One powerful infant behaviour that can be leveraged in developmental research is infants’ looking patterns. Studies of infants’ ability to group visual stimuli have revealed that young infants are sensitive to things like outlines, contrasts or shapes that can be used to form distinct categories such as cat and dog (Quinn, Eimas & Tarr, 2001). What these studies can’t tell us is what underlying neural processes are driving the emergence of such behaviours. For this, neuroimaging can complement the progress made in developmental psychology. It enables us to answer questions about when and where in the brain a capacity to distinguish a category is present and to chart this emergence in different brain regions. In adults, there are dedicated areas on the bottom – or ventral – surface that demonstrate reliable patterns of responses to the different objects we see in the world (Grill-Spector & Weiner, 2014). This series of brain regions is organised as a hierarchy, processing increasingly complex visual features, from low-level perceptual features such as orientation (Hubel & Wiesel, 1962) to more abstract groupings by semantic concept (Huth et al., 2012) or animacy (Konkle & Caramazza, 2013). Although infants’ looking preferences have been shown to align with these organising principles (Spriet et al., 2022), it remained unclear whether activity in these brain areas is present from an early age.

Beyond knowing when something becomes functional in the infant brain, we also would like to know exactly how this comes to be. What learning mechanisms are at play? Is it the kind of structured information that can be learned from the statistics of the environment, or is a strong innate prior required? For this, a computational model of learning would be useful. Indeed, a further benefit of studying the development of the visual system, in addition to the wealth of research on infant looking behaviour to which we can compare, is the existence of advanced computational models of vision. For example, we can use deep neural network models that learn how to recognise objects through a training process during which they see many images. After training, the model’s hierarchical layers map onto the ventral visual hierarchy, processing increasingly complex visual features similarly to the brain (Yamins et al., 2014). We wondered whether such models would also capture visual responses in the infant brain. If so, we could test if the infant brain might map onto models at an earlier stage of their training, or perhaps earlier layers of the model that process simpler features. We believed that if such models could effectively capture infant brain responses, this would open new avenues for building advanced computational models of infant brain development. Models whose learning can be tightly controlled may provide insights into the unique processing of the infant brain that we cannot determine from comparison to adults alone.

To answer these questions we needed rich, visual responses from the infant brain that are suitable for comparison with computational models. We therefore required data from a large cohort of awake infants as they viewed a variety of visual categories. Collecting high-quality neuroimaging data in infants comes with many challenges. MRI requires participants to refrain from moving, but we cannot ask babies to lie still. Participants may also become fussy if a particular task is not interesting, or they may fall asleep mid experiment. Despite these challenges, pioneering work in awake infant fMRI laid the foundations for what was possible in this space (Deen et al., 2017, Ellis et al., 2020). These studies provided evidence that category selectivity to faces, scenes and body parts is present from early infancy (Kosakowski et al., 2022), as is the basic structure of early visual regions that reflect where in our visual field we perceive an object (Ellis et al., 2021). Given this, we sought to characterise infants’ responses to a broader set of objects, including animate and inanimate categories such as cats, rubber ducks, and trees. This diverse set of objects allowed us to measure the fine-grained patterns of response required for comparison with deep neural network models.
For our study, 134 families generously took the time to participate when their newest family member was just 2 months of age (see Figure 1). We successfully collected awake fMRI data from 130 of these infants as they watched our visual stimuli in the scanner. Encouragingly, many infants engaged with the images depicting various objects. After careful data preprocessing and quality control for motion we had a final dataset of 101 2 month olds who completed this experiment. The same infants were also scanned at 9 months, which gave us a final sample of 44 at this age group. This dataset allowed us to robustly characterise developing infant brain responses in ways that were not previously possible. Using patterns of activity across a given brain region, we found that category structure is present by 2-months of age. Although early visual regions were the most mature, infants’ high-level visual regions were organised very similarly to adults. There was also distinct processing for categories that was reliable across different examples of the same object. Fascinatingly, the infants’ brain responses already aligned with the deepest layers of a neural network, indicating complex processing beyond simple visual features. This suggests that the structure that’s present at this age is as complex as that learned by a model that has seen millions of images and can accurately label many objects.

Figure 1. 2-month-old participant with their mother participating in the study.

In addition to revealing that category structure is present in the youngest minds, much earlier than previously appreciated, this work proved that we can compare advanced computational models to developing brains. This is very exciting, as it unlocks a new toolkit that developmental scientists can use to reveal the mechanisms of information processing and learning during infancy, laying the groundwork for the emerging field of developmental cognitive computational neuroscience. Deep neural network models provide a computational language for asking questions such as: what rules does the infant brain use to learn new information? What information can be learned from experience alone? Which properties of the developing brain rely on innate structure or genetically predetermined wiring? Deep neural networks allow us to explore these questions by varying the model architecture, the data on which we train, and the rules that the models use to learn. By combining behaviour, neuroimaging, and computational modelling to provide a holistic account of development, this brings us one step closer to answering the question: what is going on inside an infant’s mind?

Deen, B., Richardson, H., Dilks, D. D., Takahashi, A., Keil, B., Wald, L. L., … & Saxe, R. (2017). Organization of high-level visual cortex in human infants. Nature communications, 8(1), 13995.
Ellis, C. T., Skalaban, L. J., Yates, T. S., Bejjanki, V. R., Córdova, N. I., & Turk-Browne, N. B. (2020). Re-imagining fMRI for awake behaving infants. Nature Communications, 11(1), 4523.
Ellis, C. T., Yates, T. S., Skalaban, L. J., Bejjanki, V. R., Arcaro, M. J., & Turk-Browne, N. B. (2021). Retinotopic organization of visual cortex in human infants. Neuron, 109(16), 2616-2626.
Grill-Spector, K., & Weiner, K. S. (2014). The functional architecture of the ventral temporal cortex and its role in categorization. Nature Reviews Neuroscience, 15(8), 536-548.
Hubel, D. H., & Wiesel, T. N. (1962). Receptive fields, binocular interaction and functional architecture in the cat’s visual cortex. The Journal of Physiology, 160(1), 106–154.
Huth, A. G., Nishimoto, S., Vu, A. T., & Gallant, J. L. (2012). A continuous semantic space describes the representation of thousands of object and action categories across the human brain. Neuron, 76(6), 1210-1224.
Konkle, T., & Caramazza, A. (2013). Tripartite organization of the ventral stream by animacy and object size. Journal of Neuroscience, 33(25), 10235-10242.
Kosakowski, H. L., Cohen, M. A., Takahashi, A., Keil, B., Kanwisher, N., & Saxe, R. (2022). Selective responses to faces, scenes, and bodies in the ventral visual pathway of infants. Current Biology, 32(2), 265-274.
O’Doherty, C., Dineen, Á. T., Truzzi, A., King, G., Zaadnoordijk, L., Harrison, K., … & Cusack, R. (2026). Infants have rich visual categories in ventrotemporal cortex at 2 months of age. Nature Neuroscience, 1-10.
Quinn, P. C., Eimas, P. D., & Tarr, M. J. (2001). Perceptual categorization of cat and dog silhouettes by 3-to 4-month-old infants. Journal of experimental child psychology, 79(1), 78-94.
Spriet, C., Abassi, E., Hochmann, J. R., & Papeo, L. (2022). Visual object categorization in infancy. Proceedings of the National Academy of Sciences, 119(8), e2105866119.
Yamins, D. L., Hong, H., Cadieu, C. F., Solomon, E. A., Seibert, D., & DiCarlo, J. J. (2014). Performance-optimized hierarchical models predict neural responses in higher visual cortex. Proceedings of the national academy of sciences, 111(23), 8619-8624.

