Infants' top-down perceptual modulation is specific to own-race faces.

Recent studies have revealed the influence of higher-level cognitive systems in modulating perceptual processing (top-down perceptual modulation) in infancy. However, more research is needed to understand how top-down processes in infant perception contribute to early perceptual development. To this end, this study examined infants' top-down perception of own- and other-race faces to reveal whether top-down modulation is linked to the emergence of perceptual specialization. Infants first learned an association between a sound and faces, with the race of the faces manipulated between groups (own race vs. other race). We then tested infants' face perception across various levels of perceptual difficulty (manipulated by presentation duration) and indexed top-down perception by the change in perception when infants heard the sound previously associated with the face (predictive sound) versus an irrelevant sound. Infants exhibited top-down face perception for own-race faces (Experiment 1). However, we present new evidence that infants did not show evidence of top-down modulation for other-race faces (Experiment 2), suggesting an experience-based specificity of this capacity with more effective top-down modulation in familiar perceptual contexts. In addition, we ruled out the possibility that this face race effect was due to differences in infants' associative learning of the sound and faces between the two groups. This work has important implications for understanding the mechanisms supporting perceptual development and how they relate to top-down perception in infancy.

Longitudinal assessments of functional near-infrared spectroscopy background functional connectivity in low- and middle-income infants during a social cognition task.

Shortly after birth, human infants demonstrate behavioral selectivity to social stimuli. However, the neural underpinnings of this selectivity are largely unknown. Here, we examine patterns of functional connectivity to determine how regions of the brain interact while processing social stimuli and how these interactions change during the first 2 years of life. Using functional near-infrared spectroscopy (fNIRS), we measured functional connectivity at 6 (n = 147) and 24 (n = 111) months of age in infants from Bangladesh who were exposed to varying levels of environmental adversity (i.e., low- and middle-income cohorts). We employed a background functional connectivity approach that regresses out the effects of stimulus-specific univariate responses that are believed to affect functional connectivity. At 6 months, the two cohorts had similar fNIRS patterns, with moderate connectivity estimates for regions within and between hemispheres. At 24 months, the patterns diverged for the two cohorts. Global (brain-wide) connectivity estimates increased from 6 to 24 months for the low-income cohort and decreased for the middle-income (MI) cohort. In particular, connectivity estimates among regions of interest within the right hemisphere decreased for the MI cohort, providing evidence of neural specialization by 2 years of age. These findings provide insights into the impact of early environmental influences on functional brain development relevant to the processing of social stimuli. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The Influence of Memory on Visual Perception in Infants, Children, and Adults.

Perception is not an independent, in-the-moment event. Instead, perceiving involves integrating prior expectations with current observations. How does this ability develop from infancy through adulthood? We examined how prior visual experience shapes visual perception in infants, children, and adults. Using an identical task across age groups, we exposed participants to pairs of colorful stimuli and implicitly measured their ability to discriminate relative saturation levels. Results showed that adult participants were biased by previously experienced exemplars, and exhibited weakened in-the-moment discrimination between different levels of saturation. In contrast, infants and children showed less influence of memory in their perception, and they actually outperformed adults in discriminating between current levels of saturation. Our findings suggest that as humans develop, their perception relies more on prior experience and less on current observation.

Visual Perception Is Highly Flexible and Context Dependent in Young Infants: A Case of Top-Down-Modulated Motion Perception.

Top-down modulation is an essential cognitive component in human perception. Despite mounting evidence of top-down perceptual modulation in adults, it is largely unknown whether infants can engage in this cognitive function. Here, we examined top-down modulation of motion perception in 6- to 8-month-old infants (recruited in North America) via their smooth-pursuit eye movements. In four experiments, we demonstrated that infants' perception of motion direction can be flexibly shaped by briefly learned predictive cues when no coherent motion is available. The current findings present a novel insight into infant perception and its development: Infant perceptual systems respond to predictive signals engendered from higher-level learning systems, leading to a flexible and context-dependent modulation of perception. This work also suggests that the infant brain is sophisticated, interconnected, and active when placed in a context in which it can learn and predict.

Towards imaging the infant brain at play.

Infants' first-person experiences are crucial to early cognitive and neural development. To a vast extent, these early experiences involve play, which in infancy takes the form of object exploration. While at the behavioral level infant play has been studied both using specific tasks and in naturalistic scenarios, the neural correlates of object exploration have largely been studied in highly controlled task settings. These neuroimaging studies did not tap into the complexities of everyday play and what makes object exploration so important for development. Here, we review selected infant neuroimaging studies, spanning from typical, highly controlled screen-based studies on object perception to more naturalistic designs and argue for the importance of studying the neural correlates of key behaviors such as object exploration and language comprehension in naturalistic settings. We suggest that the advances in technology and analytic approaches allow measuring the infant brain at play with the use of functional near-infrared spectroscopy (fNIRS). Naturalistic fNIRS studies offer a new and exciting avenue to studying infant neurocognitive development in a way that will draw us away from our laboratory constructs and into an infant's everyday experiences that support their development.

