Bowdoin Science Journal

Psychology and Neuroscience

Pupil Mimicry Strengthens Infant-Parent Bonding

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Sometimes, it is a wonder how something so small can connect human beings on a deeper level, but that is what pupil mimicry does. Pupil mimicry describes the changes in pupil size that occur in both participants during eye contact, which can help with social bonding. It also reflects the different cognitive and emotional processes that occur during eye contact and socialization, such as showing social interest (Aktar et al., 2020). When pupil size synchronously dilates, meaning the pupil expands when eye contact is made, there is a promotion of trust and bonding between the two responders. The opposite is true for synchronous pupil constriction, which diminishes a positive social bond between the two responders.  

Pupil mimicry is an old, robust phenomenon (Prochazkova et al., 2018) that is modulated by oxytocin. This evolutionarily conserved neuropeptide acts as a hormone and neurotransmitter and facilitates social bonding (Aktar et al., 2020). Pupil mimicry has been observed in monkeys and chimpanzees, where it also increases trust and social familiarity (Kret et al., 2014). This effect occurs in infants as well, which suggests that pupil mimicry may help facilitate bonding between infants and their parents. But how can scientists measure that? 

It has been shown that young infants can differentiate between their own-race faces and other-race faces. Therefore, scientists hypothesized that infants would have quicker pupillary responses to pupils belonging to the same race as their parents when compared to other races. Researchers Aktar, Raijmakers, and Kret conducted a study with three aims to test this hypothesis: 

  1.  Do infants’ pupils react to dynamic videos of eyes with pupil sizes that change realistically? 
  2. Do parents and infants have the same speed in matching pupil size? 
  3. Do both the parents’ and infants’ pupils have differing rates of pupil mimicry between own-race faces and other-race faces

For the first aim, infants and parents watched black-and-white dynamic videos of same-race models (Dutch male and female) that had constricting, static, or dilating pupils while their pupillary reactions were tracked (Figure 1; Aktar et al., 2020). For the second and third aims, infants and parents watched black-and-white dynamic videos with two races: Dutch for the same-race category and Japanese for the other-race category (Aktar et al., 2020). The researchers compared the parents’ pupil mimicry speed to the infants’. 

Figure 1: Experimental set-up of infants and parents as they observe the stimuli (Aktar et al., 2020).

The researchers confirmed that both infants and parents were able to perform pupil mimicry. They also found that parents had quicker pupil response to dilated or constricted pupils than infants, possibly due to adults being more cognitively advanced than infants. Finally, they concluded that there was no significant difference in pupil mimicry response between own race and other races, but there were slight pupil mimicry delays. The researchers have several explanations for the slight delays. For instance, the infants’ pupils tend to stay dilated when they see a dilated pupil, regardless of race, since infants are still developing their pupil mimicry control. For adults, pupil mimicry tends to take about 2.5 milliseconds longer when given other-race stimuli. This may be from greater cognitive effort used to process other-race faces than own-race faces (Aktar et al., 2020). 

The key finding of the research is race does not affect the participants’ rate of pupil mimicry during emotionally neutral interactions (Aktar et al., 2020). So, though pupil mimicry helps strengthen parent-infant relationships, infants also have the skills to establish trust and awareness with strangers regardless of race. However, when infants are not in a neutral setting, meaning an environment where they feel unsafe and discontent, they are more likely to seek out their parents and less likely to make eye contact (Aktar et al., 2020). That is why, if the infants felt fussy or frightened, the researchers sat the parents right next to them to provide a feeling of safety (Figure 1). Eye contact conveys a great deal of information. Maybe the next time you make eye contact with someone, stare at them to see how their pupil responds to you!

References

Aktar, E., Raijmakers, M. E. J., & Kret, M. E. (2020). Pupil mimicry in infants and parents. Cognition and Emotion, 34(6), 1160–1170. https://doi.org/10.1080/02699931.2020.1732875

Kret, M. E., Tomonaga, M., & Matsuzawa, T. (2014). Chimpanzees and humans mimic pupil-size of conspecifics. PloS one, 9(8), e104886. https://doi.org/10.1371/journal.pone.0104886

Prochazkova, E., Prochazkova, L., Giffin, M. R., Scholte, H. S., De Dreu, C. K. W., & Kret, M. E. (2018, July 16). Pupil mimicry promotes trust through the theory-of-mind network – PNAS. Proceedings of the National Academy of Sciences. https://www.pnas.org/doi/10.1073/pnas.1803916115

Caution in STEM: Inhibition, Intuition, and Counterintuitive Reasoning

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Imagine you’re on a 1950s game show. The host presents three doors and lays out the rules: Behind one door is a car, and behind the other two are goats. After you choose a door, the host, knowing what’s behind each door, opens one of the remaining two doors, revealing a goat. You have the opportunity to switch. Do you?