About the Author

As we began planning ICIS 2026, we found ourselves returning again and again to a simple idea: no infant develops in a vacuum. Every smile, every shift in gaze, every gesture, and every act of exploration unfolds somewhere—with particular caregivers, in particular homes and communities, shaped by particular social, cultural, linguistic, economic, and ecological conditions. Infancy is shaped by surrounding conditions and always embedded in context. And if that is true, then our science should be too.

That conviction sits at the heart of this year’s theme: Infancy in Context. We chose it at a moment when the field feels full of possibility. Infancy researchers are asking broader and more ambitious questions than ever before. They are asking about not only how infants learn, remember, communicate, and connect, but also how those processes are shaped by everyday experiences, relationships, inequality, migration, health, technology, climate, and culture. To understand development, we have to understand the worlds in which development happens.

Context, in this sense, is not an add-on to infant development; it is part of the phenomenon itself. It includes the immediate and intimate—the rhythms of caregiver interaction, the sounds infants hear, the objects they touch, the spaces they move through. But it also includes broader systems that surround families: access to health care, education, and resources; social and economic inequalities; public policy; and the environmental conditions in which children are raised. If we want a science that is both rigorous and relevant, we need to study infancy across these intersecting levels.

Holding the congress in Panama City makes this theme feel especially meaningful. This is the first time ICIS has taken place in the Global South, which helps to broaden the geographical scope of the field. Panama is a place defined by movement, exchange, encounter, and connection—a natural setting for a global focus on early human development. For ICIS, this location also reflects an important step in broadening where and how the field comes together. Bringing the conference to the Global South expands not only our geographical reach, but also the perspectives and experiences that shape our collective understanding of infancy.

We hope ICIS 2026 will feel like more than a conference in a beautiful location. We hope it will serve as a meeting point: across disciplines, methods, regions of the world, and career stages. A place where people who might not always find themselves in the same room can learn from one another, challenge one another, and build something new together.

A central part of this vision is globalization. ICIS has long been committed to advancing infancy worldwide, but this commitment is not simply about representation; it is about scientific accuracy. Much of what we know about infant development has been built on relatively narrow samples. Yet infants’ lives vary enormously across languages, caregiving practices, communities, and cultural beliefs. Expanding the scope of our research allows us to ask different questions, test the limits of existing theories, and better understand what is universal and what is context-specific in development.

This broader perspective is reflected in the range of work we will highlight at the congress. The invited speakers and contributors represent diverse fields, including developmental neuroscience, social and emotional development, education, public health, and policy. Their work spans multiple regions of the world and addresses development across a wider range of contexts, from everyday interactions to structural inequalities. Together, they reflect the kind of interdisciplinary and globally informed science that this theme aims to encourage.

At the same time, Infancy in Context, is also about how we study development. Methods shape what we can see. They highlight certain aspects of infants’ lives while leaving others less visible. If we want to capture development as it unfolds in real-world settings, we need approaches that can meet that complexity—methods that can be used across languages and communities, that allow for more naturalistic observation, and that can scale across diverse populations. ICIS 2026 reflects this methodological expansion in concrete ways. The program includes workshops and symposia focused on emerging tools and approaches, including diffuse optical imaging, eye-tracking in naturalistic and screen-based settings, large-scale implementation of shared research tools, and open-source approaches to EEG/ERP analysis tools. These efforts are not just about new technologies, they are about expanding what questions we can ask and who we can include in our research.

Just as important, we wanted this congress to invest in the people who will shape the future of the field. Supporting early-career researchers is one of our priorities. A strong and innovative science of infancy depends on students, postdoctoral scholars, research staff, and junior investigators not only entering the field but also being supported as they grow within it. ICIS has developed important initiatives to support this goal, including fellowships, travel awards, and training opportunities that aim to increase access and participation across diverse backgrounds and regions. For ICIS 2026, we wanted that spirit to be felt throughout the meeting. We hope emerging scholars will find not only opportunities to present their work but also meaningful mentorship, constructive feedback, and new collaborations. Just as importantly, we hope they will feel that their perspectives are essential to where the field is going next.

Ultimately, Infancy in Context is both a scientific theme and an invitation. It invites us to rethink the questions we ask, the methods we use, and the assumptions we bring to our science. It encourages us to build a body of research that better reflects the diversity of infants’ lives, and a scientific community that reflects that diversity as well. It also reminds us why this work matters. Infancy is the beginning of human development, and the conditions surrounding that beginning shape trajectories that extend far beyond the early years. Understanding those conditions, how they support, constrain, and transform development, is essential if we want our science to have real-world impact.

As we look ahead to ICIS 2026, we are not only excited about the meeting itself, but about what it can set in motion. We hope it will be a space where ideas are sharpened, assumptions are productively challenged, and collaborations take root – pushing the field toward a science that is more global, more inclusive, and more attuned to the complexity of real children’s lives. Above all, we hope it will remind us of something fundamental: when we study infants, we are never studying isolated minds or bodies. We are studying development in relationships, development in places, and development in context. That is the science we are working toward—and we look forward to continuing that conversation together in Panama City.

About the Author

In the 1990s, a wave of research changed how parents thought about early childhood. Developmental scientists demonstrated that early experience is critical for brain development and that enriched environments support children’s cognitive growth (Ramey & Ramey, 1998). The message was clear: Early experiences matter. What followed, however, could be considered a cultural overcorrection. Baby Einstein videos. Mozart for infants. Activity gyms, sensory toys, and structured play schedules designed to give babies the richest possible developmental diet. The underlying assumption was attractive: If some experience is good, more must be better. It didn’t work out that way. Studies showed that Baby Einstein babies learned no more language than babies who didn’t watch—and some learned less, likely because videos can’t provide the contingent, back-and-forth responding that a live caregiver does (Zimmerman et al., 2007). Ordinary home environments and responsive caregiver interactions were sufficient. Beyond a modest threshold, more stimulation didn’t produce proportional gains. Development is remarkably resilient.

New research from Tajikistan makes a strikingly similar point about motor development and early learning. Across Central Asia, it is common practice to swaddle infants tightly in a traditional cradle called a gahvora (Figure 1) for most of the day and night during the first two years of life (Karasik et al., 2018, 2023). At three months of age, many infants spend most of the day and night in the gahvora, their arms and legs immobilized with broad cloth bindings with brief windows outside the cradle for cuddling, feeding, and social interaction. From the perspective of Western developmental psychologists, this practice sounds alarming. (We know this because many expressed their alarm.) Modern theories of motor development emphasize that infants learn through movement—that they need to kick, reach, bat, and wiggle to discover how their bodies interact with the world (Adolph & Hoch, 2019; Campos et al., 2000). Without that physical freedom, shouldn’t infants’ development suffer?

Figure 1. Infant in a traditional gahvora cradle.

That question is exactly what we set out to answer. Karasik, Robinson, and Dodojonova (2026) brought a classic paradigm into Tajik homes: the mobile conjugate reinforcement task. A ribbon attaches one of the baby’s ankles to a colorful mobile overhead. Kick that leg, and the mobile moves. Within minutes, most babies figure it out and start kicking more deliberately—this reflects contingency learning, the basic cognitive capacity to connect actions with consequences. Typically, 80–90% of three-month-olds in North American samples learn the contingency in a single session (Rovee-Collier, 1997). What about gahvora-reared infants, who have spent almost their entire lives with their limbs bound? They learned it too! Despite their history of dramatically restricted movement, in a single session, Tajik infants increased their kicking across acquisition (with the ribbon attached), selectively kicking the tethered leg more than the untethered one. They also kept kicking at high rates even after we disconnected the ribbon—a hallmark of contingency learning. Finally, when the ribbon was detached, they protested—via negative vocalizations—just like babies growing up with full freedom of movement do (Fagen & Ohr, 1985). In sum, Tajik babies formed real expectations about what their kicks would produce, despite having a fraction of the unrestricted movement time of a typical Western baby.