Using functional near-infrared spectroscopy to study the early developing brain: future directions and new challenges.

Significance: Functional near-infrared spectroscopy (fNIRS) is a frequently used neuroimaging tool to explore the developing brain, particularly in infancy, with studies spanning from birth to toddlerhood (0 to 2 years). We provide an overview of the challenges and opportunities that the developmental fNIRS field faces, after almost 25 years of research. Aim: We discuss the most recent advances in fNIRS brain imaging with infants and outlines the trends and perspectives that will likely influence progress in the field in the near future. Approach: We discuss recent progress and future challenges in various areas and applications of developmental fNIRS from methodological and technological innovations to data processing and statistical approaches. Results and Conclusions: The major trends identified include uses of fNIRS "in the wild," such as global health contexts, home and community testing, and hyperscanning; advances in hardware, such as wearable technology; assessment of individual variation and developmental trajectories particularly while embedded in studies examining other environmental, health, and context specific factors and longitudinal designs; statistical advances including resting-state network and connectivity, machine learning and reproducibility, and collaborative studies. Standardization and larger studies have been, and will likely continue to be, a major goal in the field, and new data analysis techniques, statistical methods, and collaborative cross-site projects are emerging.

Attrition rate in infant fNIRS research: A meta-analysis.

Understanding the trends and predictors of attrition rate, or the proportion of collected data that is excluded from the final analyses, is important for accurate research planning, assessing data integrity, and ensuring generalizability. In this pre-registered meta-analysis, we reviewed 182 publications in infant (0-24 months) functional near-infrared spectroscopy (fNIRS) research published from 1998 to April 9, 2020, and investigated the trends and predictors of attrition. The average attrition rate was 34.23% among 272 experiments across all 182 publications. Among a subset of 136 experiments that reported the specific reasons for subject exclusion, 21.50% of the attrition was infant-driven, while 14.21% was signal-driven. Subject characteristics (e.g., age) and study design (e.g., fNIRS cap configuration, block/trial design, and stimulus type) predicted the total and subject-driven attrition rates, suggesting that modifying the recruitment pool or the study design can meaningfully reduce the attrition rate in infant fNIRS research. Based on the findings, we established guidelines for reporting the attrition rate for scientific transparency and made recommendations to minimize the attrition rates. This research can facilitate developmental cognitive neuroscientists in their quest toward increasingly rigorous and representative research.

Infants' lexical comprehension and lexical anticipation abilities are closely linked in early language development.

Theories across cognitive domains propose that anticipating upcoming sensory input supports information processing. In line with this view, prior findings indicate that adults and children anticipate upcoming words during real-time language processing, via such processes as prediction and priming. However, it is unclear if anticipatory processes are strictly an outcome of prior language development or are more entwined with language learning and development. We operationalized this theoretical question as whether developmental emergence of comprehension of lexical items occurs before or concurrently with the anticipation of these lexical items. To this end, we tested infants of ages 12, 15, 18, and 24 months (N = 67) on their abilities to comprehend and anticipate familiar nouns. In an eye-tracking task, infants viewed pairs of images and heard sentences with either informative words (e.g., eat) that allowed them to anticipate an upcoming noun (e.g., cookie), or uninformative words (e.g., see). Findings indicated that infants' comprehension and anticipation abilities are closely linked over developmental time and within individuals. Importantly, we do not find evidence for lexical comprehension in the absence of lexical anticipation. Thus, anticipatory processes are present early in infants' second year, suggesting they are a part of language development rather than solely an outcome of it.

Optical imaging and spectroscopy for the study of the human brain: status report.

This report is the second part of a comprehensive two-part series aimed at reviewing an extensive and diverse toolkit of novel methods to explore brain health and function. While the first report focused on neurophotonic tools mostly applicable to animal studies, here, we highlight optical spectroscopy and imaging methods relevant to noninvasive human brain studies. We outline current state-of-the-art technologies and software advances, explore the most recent impact of these technologies on neuroscience and clinical applications, identify the areas where innovation is needed, and provide an outlook for the future directions.

Cognitive development: Looking for perceptual awareness in human infants.

The extent to which young human infants are conscious, in the sense of being perceptually aware of their environment, has been long debated. A new study has revealed that infants do exhibit a key signature of consciousness - the attentional blink - but this early consciousness changes with age.

Temporal Predictability Modulates Cortical Activity and Functional Connectivity in the Frontoparietal Network in 6-Month-Old Infants.