This is, of course, the infamous Monty Hall problem. Assuming you prefer the car over the goat, the answer is to always switch, since it will give you double the probability—⅔ rather than ⅓—of winning the car. Here’s an explanation that goes through each possible case (Table 1):

Table 1: Possible outcomes for staying and switching in the Monty Hall problem (Saenen et al., 2018)

If you got it wrong, you’re not alone—between 79% and 87% of adults get it wrong, too (Saenen et al., 2018). But what is behind this phenomenon? Solving unintuitive problems like the Monty Hall problem is thought to require the inhibition of misleading information, such as from prior knowledge or false cues (Dumontheil et al., 2022; Saenen et al., 2018). However, a 2018 study by Brookman-Byrne et al. and a 2022 study by Dumontheil et al. shine a new, more nuanced light on the connection between inhibitory control and (counter)intuition.

Both studies had British schoolchildren aged 11-15 undergo a volley of tests assessing their response inhibition (the ability to manage and filter out conflicting information), semantic inhibition (the ability to suppress responses driven by impulse ), vocabulary, reasoning, and working memory. Researchers then had participants complete a set of intuitive (control) and counterintuitive math and science problems. Dumontheil et al. (2022) measured neural activity using fMRI (functional Magnetic Resonance Imaging, an imaging technique which measures blood-oxygen levels to determine which parts of the brain are active) throughout.

Unsurprisingly, researchers consistently found that participants were more accurate and faster in solving intuitive problems than counterintuitive problems. Furthermore, in counterintuitive reasoning, response inhibition predicted response times, whereas semantic inhibition predicted accuracy. Interestingly, however, the only predictors of counterintuitive reasoning ability found in both studies were a more extensive vocabulary and increased age, both of which also predicted response inhibition (Brookman-Byrne et al., 2018; Dumontheil et al., 2022). Given these unexpected findings, neuroimaging results by Dumontheil et al. (2022) were necessary to provide some insight into what goes on in participants’ brains. 

Figure 1: Brain regions showing greater activation for (A) counterintuitive versus control (intuitive) problems, (C) response inhibition versus no response inhibition, and (D) semantic inhibition versus no semantic inhibition (Dumontheil et al., 2022). 

Figure 2: A comparison between areas showing increased activation during counterintuitive reasoning and (A) complex inhibition behavior, and (B) interference control behavior (Dumontheil et al., 2022). 

Since the overlap is limited in Figure 2, researchers concluded that the relationship between inhibitory control and counterintuitive problem solving was not direct (Dumontheil et al., 2022). They posit that the role of inhibition in counterintuitive reasoning may be limited to specific types of inhibition. In particular, semantic inhibition might be a better explanation than just response inhibition (Dumontheil et al., 2022). 

Neurosynth (an fMRI image database) also associates areas activated during counterintuitive reasoning with “working memory,” “calculation,” “symbolic,” “attention,” “visually,” and “spatial,” suggesting that inhibition is not the only factor at play (Dumontheil et al., 2022). They highlight that two areas known as the intraparietal sulcus (IPS) and Brodmann area 7 (BA 7)—which together are responsible for visuo-spatial attention—show increased activation during counterintuitive reasoning, response inhibition, and semantic inhibition (Dumontheil et al., 2022). Hence, they also suggest that visuo-spatial attention may be another factor in counterintuitive reasoning (Dumontheil et al., 2022). 

So what does this mean, practically? For educators, it seems that curriculum design in STEM should not be done in isolation. Given the impact of semantic reasoning, it would be prudent to balance training in purely symbolic reasoning with training in semantic reasoning (e.g., by requiring humanities classes be taken with STEM classes). For cognitive neuroscientists, this research suggests that there may be another dimension to understanding counterintuitive reasoning: the complex causal relationships between visuo-spatial attention, inhibitory control, and counterintuitive reasoning. Indeed, this is a cautionary tale about the importance of inhibition in science itself—causation is difficult to establish, and the most intuitive models in science may not always be right, either.

 

References

Brookman-Byrne, A., Mareschal, D., Tolmie, A. K., & Dumontheil, I. (2018, June 21). Inhibitory control and counterintuitive science and maths reasoning in adolescence. PLoS ONE, 13(6), 1-19. https://doi.org/10.1371/journal.pone.0198973

Dumontheil, I., Brookman-Byrne, A., Tolmie, A. K., & Mareschal, D. (2022). Neural and Cognitive Underpinnings of Counterintuitive Science and Math Reasoning in Adolescence. Journal of Cognitive Neuroscience, 34(7), 1205. https://doi.org/10.1162/jocn_a_01854

Saenen, L., Heyvaert, M., Van Dooren, W., Schaeken, W., & Onghena, P. (2018). Why Humans Fail in Solving the Monty Hall Dilemma: A Systematic Review. Psychologica Belgica, 58(1), 128-158. https://doi.org/10.5334/pb.274