The Timing Wrinkle and What It Reveals

One nuance in our findings illuminates just how the gahvora shapes learning. Infants naturally varied in how long they had been out of the cradle just before the task, from a few minutes to over an hour. Infants released right before the task barely moved during baseline—some hardly at all—while babies who had been free to move for a while were already kicking and vocalizing. But here’s the key finding: By the end of the session, both groups had learned equally well. Infants who started slowly needed time to get into the rhythm of free movement before they could exploit the contingency, but once they did—within minutes—their kicking spiked and stayed elevated through extinction. This very slight delay is not a failure of learning; it’s recalibration to an environment in which movement is newly unrestrained. As in Western infants faced with other motoric challenges (shoes, backpacks; Adolph & Avolio, 2000; Cole et al., 2014), the period of adjustment to new motor demands in Tajik infants happens fast, but it is not immediate.

What This Means for Parents (and for Developmental Science)

These findings shed light on a puzzle: Why do gahvora-reared infants show no long-term motor lags despite such extensive early restriction (Karasik et al., 2023, 2024), when, for example, orphanage-reared infants—who also experience restricted movement—show persistent delays (Gunnar, 2001)? The difference may not be the movement restriction itself, but the caregiving context that surrounds it. Whereas orphanage-reared infants often lack consistent, responsive caregivers altogether, gahvora-reared infants have dedicated caregivers who consistently attend to their signals and interact with them, both inside and during their windows outside the cradle.

This carries a message that runs counter to the assumptions underlying Baby Einstein and other super-enrichment schemes. Contingency learning—one of the foundational building blocks of cognitive and social development—doesn’t require months of unrestricted movement to kick in. It activates quickly whenever infants get the chance to act. What matters is not the sheer quantity of free movement, but whether infants have access to responsive caregiving and face real-world contingencies to act on the world when they are free to move. Quality over quantity.

A Word to Anxious Parents

Our findings have practical implications that deserve to be said plainly. If you’re not filling every waking moment with enrichment activities, your child is still going to learn to reach, to kick, to roll, to walk—and to figure out how the world responds to their actions. Babies don’t need a full-time event planner!

But the deeper point is not just that limited movement is harmless—it’s that infants are resourceful learners who adapt to what’s available. When one channel for exploration narrows, others stay open—watching, listening, tracking the social world. When free movement resumes, recalibration is fast. These aren’t moments lost; they’re moments spent differently.

The Baby Einstein hypothesis assumes that development is a bank account: the more you deposit, the richer the child. But it doesn’t work that way. Development doesn’t require optimization at every moment. What it requires is sufficient opportunity: some time to move, some time to interact with a responsive caregiver, and self-generated actions that produce meaningful consequences. Beyond that threshold, more is not necessarily better. Enough is enough.

Transporting a classic learning paradigm into homes halfway around the world, and discovering that infants defy our assumptions about what they need to thrive, requires sustained investment in basic developmental science. This work was funded by the National Science Foundation, and it is exactly the kind of question-driven, cross-cultural research that federal funding makes possible.

References

Adolph, K., & Avolio, A. (2000). Walking infants adapt locomotion to changing body dimensions. Journal of Experimental Psychology: Human Perception and Performance, 26(3), 1148–1166. https://doi.org/10.1037/0096-1523.26.3.1148

Adolph, K. E., & Hoch, J. E. (2019). Motor development: Embodied, embedded, enculturated, and enabling. Annual Review of Psychology, 70, 141–164.

Campos, J. J., Anderson, D. I., Barbu-Roth, M. A., Hubbard, E. M., Hertenstein, M. J., & Witherington, D. C. (2000). Travel broadens the mind. Infancy, 1, 149–219.

Cole, W. G., Gill, S. G., Vereijken, B., Adolph, K. E. (2014). Coping with asymmetry: How infants and adults walk with one elongated leg. Infant Behavior and Development, 37, 305-314.

Fagen, J. W., & Ohr, P. S. (1985). Temperament and crying in response to the violation of a learned expectancy in early infancy. Infant Behavior and Development, 8, 157–166.

Gunnar, M. R. (2001). Effects of early deprivation: Findings from orphanage-reared infants and children. In C. Nelson & M. Luciana (Eds.), Handbook of developmental cognitive neuroscience (pp. 617–629). MIT Press.

Karasik, L. B., Tamis-LeMonda, C. S., Ossmy, O., & Adolph, K. E. (2018). The ties that bind: Cradling in Tajikistan. PLoS ONE, 13, 1–18.

Karasik, L. B., Adolph, K. E., Fernandes, S. N., Robinson, S. R., & Tamis-LeMonda, C. S. (2023). Gahvora cradling in Tajikistan: Cultural practices and associations with motor development. Child Development, 94, 1049–1067.

Karasik, L. B., Schneider, J. L., Kuchirko, Y. A., & Dodojonova, R. M. (2024). Object play in Tajikistan: Infants explore objects despite bounds on play. Infancy, 30, e12627.

Ramey, C. T., & Ramey, S. L. (1998). Early intervention and early experience. American Psychologist, 53, 109–120.

Rovee-Collier, C. K. (1997). Dissociations in infant memory: Rethinking the development of implicit and explicit memory. Psychological Review, 104, 467–498.

Zimmerman, F. J., Christakis, D. A., & Meltzoff, A. N. (2007). Associations between media viewing and language development in children under age 2 years. Journal of Pediatrics, 151, 364–368.

About the Author

Previous research has shown that infant and adult preferences may in fact align. Infants are sensitive to low-level statistics— visual attributes of scenes or images consisting of properties such as edges, colours, and textures. Research has found that infants are sensitive to and prefer to look at certain image statistics over others (Newman et al., 2025). For example, in one study, infants tended to look longer at Van Gogh paintings that had a high variation in saturation and luminance (McAdams et al., 2023). Adults also tended to rate such paintings as being the most ‘pleasant’, displaying a shared preference for the same artworks that babies liked to look at. The authors tentatively suggested that these low-level image statistics that contributed to both infant visual preferences and adult pleasantness ratings are a form of ‘perceptual primitives’— the origins of aesthetic preference. Similar positive relationships between infant looking and adult aesthetics have been found for faces (Damon et al., 2019), colour (Skelton & Franklin, 2020), and building facades (McAdams et al., 2025).

In our research, we further investigated the relationship between infant looking and adult liking using baby book images. There is much evidence to suggest that early engagement with books is good for language acquisition (Franks et al., 2022), as well as social and emotional development (Briggs-Gowan, 2004). However, what kinds of books are most visually engaging for young babies, and are those books typically the ones that adults also like? We showed 54 infants (aged 2-12 months) 100 pages from baby board books across two experiments. A sample of 18 adults (aged 19-40 years) was also included in the second experiment. Infants were eye-tracked and their looking times, number of fixations, and saccade amplitudes were measured. Adults were also asked to rate the images on a sliding scale between 0 and 100, ranging from “I do not like at all” (0) to “I like a lot” (100). Scanned images of the book pages (see figure 1) were presented centrally on the screen, with the rating scale appearing below the stimuli in the adult experiment. The low-level image statistics of the book pages were also computed and were chosen based on their usage in previous research on both adult aesthetics (Berman et al., 2014) and infant looking behaviours (McAdams et al., 2023). These included saturation, luminance, straight and curved edge density, the proportion of different hues, and more (see figure 1 for examples).

