Guide Blinking

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Excessive eye blinking can be stressful and hard to ignore. Many things can cause it, but once the cause is identified, there is usually an.
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Humans also tend to look into each other's eyes during a conversation. The authors of the recent study believe that blinking conveys a message that we can subconsciously read and understand. The researchers theorized that if blinks do carry information, altering their duration might make a difference to how an individual involved in a conversation might behave. For their experiment, the scientists used virtual reality. Participants talked to an avatar that acted as a "virtual listener. The avatar, when "listening" to responses, would nod along in a manner modeled on real-life conversations.

For some of the sessions, the avatar's blinks were short, lasting milliseconds. For others, they were longer, lasting milliseconds. The durations were based on blinks measured in standard conversations, so neither were unusual. When asked, the participants did not perceive any differences between the blink durations, but subconsciously, they do seem to have taken note. When the avatar's blinks were longer, the participants' answers were several seconds shorter. This gives weight to the scientists' theory that blinking is another type of nonverbal clue that plays a part in conversations.


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The authors believe that a longer blink may signify understanding. They conclude:. Many of us do not give blinking much thought, but scientists have pondered its function over the years. For instance, studies have shown that we blink more when we are experiencing a high cognitive load than when our brains are not being taxed.

Reduced and incomplete blinking along with increased tear film break-up during normal visual tasks may explain the increased level of ocular discomfort symptoms reported at the end of the day, particularly in dry eye patients. National Center for Biotechnology Information , U. Didn't get the message? Find out why Add to Clipboard. Add to Collections. Order articles. Fetching bibliography The distinction between affective and physical events was important to the experimental design because the children who watched the video were divided into two groups that vary in their response to affective and physical cues 28 , The video was shown to 41 two-year-olds with autism spectrum disorders ASD as well as 52 typical two-year-olds full clinical characterization data and procedures are provided in Table S1 and the SI Materials and Methods, Participants.

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Here, the children with ASD provide the critical comparison group because these children have been shown previously to display atypical patterns of visual attention to social interaction 30 , 31 , attenuated reactivity to varying social affect 32 , and lack of differential response to social attentional cues 28 but also intact response to physical attentional cues 28 , 29 and intact ability to predict and attend to physical events 31 , 33 , In the current experimental paradigm, we tested blink inhibition as a marker of perceived stimulus salience, varying by group membership.

We first examined overall blink rate and blink duration to test for physiological differences in eye-blink behavior between toddlers with ASD and typical toddlers. Eye movement data were collected at the rate of 60 Hz, and blinks were recorded as events with a measurable duration, identified by an automated algorithm, supplemented and verified by simultaneous video recording in all participants, and separately verified by simultaneous electromyography recordings in one adult viewer [complete details are provided in SI Materials and Methods, Data Acquisition and Analysis and are described in the study by Jones et al.

Mean blink rate and blink rate in relation to age. A No difference was found in blink rate bpm between toddlers with ASD and typical toddlers analysis performed on log-transformed data; bars are untransformed data, error bars are SEM. We next tested explicitly our anecdotal observation of variation in blink rate during the intertrial intervals before and after each experimental trial the video scene Fig.

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During these intervals, a centering cue was presented on an otherwise blank screen to draw the attention of viewers to a common fixation location. Based on our earlier observations, we predicted that blink rate would decrease during the experimental trial relative to intertrial intervals. Task-dependent modulation of blinking.

A We measured individual blink rates before, during, and after experimental trials. B Mean blink rate of both toddlers with ASD and typical toddlers decreased during the experimental trial relative to pre- and posttrial periods error bars are SEM. As shown in Fig. We next tested whether instantaneous blink rate was significantly modulated during the video itself Fig. Individual data were recorded as Hz time series with binary values at each point in the series indicating whether a given individual was blinking or not. Instantaneous blink rate was computed across all individuals for each group complete details are provided in SI Materials and Methods, Instantaneous Blink Rate.

To test the null hypothesis that the timing of blink inhibition was unrelated to scene content, we used permutation testing In each of 1, iterations, for each group, the binary times series blink data for each child were permuted by circular shifting 39 , with shift size for each child drawn independently from a random number generator with uniform distribution.

Instantaneous blink rate was then calculated across the shifted individual data. By this approach, in the permuted data, the mean blink rate of participants during the entire task remains unchanged and task-specific but the timing of when instantaneous blink rate is increased or decreased is made random. Instances of statistically significant blink inhibition during natural viewing of a video scene. A Raster plot of eye blinks made by typical toddlers. B Instantaneous blink rate bpm of typical toddlers while viewing the movie.

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C Fifth and 95th percentiles of permuted blink data. Periods of statistically significant blink inhibition were identified as times when the actual blink rate was less than the fifth percentile of permuted data. A — D Twenty-eight-second excerpt from video data is shown. In contrast, in the actual data, we found that the blink rate for typical toddlers was significantly inhibited exhibiting values less than the 0.

