye tracker enable the measurement of pupil size fluctuations correlated with cognition during a VR experience. We present a method to correct for the light-induced pupil size changes, otherwise masking the more subtle cognitively-driven effects, such as cognitive load and emotional state. We explore...
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... At the PLR peak for the blue stimulus, the pupil diameter was 1.66 times larger than that for the red stimulus (Fig 4). Since the PLR is driven by known photoreceptors, such as rods, cones, and intrinsically photosensitive retinal ganglion cells (ipRGCs) [41], all of which have different sensitivity characteristics [42], the amplitude of the PLR to red/blue stimuli is known to differ [43]. Szabadi et al. reported that short-wavelength light is more effective than isoluminant long-wavelength light in evoking the PLR because of the stimulation of melanopsin-containing photoreceptors [26]. ...
... Notably, recent studies suggest that the PLR is not merely a reflex to brightness, but also affected by higherorder factors [42]. As a matter of fact, pupil size also fluctuates according to hue (e.g., [26][27][28]43]), and even illusory brightness and subjectively perceived luminance (e.g., [52][53][54]). Furthermore, Kinzuka et al. recently reported that temporal perception is also modulated by the illusory brightness of a glare illusion (a visual illusion that enhances perceived brightness without changing physical luminance) [25], resulting in a different PLR response during the to-be-timed stimuli presentation [55,56]. ...
As time plays a fundamental role in our social activities, scholars have studied temporal perception since the earliest days of experimental psychology. Since the 1960s, the ubiquity of color has been driving research on the potential effects of the colors red and blue on temporal perception and on its underlying mechanism. However, the results have been inconsistent, which could be attributed to the difficulty of controlling physical properties such as hue and luminance within and between studies. Therefore, we conducted a two-interval duration-discrimination task to evaluate the perceived duration of color stimuli under different equiluminant conditions: subjective or pupillary light reflex (PLR)-based equiluminance. The results, based on psychometric functional analyses and simultaneous pupillary recordings, showed that the perceived duration of red was overestimated compared with blue even when the intensity of the stimulus was controlled based on subjective equiluminance (Experiment 1). However, since blue is known to induce a larger PLR than red despite equiluminance, we conducted a controlled study to distinguish the indirect effect of pupillary response to temporal perception. Interestingly, the effect observed in Experiment 1 faded when the luminance levels of the two stimuli were matched based on PLR response (Experiment 2). These results indicate that duration judgement can be affected not only by the hue but also by different equiluminance methods. Furthermore, this causality between the equiluminance method and temporal perception can be explained by the fluctuations in incident light entering the pupil.
The size of the eyes' pupils determines how much light enters the eye and also how well this light is focused. Through this route, pupil size shapes the earliest stages of visual processing. Yet causal effects of pupil size on vision are poorly understood and rarely studied. Here we report the effects of both experimentally induced and spontaneous changes in pupil size on visual processing as measured through EEG. We compare these to the effects of stimulus intensity and covert visual attention. Previous studies have shown that these factors all have comparable effects on some common measures of early visual processing, such as detection performance and steady-state visual evoked potentials; yet it is still unclear whether these are superficial similarities, or rather whether they reflect similar underlying processes. Using a mix of neural-network decoding, ERP analyses, and time-frequency analyses, we find that induced pupil size, spontaneous pupil size, stimulus intensity, and covert visual attention all affect EEG responses, mainly over occipital and parietal electrodes, but--crucially--that they do so in qualitatively different ways. Induced and spontaneous pupil-size changes mainly modulate activity patterns (but not overall power or intertrial coherence) in the high-frequency beta range; this may reflect a causal effect of pupil size on oculomotor activity and/ or visual processing. In addition, spontaneous (but not induced) pupil size tends to correlate negatively with alpha-band power and positively with intertrial coherence; this may reflect a non-causal relationship, mediated by arousal. Taken together, our findings suggest that pupil size has qualitatively different effects on visual processing from stimulus intensity and covert visual attention. This shows that pupil size causally affects visual processing, and provides concrete starting points for further study of this important yet understudied earliest stage of visual processing.
As an important index in studies on vision and display technology, pupil size controls the amount of the light entering human eye. Eye tracking systems are normally used to measure the pupil size while a pupil size estimation model can be applied when actual measurement is not available. The weighting functions of the reported pupil size estimation models show radial symmetry, which contradicted the radial asymmetric distribution of photoreceptors on the retina. Chromaticity spatial distribution has not been taken into consideration either. In this paper, the perceptual experiments are carried out with patterned and colored stimuli to evaluate the spatial and color varying effect of luminance to the pupil. A revised corneal flux density is proposed, which shows a high correlation with pupil diameters. Based on this, a pupil size estimation model is proposed. Pupil diameters can be calculated after inputting luminance and chromaticity spatial distribution matrixes. After verification, this model can be applied to indoor scenes with different lighting temperatures within the general illumination range. This model should be useful in scientific and practical applications where pupil diameter matters. To obtain the pupil diameter by inputting the luminance and chromaticity distribution, the perceptual experiments are carried out by us with patterned and colored stimuli to evaluate the spatial and color‐varying effect of luminance on pupil size. A revised corneal flux density is proposed, which shows a high correlation with pupil diameters.