Fig. 1. Examples of the image statistics used in the study (a) A book page used as a stimulus in Experiment 2 (Look Touch Learn Sky © 2022 Child’s Play (International) Ltd.), (b) The luminance matrix of the book page, (c) the edges of the book page highlighted by image analysis, (d) the pixel chromaticity plotted in the MacLeod & Boynton (1979) colour space, (e) the 8 hue segments (and the mean hue angles: 45°, red; 90°, cherry; 135°, yellow; 180°, chartreuse; 225°, green; 270°, teal; 315°, blue; 360°, violet) used to compute the mean saturation and proportion of pixels of different hues, with the dimension of saturation also shown. Figure from Newman et al. (2026).

Infant visual engagement in experiments one and two and adult liking ratings shared common predictors: variation in saturation, saturation of cherry and red hues, mean luminance, mean saturation, entropy, curved edge density, and fractal dimension. However, interestingly all predictors were in opposite directions for infants and adults. For example, infants visually engaged more with book pages that had a higher saturation, more colour contrast, more bluish hues, and a lower edge density, whereas adults liked these pages less.

In fact, infants were the most visually engaged with book pages that adults liked the least (see figure 2). Likewise, while pages with desaturated colours or black and white designs, low contrast, visual complexity, and detail were the most well-liked by adults, infants tended to visually engage with them the least.

Fig. 2. Scatterplot showing the relationship between the infant visual engagement principal component and adult liking ratings for each book page (each page is indicated by a black dot). The black line indicates the line of best fit. Figure from Newman et al. (2026).

While these results can act as a guide for baby book publishers, there are also implications for our understanding of what underlies infant visual preferences. Infant engagement and adult liking sharing common predictors echoes the notion of the ‘perceptual primitives’ of aesthetics. However, unlike previous research infants and adults responded in opposite ways for book images. These differences in infant visual preference and adult aesthetic preferences may be a result of infants’ immature visual system (Norcia & Tyler, 1985). While infants have functional colour vision by at least two-months-old (Teller, 1998), colours need to be highly-saturated to be visible to them. Infants’ poor visual acuity and colour sensitivities are not yet sufficient enough to properly engage in images with high detail and pastel colours, yet high contrast black and white designs may in fact be too ‘easy’ given that infants have colour vision, which may explain why infants visually engage the most with book pages that are highly colourful.

About the Author

Some researchers have begun to map structural brain development with growth charts using magnetic resonance imaging (MRI)³, but there has been much less work on comparable charts of early brain function. As we know, brain function also undergoes rapid change in early life, and this ongoing functional development supports emerging behavioral skills. But there has been very limited progress in identifying whether growth charts can be used to map brain function. Additionally, MRI is limited as a tool for scalable public health implementation due to its prohibitive cost and infrastructure. We sought to develop normative growth curves of infant brain function measured with electroencephalogram (EEG)⁴. EEG is a tool well-suited to this kind of public health developmental context, as it is a scalable, relatively low-cost modality that we can use to measure brain function in humans starting at birth.

We chose to characterize brain function in a key sensory domain: visual neurodevelopment. This domain is important for later visual functioning and may also scaffold later cognitive skills that matter across the lifespan. The visual-evoked potential (VEP) is a robust activity signal that has been measured across species and may reflect features of the neural architecture, such as myelination and underlying cortical circuit function. It can be collected with EEG while an infant watches a visual stimulus, like a flashing checkerboard. Even in infancy, the VEP has a canonical waveform, characterized by an initial negative peak (N1), a later positive peak (P2), and a final negative peak (N2), as shown in the bottom right panel of Figure 1.

Figure 1: Study Overview. 128-channel EEG data were collected in 802 infants (n=1374 EEG observations) between 57 and 579 days old across three continents. These data were a priori harmonized for paradigm, acquisition, and processing parameters across sites. Standard processing was used to extract the visual-evoked potential (VEP) from the EEG data and measure the amplitudes and latencies of the N1, P1, and N2 peaks. We created growth curves for each amplitude and latency.

We collected standardized EEG VEPs from 802 infants (ages 57 to 579 days old) from four longitudinal cohorts across three global sites (i.e., Cape Town, South Africa; São Paulo, Brazil; and Boston, USA), resulting in 1374 observations. These sites represent distinct cultural, linguistic (i.e., primarily speaking Xhosa, Brazilian Portuguese, and English, respectively), geographic, and socioeconomic contexts. For example, the socioeconomic diversity can be seen as more than 60% of the caregivers in the South Africa cohort reported an annual household income of less than $3,303 (60,000 ZAR); whereas 10.3% in the Brazil cohort fell under an HHI of $4,763 ($27,600 Brazilian Real) and only 5.4% in the US cohort reported making $50,000 or less. These differences allowed us to test whether developmental trajectories generalize across markedly different settings.

We developed growth curves for the different EEG signal components of this visual response. After extracting VEP waveforms from the EEG data, they can be characterized by the amplitudes (i.e., heights) and latencies (i.e., times from stimulus onset to peak) of the N1, P1, and N2 peaks. Growth curves for each of these parameters were created. Our modeling approach applied GAMLSS⁵ (generalized additive models of location, scale, and shape), a flexible centile-modeling method that can capture complex nonlinear trajectories and has been used in growth-chart work (see Figure 2). This approach creates flexible centile curves similar to those used in WHO growth standards. However, given the diversity of our three sites, we sought to test whether the developmental patterns we observed were similar across the distinct populations. When we modeled visual neurodevelopment features in two of the sites, we successfully applied the model to the held-out site, suggesting that these developmental trajectories were similar across populations.

Figure 2: Modeling Overview. We independently trained GAMLSS curves for each site and VEP feature (i.e., N1, P1, and N2 amplitudes and latencies). The GAMLSS curves were generalized across sites, indicating that a curve trained on the Boston data was valid for the Cape Town data. Individual centiles were extracted and linked to cognitive scores from a global public health measure (Global Scales of Early Development, Long Form).

Individual centile scores on these growth curves may also associate with broader cognitive development. We found that deviations from these trajectories were associated with Global Scales for Early Development scores, a WHO-developed measure of general development, in the South Africa cohort. Higher centile scores were associated with higher developmental scores at two years of age.

Our research suggests that key VEP developmental patterns are similar across these populations, despite substantial environmental, genetic, and cultural differences. Beyond this cross-site consistency, the VEP is a promising metric of neurodevelopment because of its accessibility. It can be collected in newborns using a simple, portable, and relatively low-cost EEG paradigm. This allows for greater diversity in both the data used to train the models and the settings where this technology could be deployed. Open-source preprocessing software, such as Harvard Automated Preprocessing Pipeline for EEG⁶ (HAPPE; https://github.com/PINE-Lab/HAPPE), can also facilitate standardized processing of EEG data. We have integrated our growth curves from the current dataset into HAPPE, making it easier to extract centile scores from new participants. We hope to continue updating these models as more data are collected and to improve our understanding of how the VEP relates to broader cognitive development. With further replication and prospective validation, VEP growth curves may provide a scalable framework for characterizing atypical developmental trajectories. In the future, they may help identify critical periods and support the assessment of intervention-related change.

Want to learn more about this study? Read our preprint here: https://doi.org/10.1101/2025.03.25.645314

1          Group, W. M. G. R. S. WHO Child Growth Standards based on length/height, weight and age. Acta Paediatr Suppl 450, 76-85 (2006). https://doi.org/10.1111/j.1651-2227.2006.tb02378.x
2          Kuczmarski, R. J. et al. 2000 CDC Growth Charts for the United States: methods and development. Vital Health Stat 11, 1-190 (2002).
3          Bethlehem, R. A. I. et al. Brain charts for the human lifespan. Nature 604, 525-533 (2022). https://doi.org/10.1038/s41586-022-04554-y
4          Margolis, E. T. et al. Growth charts of infant visual neurodevelopment generalize across global contexts. bioRxiv, 2025.2003.2025.645314 (2025). https://doi.org/10.1101/2025.03.25.645314

About the Author

When it comes to babies’ social worlds, one size does not fit all.