Having confirmed that blinking was inhibited at levels greater than expected by chance and inhibited at specific times during unconstrained viewing of natural scenes, we next tested whether blink inhibition varied selectively with respect to video content, visual fixation, and viewer group.


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As described above, the experimental paradigm presented two categories of content affective and physical events to two populations of children known for differential attention to those categories children with ASD and typical toddlers. In the video shown to participants, the boy in the video desires to leave the wagon door open, whereas the girl wants it to be closed; this scenario conveniently created varying levels of affective content the discord between the boy and the girl and a repeated physical action the closing or opening of the wagon door.

Physical events were operationalized as times when the wagon door was moving complete details of all rating procedures are provided in SI Materials and Methods, Ratings of Affective and Physical Events. The two event types were not mutually exclusive but, per the independent raters, overlapped less than The remaining segments of the video were classified as nonaffective nonphysical events. We predicted that viewers would inhibit their blinking during moments perceived to be particularly important to process and would increase their blinking during moments perceived to be less important.

PSTHs were constructed by aligning segments of individual time series blink data to the onset of events and by then computing counts of an individual's blinks occurring in Bin counts were computed for each participant across all events and then averaged across all participants to obtain group means. To test whether the observed changes in blink rate differed from those expected by chance, we computed a second set of PSTHs from permuted blink data.

As before, individual blink sequences were permuted by circular shifting of individual data 1, times PSTHs were then computed on each of those permuted datasets. The mean instantaneous blink rate, during each bin, across all 1, PSTHs from permuted data quantified the blink rate one would observe if blink rate were random with respect to onscreen events. If, on the other hand, blink rate were time-locked to onscreen events and not random, one would expect to see significant deviations from the permuted data distribution.

To test for between-group differences, we computed confidence intervals CIs of bootstrapped data for each group Toddlers with ASD also show a reduction in blink rate Time-locked blinks and blink inhibition during natural viewing, together with example visual fixation data. We measured time-locking of blinks and blink inhibition relative to affective events A and G , physical events B and H , and nonaffective nonphysical events C and I by constructing PSTHs. PSTHs show the percent change in bpm relative to the mean of permuted blink data. Dashed horizontal lines mark 0.

The Importance of Blinking - Vermont Eye Laser

CIs scale inversely with the number of events with approximately double the number of events in the nonaffective nonphysical category. Absolute minimum and maximum changes in bpm are highlighted by black squares in each plot. Example visual fixation data during change in blink rate for affective D and J , physical E and K , and nonaffective nonphysical F and L events. Data from typical toddlers show greater density of fixations on people during both affective D and physical E events, whereas data from toddlers with ASD show greater density of fixations on the wagon door J and K.

Three column plots show a still frame from the video first column, sampled at the absolute minimum decrease in bpm ; kernel density plot of fixation data at the same moment second column, with hotter colors denoting greater density ; and the same kernel density plot scaled from black to transparent, overlaid on the original frame third column. The color of fixation density plots is scaled relative to the sample size of each group, such that maximum and minimum possible densities have the same color values for each group despite differences in sample size.

M Timing of blink inhibition for affective vs.

N Percent decrease in bpm for affective vs. O Percent fixation on objects for affective vs. Error bars are SEM. The between-group difference in timing is highly significant, because the CIs of bootstrapped lag data for each group are nonoverlapping Fig. Each group shows a numerical, although not statistically significant, reduction in blink rate by event type Fig.

The Importance of Blinking

Both groups of toddlers show a significant increase in blink rate relative to nonaffective nonphysical events Fig. Helping to disambiguate the question of differential engagement is the pattern of each group's visual fixations during the two event types Fig. Paired-samples t tests confirmed that typical toddlers showed no difference in percentage of fixation on objects during affective vs.

In contrast, for toddlers with ASD, blink inhibition was i most reduced after the zero lag of events, ii numerically greater for physical rather than affective events, and iii marked by a significant increase in fixation on objects during physical events. These data indicate that children as young as 2 y of age inhibit their blinking to maximize access to visual information that they perceive to be important.


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  7. Of particular interest to our laboratory, the patterns of blink inhibition and the distribution of visual fixations map onto well-established between-group differences 30 , 31 , 33 but also reveal more subtle differences in the subjective assessment of stimulus salience. When the data were time-aligned to scenes of heightened affective content Fig.

    Toddlers with ASD, in contrast, exhibited a peak in blink inhibition that occurred more than 0. That typical toddlers inhibit their blinking earlier than toddlers with ASD suggests the intriguing possibility that typical toddlers are actively anticipating the unfolding of salient events, and doing so in a time-locked fashion.

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    The visual fixation data tell a similar story: Toddlers with ASD look more at physical objects in the video scene and selectively increase their fixation on those objects when the objects move that is, during the designated physical events. Critically, the ASD data show no evidence of more general delays in speed or frequency of eye movements: There are no between-group differences in duration or frequency of fixations, or differences in frequency of saccades or latency to initiate a first saccade at the onset of the movie.