Read this? Your brain is already deciding when to blink next

Read this? Your brain is already deciding when to blink next

How do you know when to blink? A study shows that blinking does more than just keep your eyes moist. Your brain times your blinks around sentences, surprises and the flow of a story.

Study:The timing of spontaneous eye blinks during text reading suggests a cognitive role. Photo credit: Doucefleur/Shutterstock.com

Ghent University published a study inScientific reportsThis identified the cognitive role of spontaneous eyes during text.

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Spontaneous eye blinks are involuntary eye movements that are not a reflex reaction. This involuntary blinking is crucial to lubricate the eyes and prevent them from drying out. In humans, the average eye blink rate is 15 blinks per minute. However, the rate changes with age and varies between individuals.

Blinking is linked to the brain's cognitive processing. In addition to biological needs, a reduction in blink rate has been observed in tasks with high cognitive demands such as driving or controlling air traffic.

Performing tasks with high cognitive demands requires increased attention, which is associated with a reduced blink rate. Similar effects were observed when processing purely auditory information. These results suggest that eye blinks serve as content-sensitive markers regardless of the type of sensory information. Blinks are unconsciously regulated by attentional mechanisms to optimize task performance.

Existing evidence suggests that spontaneous eye blinks are reduced during memorable scenes in a movie and increased during attentional components, e.g. B. the conclusion of an action or repeated presentations of a similar scene. This suggests that spontaneous blinking is not only a physiological necessity but also actively linked to the content of the scene.

In the current study, researchers wanted to investigate whether spontaneous eye blinking plays a cognitive role during text reading.

The study

The researchers analyzed data from the large corpus (Ghent Eye Tracking Corpus), which contains data movement data from 15 participants who silently read an entire novel. The GECO was originally designed for general eye movement research and not specifically for blink analysis, so blink events were extracted from the raw eye tracking data. They specifically assessed the effects of punctuation marks, word frequency, and word predictability on flashing patterns.

Punctuation marks indicate the end of a sentence or a pause in a sentence. The researchers hypothesized that these markings could be components of attention during fluent reading and could influence the blinking pattern. They also hypothesized that word frequency and predictability may influence blinking patterns, as the presence of unusual or unexpected words in a text has been observed to increase cognitive demand.

Statistical models, including beta regression for text position effects and mixed effects logistic regression, were used to assess how word frequency and word predictability influenced the likelihood of blinking. To avoid confusion with function words, only content words were used in the word frequency and predictability analysis.

Study results

The study reported a significantly higher spontaneous blink rate around punctuation marks than other random text positions. An increased probability of blinking was also observed at the end of a sentence or around positions where character symbols and line endings coincide.

Regarding word frequency and predictability, the study reported a significant reduction in blink rate while reading words that occur more frequently in text. In contrast, unexpected or surprising words significantly increased blink rates.

The analysis also revealed a significant interaction between word frequency and predictability. The effect of word predictability was most pronounced for high-frequency words. This means that when readers encounter a word that is typically common but appears in an unpredictable or surprising word context, the likelihood of blinking even more than a rare word increases.

Not all differences between punctuation types were statistically significant, but overall all punctuation types were associated with higher blink rates than random positions in the text.

Investigate significance

The study highlights the significant cognitive role of spontaneous eye blinking during text reading. Specifically, it identifies punctuation marks, word frequency, and word predictability as key drivers of flashing patterns in reading.

As the researchers noted, this work serves as a much-needed contemporary follow-up to the original pioneering study that examined blink rates during reading using a manual blink count.

Loss of perceptual information when blinking is inevitable. It is generally believed that the brain regulates the blinking frequency during reading to avoid possible loss of information. The observed reduction in blink rate (10 blinks per minute) compared to the commonly established blink rate (15 blinks per minute) justifies this hypothesis.

The study finds an induction in blinking rates around punctuation marks, which may reflect a reduction in incoming information load and attentional demands. This justifies a possible connection between spontaneous blinking and cognitive processing.

The study also found a reduction in blink rates when reading high-frequency and predictable words. The word frequency effect indicates that high-frequency words are cognitively less demanding and require lower-level cognitive processing than low-frequency words. Similarly, the word predictability effect suggests that common (predictable) words require less cognitive processing than unexpected or unusual words.

The interaction effect suggests that predictability issues, particularly for frequent words, are important, adding a layer of nuance to previous findings. Both effects collectively demonstrate that spontaneous eye blinking plays an essential cognitive and attentional role during text comprehension.

While analyzing the dataset, researchers looked at the most recorded blink events to represent real blinks. However, it remains possible that some of the recorded blink events result from short-term data loss or recording errors. Although unlikely to significantly impact study results, these incidents may introduce additional data.

Another limitation is that the original dataset was not explicitly designed for Blink research, which may have introduced further sources of noise or bias. However, big data analysis is likely to mitigate the impact of such factors.

Several studies have suggested blinks as a potential tool for studying perception and related mental processes such as attention. However, few studies have scientifically suggested that blinking can be used to study cognitive processes, particularly during reading. Given the results of the current studies, researchers encourage further exploration of this possibility in future research.

They also suggest that future work could examine whether blink rates are influenced by other text features or subjective boundaries in narrative structure, as observed in video ad studies.

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