Even within the first year of life, infants differ in how their brains respond to social information, such as facial expressions, eye contact and speech. Rather than all babies attending to social cues in the same way, each infant appears to have their own unique pattern of neural engagement. Novel AI-based methods can now be used to personalise brain science and track these individual patterns in real time. This allows us to ask a simple but powerful question: what does each baby’s brain find most engaging in a social exchange?

Studying baby brains, one baby at a time

Traditionally, infant research has focused on group averages. While this approach has taught us a great deal, it can sometimes miss something important: individual differences. To address this, researchers at the Centre for Brain and Cognitive Development at Birkbeck, University of London used a cutting-edge method called Neuroadaptive Bayesian Optimisation (NBO), an artificial-intelligence technique that adapts in real time to each baby’s brain activity^1,2.

In a pre-registered study involving 61 infants aged 5 to 12 months³, babies looked at images of their caregiver’s face, a stranger’s face, or faces that were a mix of both. While babies viewed the faces, we recorded brain activity using electroencephalography (EEG), a safe and non-invasive technique (see Figure 1). We then used a machine learning algorithm that learned from each baby’s brain responses as the experiment unfolded. After each image was shown to the baby, the algorithm estimated which face had sparked the strongest response and used that information to choose what image to show next, allowing us to adjust the experiment moment by moment to each infant’s brain signals. This approach helped us identify which type of face triggered the strongest response for every individual baby.

Figure 1. Baby participants wearing EEG caps that measure their brain activity while they view images of different faces on a screen.

No “average” baby brain

What did we find? There was no single face type that worked best for all babies. Instead, around 85% of infants who completed the study showed strong individual preferences, with different babies responding most strongly to different faces.

An added bonus? This personalised approach also led to lower drop-out rates (about 15%, compared to the 22% typically seen in infant EEG studies). This demonstrates how tailoring experiments to babies by presenting images that elicit the strongest brain response can help keep them engaged.

The BONDS project: personalised approaches to social development

These findings are part of the wider BONDS project (Behaviour and Online Neuroimaging to study the Development of Socialisation), which involved over 120 infants and their families. BONDS combines wearable neuroimaging with artificial intelligence to test what social cues individual babies’ brains attend to.

A recent pre-registered study⁴ extended this work by showing that infants’ brains are sensitive to different combinations of social cues, such as eye gaze, head orientation, and emotional expression, and that the most engaging combinations vary from baby to baby.

Further, BONDS research has shown that personalised methods can be used not only with images on a screen, but also during live social interactions with an experimenter⁵. These studies demonstrate that:

• Infants differ in which social signals (e.g., gaze, infant-directed speech) elicit the strongest neural responses
• Brain engagement during social interaction reflects how motivated and attentive infants are in that moment
• Individual neural preferences can be detected reliably, even in dynamic, real-world social situations

Together, these findings suggest that early social brain development is shaped by individual experience and neural tuning, rather than following a single “typical” pattern.

Follow the baby’s lead

In summary, we showed, with a set of rigorous neuroimaging studies, that babies naturally differ in what captures their attention. Some may be especially drawn to expressive faces or direct eye contact, while others respond more strongly to subtler social cues. Because infants differ in what captures their attention, using personalised neuroimaging approaches to study these early differences in interests could open up new ways to support responsive parenting — that is, noticing what a baby naturally attends to and responding to it. Tuning into these individual preferences may help nurture babies’ attention and emerging social skills.

Looking ahead

By using personalised neuroimaging approaches, researchers are gaining a richer understanding of how babies engage with others from the very start of life. This work highlights the importance of recognising and respecting individual differences in early development — both in science and in everyday parenting.

The BONDS project is now expanding beyond infancy to study neurotypical and autistic toddlers, focusing on how children interact with their parents during real social exchanges. By studying parent–child interaction at this stage, the project aims to capture how diverse developmental pathways unfold, and how personalised approaches can help us understand and support children with different strengths and needs.

To learn more about this research and future findings, visit the BONDS project website: https://sites.google.com/view/bonds-project/

References:

1. Lorenz, R., Hampshire, A., & Leech, R. (2017). Neuroadaptive Bayesian optimization and hypothesis testing. Trends in cognitive sciences, 21(3), 155-167.
2. Gui, A., Throm, E. V., da Costa, P. F., Haartsen, R., Leech, R., & Jones, E. J. (2022). Proving and improving the reliability of infant research with neuroadaptive Bayesian optimization. Infant and Child Development, 31(5), e2323.
3. Throm, E., Gui, A., Haartsen, R., da Costa, P. F., Leech, R., Mason, L., & Jones, E. J. (2025). Combining Real‐Time Neuroimaging With Machine Learning to Study Attention to Familiar Faces During Infancy: A Proof of Principle Study. Developmental Science, 28(1), e13592.
4. Gui, A., Throm, E., da Costa, P. F., Penza, F., Mayans, M. A., Jordan-Barros, A., Haartsen, R., Leech, R., & Jones, E. J. H. (2024). Neuroadaptive Bayesian optimisation to study individual differences in infants’ engagement with social cues. Developmental Cognitive Neuroscience, 68, 101401.
5. Throm, E., Gui, A., Haartsen, R., da Costa, P. F., Leech, R., & Jones, E. J. (2023). Real-time monitoring of infant theta power during naturalistic social experiences. Developmental Cognitive Neuroscience, 63, 101300.

About the Author

As we launch into 2026—despite painfully freezing temperatures in NYC and a calendar with overly optimistic back-to-back-to-back meetings—I can’t help but feel an immense sense of warm gratitude for the opportunity to mentor outstanding undergraduates, graduate students, research staff, and postdoctoral scientists on our ever-favorite topic of infant development. I am likewise grateful for the opportunity to continue to learn from and contribute to members in the International Congress of Infant Studies. As I enter my 35th year as Professor at NYU, preceded by 4 years of PhD mentorship under Marc Bornstein (yup, I am very old!), I attended ~20 ICIS conferences, more than any other conference. That’s because ICIS is my favorite society by far. I admire the exquisite balance it offers between cutting-edge scholarship and simply having a good time with a vibrant, energetic, visionary, and absolutely welcoming international community of researchers at all stages of their careers. I can’t wait to add another meeting to my list this July in Panama.

Looking back to the end of 2025, November and December were all ICIS. The two weeks before ‘submission deadline’ our lab was frenzied to say the least (I would venture a guess that this was the case for many of you). It was filled with meetings and collaborations on abstracts around infant object interactions, communication, language, social interactions, temporal features of behavior, the home environment, culture, and even motor development (thanks to my sister lab, led by Karen Adolph). Somehow, we managed to submit who knows how many posters, talks, and symposia (I lost count).

So, what is the point of my writing this blog? Why do I feel compelled to express the deep fulfillment I feel about the work we do, the sharing of our research with others, and learning about the pioneering work of our colleagues (many of whom are also good friends)? Why do I feel compelled to applaud the open sharing that allows everyone in our field to learn and grow from each other in ways that make the whole much more than the sum of its parts? Why do I feel compelled to celebrate the sometimes-half-full glass of infancy research even at times when the half-empty glass appears to be front and center? Because I cannot think of anything more important than seeking to understand how infants learn and develop and the factors that propel their learning. The questions we ask as a field, and our excitement around scientific discovery and the testing of hypotheses, must always be louder than any obstacles or concerns. In truth, our glass is overflowing—with new ideas, new methods of data collection, new technologies, and new analytic approaches that allow us to collectively push science forward.

Of course, I am quite aware of the reality that many mentees and staff in my lab, department, university (and surely universities around the globe) are concerned about the future—the job market, academia, grant funding. Students are further concerned about countless other pressures and hurdles they must overcome—their comprehensive exams, R scripts that won’t run, how much they need to publish to land a postdoc or faculty position, and how to handle the comments of ‘Reviewer 2’ (if you are Reviewer #2, I prefer you don’t let us know).

But then I remind everyone in the lab to take a pause and reflect on how totally cool and exciting their work is. I tell my students and staff that their only job right now, their only concern, should be to grow and be passionate about their research and ultimately to do good (hopefully great) work that advances the science of infancy. Then, when we get together for our weekly lab meeting, the excitement of their work takes on a new life. We get to watch videos—hundreds of hours of videos—of babies and toddlers yelling “NO!” to their moms or dads, crawling and walking from room to room, flitting from object to object as they explore their surroundings and generate feedback from the people around them. We watch videos of cultural practices around the globe, from cradling to cuddling, talking to walking. We observe and quantify the unique physical characteristics of apartments in NYC, Hong Kong, and Seoul South Korea, which contain hundreds of child-designed toys, and we contrast those environments with homes in Tajikistan, which are spread over courtyards and where infants play with boulders and twigs, their cribs, plastic water bottles, and the pots and pans their mothers use to cook. We talk about the next study we will run, the grant that just got funded (yay!), the next grant we are currently writing, and how to design our protocols. We start the process of translating and adapting methods and measures to different languages, thankfully made possible by the multilingual community of committed and eager researchers who populate our lab. We upload our videos, coding manuals, spreadsheets and so on to Databrary.org so that authorized investigators can address new questions that we don’t have the bandwidth or expertise to tackle, thereby capitalizing on the investments of federal agencies, foundations, and families who generously give their time to us. Then, we stop to write our abstracts, about what we saw and what we learned, and we submit our work to ICIS.

We may have been frenzied toward the end of 2025, but what could be more fulfilling than clicking submit to share our science? And now, in the blustery cold of winter, we will sit back to await the news, celebrate the overflowing cup of infancy research, and plan our trip to Panama to attend the greatest international conference in developmental science out there. See you all soon!

About the Author

Across four preregistered experiments, we had 1.5- to 8-year-olds play a card-matching game on a tablet or video screen (see Figure 1). The game consisted of three face-down cards that “fly” in. There were two cards on the bottom and one on the top. Each of the two bottom cards flipped over to reveal an image. Then, they flipped face down. Finally, the top card flipped over to reveal a match with one of the two bottom cards. It is there that we looked to see whether children looked at (1.5- to 2.5-year-olds) or tapped (3- to 8-year-olds) the correct matching card. There are four trials of this card-matching game where the images on the cards are all unique, and four trials where the images on the cards are repeated from trial to trial. In this repeated condition, the first trial may have an orange on the left card and a banana on the right card. The second trial may then have the orange on the right and the banana on the left. If toddlers and young children are affected by proactive interference, then on later trials, they may have more trouble picking out which side the matching card was on in the repeated condition compared to the version where they see all new cards in each trial.

Figure 1. The sequence of events in a test trial for the card-matching game.

So how do children do? Our first study² using this card-matching game across three preregistered experiments (N = 245, 111 boys) found that 2.5- to 8-year-old children will, like you, walk to yesterday’s parking spot instead of today’s. Our fourth preregistered experiment^3, tested 1.5- to 2.5-year-olds (N = 34) and found that toddlers also make more memory mistakes when old information (“the orange was on the left last time…”) can interfere with new information (“was the orange on the left or the right this time?”). This may not sound too surprising, as we all know that children make much bigger (and funnier, at times) memory mistakes than getting mixed up in a card-matching game. We indeed expected that children, especially young toddlers, would be more susceptible to something like proactive interference than older children or adults. What’s important about quantifying this is that most measures of memory performance in children and toddlers don’t take proactive interference into account, and thus may be reporting children’s memory as worse than it really is.

Plenty of laboratory and clinical tasks measuring memory performance in toddlers and children involve repeated trials where children have to remember the same or similar information over and over again^4,5,6. Although this is an intuitive way to get an average memory “score”, if children’s memory is disproportionately affected by proactive interference, then their performance will tend to decline across trials and thus lead to an underestimation of their actual memory abilities. For example, in our card-matching game, children must remember (1) the image on the bottom-left card, (2) the image on the bottom-right card, and after they see the top card and need to choose the match, they need to remember (3) where (right or left) the matching card was. Previous work has shown that by 9 months of age, infants can keep track of “what” went “where” for two objects at a time⁷. Yet when we induce proactive interference in our experiment, 1.5- to 2.5-year-olds’ performance drops to chance level at this “what” went “where” task by the 4th trial.

It comes as no surprise that toddlers’ working memory would be sensitive to interference effects. Our research has the following takeaway: through critically assessing old assumptions, we can come to new conclusions that impact how future research is conducted. This is the beauty of scientific progress, and it wouldn’t be possible without the R15 grant from the National Institutes of Health (NIH) we received to help pay for equipment and reimbursing the hundreds of families who volunteered their time to participate in our research. Federal grants not only provide financial stability to research projects, but they also buy time. An awarded NIH grant allows researchers to spend time training and mentoring the future generation of scientists. For example, the current project is co-led by an undergraduate research assistant, Zane Mourad, who is not only a co-author on this blog post, but they are also being fully immersed in research thanks to the time that grants allow faculty and graduate students to train mentees. Therefore, only through this kind of major funding could we tackle our next questions: are some kids more susceptible to proactive interference than others? If so, do cognitive assessments appropriately take this into account? We hope to continue our research into children’s memory and forgetting.

1. Hamilton, M., Ross, A., Blaser, E., & Kaldy, Z. (2022). Proactive interference and the development of working memory. Wiley Interdisciplinary Reviews – Cognitive Science, 13(3), e1593.
2. Hamilton, M., Roper, T., Blaser, E., & Kaldy, Z. (2024). Can’t get it out of my head: Proactive interference in the visual working memory of 3- to 8-year-old children. Developmental Psychology, 60(3), 582–594.
3. Koolhaas, C., Hamilton, M., Roper, T., Blaser, E., Kaldy, Z. Proactive interference disrupts 2-year-olds’ working memory. Poster presentation at the Biennial Meeting of the Society for Research in Child Development, May 1 – May 3, 2025, Minneapolis, MN.
4. Fitzpatrick, C., & Pagani, L. S. (2012). Toddler working memory skills predict kindergarten school readiness. Intelligence, 40(2), 205-212.
5. Morra, S., Gandolfi, E., Panesi, S., & Prandelli, L. (2021). A working memory span task for toddlers. Infant Behavior and Development, 63, 101550.
6. Willoughby, M. T., Blair, C. B., Wirth, R. J., & Greenberg, M. (2010). The measurement of executive function at age 3 years: psychometric properties and criterion validity of a new battery of tasks. Psychological Assessment, 22(2), 306.
7. Kaldy, Z., & Leslie, A. M. (2003). Identification of objects in 9‐month‐old infants: integrating ‘and ‘information. Developmental Science, 6(3), 360-373.

About the Author

September 10, 1943—October 23, 2025

Judy S. DeLoache was born on September 10, 1943 in the small town of Holyoke, Colorado where she grew up on a wheat farm. There were only 38 people in her graduating class. But being from a small town did not keep her from having a big life. She received her BA and MA degrees at Georgia State College where she worked with Professor James Pate, an experimentalist and statistics instructor.  At the time, her research subjects were rats, and her first publication was “Hippocampal lesions and spontaneous alternation behavior in the rat,” which appeared in Physiology and Behavior. Jim saw her potential and encouraged her to pursue a PhD, so in 1969, she left Georgia and moved to the University of Illinois in Champaign-Urbana, where she began her PhD studying infant memory with Dr. Les Cohen.  After receiving her degree in 1973, she took a position as an Assistant Professor at Florida Atlantic University.  But after only a year, she returned to Illinois, after meeting her husband, Jerry Clore. They were married in 1977, and their son Ben was born in 1978.  She spent several years there on soft money, receiving financial and moral support from Professors Ann Brown and Joe Campione, which enabled her to apply for and receive her first NIH research grant called “Representational Functioning in Young Children.” This grant was continuously funded for the entirety of her career.

In 1981, she became an Assistant Professor in the small Department of Human Development and Family Ecology at the University of Illinois, where she came up through the ranks and eventually served as department chair.  She was then hired by the Psychology Department in 1991, where she taught until 2000, after being awarded an Alumni Distinguished Professorship in 1999. In 2001, she moved to the University of Virginia, where she was the Keenan Professor of Psychology until she retired in 2014.

Judy’s successful career as a developmental scientist can be at least partially attributed to the fact that she was a brilliant observer of human behavior. It was in her early memory work that she used a scale model of a larger room to hide an object to see if children could remember where it was hidden in an identical full-sized room. One thing that struck her was that 2.5-year-olds unexpectedly failed this seemingly easy task. Where some researchers would be distraught and call this a failure, Judy observed something interesting. She went on to use this “scale model task” to explore the developmental shift in children’s ability to use a miniature model as a representation of a larger room. Her initial findings using this task led to her seminal paper in Science entitled “Rapid change in the symbolic functioning of very young children,” (1987), and launched a decades long career on young children’s understanding of symbols.

Her largest contribution to developmental science was her theory of dual representation, which explains how children come to understand that a symbolic object—like a picture, map, or scale model—can be both a real object and a representation of something else at the same time. Her work has made a huge impact on how developmental psychologists have studied how children come to understand that pictures, models, books, maps, digital media, and other symbolic objects stand for real-world things. Her work shed a new light on how representational insight develops and how it supports long-term learning, and has influenced not only theories of cognitive development, but also practical approaches to education and media design for young children. Her seminal “shrinking room study,” which advanced her dual representation theory, was selected for the Society for Research in Child Development (SRCD)’s list of “Twenty Studies that Fascinated Child Psychology,” in 2003, properly putting her name next to giants in the field like Harry Harlow, Eleanor Gibson, and Jean Piaget.

Judy was also the recipient of numerous national and international awards including the APA William James Fellow Award, Fellow of the American Association for the Advancement of Science (AAAS), Fellow of the American Academy of Arts and Sciences, Member of the Society of Experimental Psychologists, SRCD Senior Distinguished Contributions Award, and the Distinguished Contribution Award from the International Congress on Infant Studies (ICIS).

Despite being a brilliant and world-renown scientist, Judy was down to earth, kind, and generous with her time. And she was fun. She loved life, she loved people, and she loved her students. She especially loved her husband Jerry, her son Ben and daughter-in-law Laura, and her grandchildren Waverly and Wilder. Of all of her many accomplishments, her family was the one she was most proud of. To me, Judy was a teacher, a mentor, and a friend. She was always the life of the party—the person everyone in the room wanted to talk to. She was one of my favorite people. And if you knew her, I’m certain she was one of yours too.

Vanessa LoBue

The big picture

Thanks to modern neonatal care, more preterm babies are surviving than ever before. Yet more than thirteen million babies worldwide are still born early each year, and many spend their first days or weeks in neonatal intensive-care units (NICUs) ([1]; [2]). Being born early can place children at higher risk for long-term challenges with movement, attention, and behavior ([3]; [4]; [5]).

Alongside medicines when they are needed (e.g., [6]), researchers have been testing gentle, non-drug approaches that can soothe and support development – like carefully structured sounds (white noise, heartbeat recordings, and other environmental sounds) that help stabilize sleep and reduce stress ([10]; [11]). Music – whether passively listened to or used in a therapeutic way ([12]-[15]) – has also been linked to better physiological regulation and emotional well-being in infants, with longer-term benefits for mental health and social inclusion ([16]; [17]).

Because premature infants are extra sensitive to noise, sound in the NICU has to be handled with care: average levels outside the incubator should stay around 45–50 dB, with brief peaks below 65 dB ([18]; [19]). And none of this replaces the power of everyday bonding. Early, sensitive parent–infant interactions set the stage for healthy brain development – but those interactions can be harder to achieve after a stressful or traumatic birth ([20]; [21]). With that context in mind, our team asked a simple question with big stakes: Do a caregiver’s relationship to the baby (kinship) and the pitch of their voice (which tends to be lower in men and higher in women) change how a preterm infant’s brain responds to singing? To find out, we created a precision-music medicine protocol designed specifically for fragile newborns [22].

What we did

We ran a small, carefully controlled study in the NICU. 30 very-preterm infants (born at or before 32 weeks gestation) took part. In the experimental group (15 infants), over four consecutive days, each baby experienced the same short, 11.5-minute “listening session”, but the singer changed from day to day: father, mother, a male music therapist, and a female music therapist – in randomized order. That let us tease apart two things at once: kinship (parent vs. non-parent) and voice type (typically lower-pitched male voices vs. higher-pitched female voices). Each session included quiet periods for comparison and two kinds of sounds: a single musical note and a lullaby. While the babies listened, we recorded their brain activity using an infant-friendly electroencephalography (EEG) set up. We focused on the “delta” brainwaves range – slow brain waves linked to cortical maturation in premature infants – because it is a useful window into how the brain is organizing itself at this stage.

What we found

In our preliminary report published in Plos One journal [22], showed that mothers’ singing tended to evoke strong slow-wave responses under most conditions. But during the lullaby – a richer, more complex sound – father’ singing produced the strongest average response, followed by the male music therapist, then the mother, and then the female music therapist.

When we analyzed the full cohort of all 15 infants in the experimental group, the overall pattern held. The lullaby prompted especially robust slow-wave activity, and paternal singing again came out on top. To zero in on whether this had more to do with voice type than the specific people, we grouped male voices (father + male therapist) and female voices (mother + female therapist). Male voices elicited significantly higher slow-wave (delta) activity during the lullaby condition even in this case. In everyday terms: a lower-pitched lullaby seemed to sync more strongly with these babies’ developing brain rhythms.

Of course, this is a small study, so we should be cautious. But the results suggest that both the complexity of the sound (like a full lullaby) and the voice’s pitch can shape how a very-preterm infant’s brain responds.

Why this matters for families

These findings push back on the idea that only a mother’s voice “counts” in early interventions. Certainly, mothers remain essential – their voices reliably supported strong brain responses under simpler sound conditions, but fathers’ singing – especially a real lullaby – may offer a unique boost.

What could this look like in practice? We need to start inviting fathers in NICUs more often and more systematically, where bonding can be interrupted by medical needs. In these terms, structured paternal singing may help spark healthy brain rhythms and strengthen father–infant bonding and later attachment right from the start. Furthermore, when a mother cannot sing on a given day – because of medical recovery, logistics, or simply exhaustion – a father’s lullaby can serve as a powerful stand-in, helping maintain consistent, meaningful sensory input for the baby. For mothers who are singing most often, it can also help to experiment with a slightly lower pitch range or a slower tempo to see whether it better matches the baby’s calm, slow rhythms, especially during lullabies. Remember: sound levels in the NICU must stay gentle and safe, and nothing replaces nurturing contact and responsive caregiving. Singing is one supportive tool among many.

Why public funding also matters

This work was possible because of hospital/state support – the kind of public investment that lets teams build safe, family-centered protocols and bring advanced tools to the bedside. Findings like ours, therefore, do not just refine how we think about early bonding. They point to practical changes that national and international health policies can encourage, such as expanding paternal leave and making room for father-infant co-regulation in the earliest days.

We should also mention that studies like this are careful and resource intensive. We used infant-grade EEG, a data-cleaning process tailored to fragile signals, and a study design where each baby experienced every experimental condition so we could spot real differences with a small group. That approach is efficient – it squeezes more clarity out of fewer participants – but it only works when public funding supports skilled clinician-scientist teams, specialized equipment, and the time needed to do the work right (ideally including follow-up as children grow).

Without that broader public infrastructure, questions at the intersection of sound, relationships, and early brain development would remain unanswered, and precision, family-centered care underpowered. Therefore, our research and findings, we believe, make a strong case for continued public stewardship: even modest investments in precision, family-focused neonatal care can generate knowledge and insights that improve care now and reduce costs later – by lowering the burden of neurodevelopmental difficulties across childhood. In short, public investment pays off twice – first by protecting fragile beginnings and again by strengthening the society those children will help build.

References

[1] Bradley, E., Blencowe, H., Moller, A. B., et al. (2025). Born too soon: Global epidemiology of preterm birth and drivers for change. Reproductive Health, 22(Suppl. 2), 105. https://doi.org/10.1186/s12978-025-02033-x

[2] Cheong, J. L., Spittle, A. J., Burnett, A. C., Anderson, P. J., & Doyle, L. W. (2020). Have outcomes following extremely preterm birth improved over time? Seminars in Fetal & Neonatal Medicine, 25(3), 101114. https://doi.org/10.1016/j.siny.2020.101114

[3] Camerota, M., & Lester, B. M. (2025). Neurobehavioral outcomes of preterm infants: Toward a holistic approach. Pediatric Research, 97(5), 1475–1480. https://doi.org/10.1038/s41390-024-03505-9

[4] Song, I. G. (2023). Neurodevelopmental outcomes of preterm infants. Clinical and Experimental Pediatrics, 66(7), 281–287. https://doi.org/10.3345/cep.2022.00822

[5] Twilhaar, E. S., Wade, R. M., de Kieviet, J. F., van Goudoever, J. B., van Elburg, R. M., & Oosterlaan, J. (2018). Cognitive outcomes of children born extremely or very preterm since the 1990s and associated risk factors: A meta‐analysis and meta‐regression. JAMA Pediatrics, 172(4), 361–367. https://doi.org/10.1001/jamapediatrics.2017.5323

[6] Juul, S. E., Comstock, B. A., Wadhawan, R., Mayock, D. E., Courtney, S. E., Robinson, T., … Heagerty, P. J. (2020). A randomized trial of erythropoietin for neuroprotection in preterm infants. New England Journal of Medicine, 382(3), 233–243.

[7] Rohmah, I., Mukminin, M. A., Hasan, F., Romadlon, D. S., Chang, K. M., Chen, K. H., & Chiu, H. Y. (2025). Comparative effects of nonpharmacological interventions on sleep-wake states among preterm infants in neonatal intensive care units: A systematic review and network meta-analysis. Intensive and Critical Care Nursing, 91, 104168. https://doi.org/10.1016/j.iccn.2025.104168

[8] Shen, Q., Huang, Z., Leng, H., Luo, X., & Zheng, X. (2022). Efficacy and safety of non-pharmacological interventions for neonatal pain: An overview of systematic reviews. BMJ Open, 12(9), e062296. https://doi.org/10.1136/bmjopen-2022-062296

[9] Sofologi, M., Pliogou, V., Bonti, E., Efstratopoulou, M., Kougioumtzis, G. A., Papatzikis, E., … & Papantoniou, G. (2022). An investigation of working memory profile and fluid intelligence in children with neurodevelopmental difficulties. Frontiers in psychology, 12, 773732. https://doi.org/10.3389/fpsyg.2021.773732

[10] Zhang, Q., Huo, Q., Chen, P., Yao, W., & Ni, Z. (2024). Effects of white noise on preterm infants in the neonatal intensive care unit: A meta-analysis of randomised controlled trials. Nursing Open, 11(1), e2094. https://doi.org/10.1002/nop2.2094

[11] Zhang, S., & He, C. (2023). Effect of the sound of the mother’s heartbeat combined with white noise on heart rate, weight, and sleep in premature infants: A retrospective comparative cohort study. Annals of Palliative Medicine, 12(1), 11120–11120.

[12] Jaschke, A. C., Papatzikis, E., & Haslbeck, F. B. (2025). Medical Neurohumanities: Sharing Insights from Medicine, Neuroscience, and Music in Paediatric Care. Frontiers in Neuroscience, 19, 1648030. https://doi.org/10.3389/fnins.2025.1648030

[13] Papatzikis, E., Agapaki, M., Selvan, R. N., Hanson-Abromeit, D., Gold, C., Epstein, S., … Pandey, V. (2024). Music medicine and music therapy in neonatal care: A scoping review of passive music listening research applications and findings on infant development and medical practice. BMC Pediatrics, 24(1), 829.

[14] Yakobson, D., Gold, C., Beck, B. D., Elefant, C., Bauer-Rusek, S., & Arnon, S. (2021). Effects of live music therapy on autonomic stability in preterm infants: A cluster-randomized controlled trial. Children, 8(11), 1077. https://doi.org/10.3390/children8111077

[15] Haslbeck, F. B., Jakab, A., Held, U., Bassler, D., Bucher, H. U., & Hagmann, C. (2020). Creative music therapy to promote brain function and brain structure in preterm infants: A randomized controlled pilot study. NeuroImage: Clinical, 25, 102171. https://doi.org/10.1016/j.nicl.2020.102171

[16] Agapaki, M., Pinkerton, E. A., & Papatzikis, E. (2022). Music and neuroscience research for mental health, cognition, and development: Ways forward. Frontiers in Psychology, 13, 976883. https://doi.org/10.3389/fpsyg.2022.976883

[17] Papatzikis, E., & Rishony, H. (2022). What is music for neuroplasticity?: Combined value on infant development and inclusion. In Rethinking inclusion and transformation in special education (pp. 160-177). IGI Global Scientific Publishing. https://doi.org/10.4018/978-1-6684-4680-5.ch010

[18] Almadhoob, A., & Ohlsson, A. (2020). Sound reduction management in the neonatal intensive care unit for preterm or very low birth weight infants. The Cochrane Database of Systematic Reviews, 1(1), CD010333. https://doi.org/10.1002/14651858.CD010333.pub3

[19] Smith, S. W., Ortmann, A. J., & Clark, W. W. (2018). Noise in the neonatal intensive care unit: A new approach to examining acoustic events. Noise & Health, 20(95), 121–130. https://doi.org/10.4103/nah.NAH_53_17

[20] Shaw, R. J., Givrad, S., Poe, C., Loi, E. C., Hoge, M. K., & Scala, M. (2023). Neurodevelopmental, mental health, and parenting issues in preterm infants. Children, 10(9), 1565. https://doi.org/10.3390/children10091565

[21] Boissel, L., Pinchaux, E., Guilé, M., Corde, P., Crovetto, C., Diouf, M., Mariana, C., Meynier, J., Picard, C., Scoury, D., Cohen, D., Benarous, X., Viaux-Savelon, S., & Guilé, J. M. (2022). Development and reliability of the coding system evaluating maternal sensitivity to social interactions with 34- to 36-week postmenstrual age preterm infants. Frontiers in Psychiatry, 13, 938482. https://doi.org/10.3389/fpsyt.2022.938482

[22] Papatzikis E., Dimitropoulos K., Tataropoulou K., Kyrtsoudi M., Pasoudi E., O’Toole JM., et al. (2025) The father’s singing voice may impact premature infants’ brain more than their mother’s: A NICU single-arm exploratory study protocol and preliminary data on a singing and EEG framework based on the fundamental frequency of voice and kinship. PLoS One 20(8): e0328211. https://doi.org/10.1371/journal.pone.0328211

About the Author