Despite the abundance of behavioral evidence showing the interaction between attention and prediction in infants, the neural underpinnings of this interaction are not yet well understood. The endogenous attentional function in adults have been largely localized to the frontoparietal network. However, resting-state and neuroanatomical investigations have found that this frontoparietal network exhibits a protracted developmental trajectory and involves weak and unmyelinated long-range connections early in infancy. Can this developmentally nascent network still be modulated by predictions? Here, we conducted the first investigation of infant frontoparietal network engagement as a function of the predictability of visual events. Using functional near-infrared spectroscopy, the hemodynamic response in the frontal, parietal, and occipital lobes was analyzed as infants watched videos of temporally predictable or unpredictable sequences. We replicated previous findings of cortical signal attenuation in the frontal and sensory cortices in response to predictable sequences and extended these findings to the parietal lobe. We also estimated background functional connectivity (i.e., by regressing out task-evoked responses) to reveal that frontoparietal functional connectivity was significantly greater during predictable sequences compared to unpredictable sequences, suggesting that this frontoparietal network may underlie how the infant brain communicates predictions. Taken together, our results illustrate that temporal predictability modulates the activation and connectivity of the frontoparietal network early in infancy, supporting the notion that this network may be functionally available early in life despite its protracted developmental trajectory.

Explainable artificial intelligence based analysis for interpreting infant fNIRS data in developmental cognitive neuroscience.

In the last decades, non-invasive and portable neuroimaging techniques, such as functional near infrared spectroscopy (fNIRS), have allowed researchers to study the mechanisms underlying the functional cognitive development of the human brain, thus furthering the potential of Developmental Cognitive Neuroscience (DCN). However, the traditional paradigms used for the analysis of infant fNIRS data are still quite limited. Here, we introduce a multivariate pattern analysis for fNIRS data, xMVPA, that is powered by eXplainable Artificial Intelligence (XAI). The proposed approach is exemplified in a study that investigates visual and auditory processing in six-month-old infants. xMVPA not only identified patterns of cortical interactions, which confirmed the existent literature; in the form of conceptual linguistic representations, it also provided evidence for brain networks engaged in the processing of visual and auditory stimuli that were previously overlooked by other methods, while demonstrating similar statistical performance.

How an infant's active response to structured experience supports perceptual-cognitive development.

Previous research on perceptual and cognitive development has predominantly focused on infants' passive response to experience. For example, if infants are exposed to acoustic patterns in the background while they are engaged in another activity, what are they able to learn? However, recent work in this area has revealed that even very young infants are also capable of active perceptual and cognitive responses to experience. Specifically, recent neuroimaging work showed that infants' perceptual systems predict upcoming sensory events and that learning to predict new events rapidly modulates the responses of their perceptual systems. In addition, there is new evidence that young infants have access to endogenous attention and their prediction and attention are rapidly and robustly modified through learning about patterns in the environment. In this chapter, we present a synthesis of the existing research on the impact of infants' active responses to experience and argue that this active engagement importantly supports infants' perceptual-cognitive development. To this end, we first define what a mechanism of active engagement is and examine how learning, selective attention, and prediction can be considered active mechanisms. Then, we argue that these active mechanisms become engaged in response to higher-order environmental structures, such as temporal, spatial, and relational patterns, and review both behavioral and neural evidence of infants' active responses to these structures or patterns. Finally, we discuss how this active engagement in infancy may give rise to the emergence of specialized perceptual-cognitive systems and highlight directions for future research.

Using pupillometry to investigate predictive processes in infancy.

Prediction, a prospective cognitive process, is increasingly believed to be crucial for adult cognition and learning. Despite decades of targeted research on prediction in adults, methodological limitations still exist for investigating prediction in infancy. In this article, we argue that pupillometry, or the measurement of pupil size, is an effective method to examine predictive processing in infants and will expand on existing methods (namely looking time and anticipatory eye movements). In particular, we argue that there are three specific features of pupillometry that make it particularly useful for augmenting the investigation of prediction in infancy. First, pupillometry has excellent temporal resolution that will facilitate the differentiation of prediction subcomponents. Second, pupillometry is highly continuous across the life span, allowing researchers to directly compare responses between infants and adults using an identical paradigm. Third, pupillometry can be used in conjunction with other behavioral measures, allowing for different yet complementary results. In addition, we review relevant adult and infant pupillometry studies that will facilitate infancy researchers to adopt this technique. Overall, pupillometry is particularly useful in investigating prediction in infancy and opens up several avenues for developmental research.

Video-based motion-resilient reconstruction of three-dimensional position for functional near-infrared spectroscopy and electroencephalography head mounted probes.

Significance: We propose a video-based, motion-resilient, and fast method for estimating the position of optodes on the scalp. Aim: Measuring the exact placement of probes (e.g., electrodes and optodes) on a participant's head is a notoriously difficult step in acquiring neuroimaging data from methods that rely on scalp recordings (e.g., electroencephalography and functional near-infrared spectroscopy) and is particularly difficult for any clinical or developmental population. Existing methods of head measurements require the participant to remain still for a lengthy period of time, are laborious, and require extensive training. Therefore, a fast and motion-resilient method is required for estimating the scalp location of probes. Approach: We propose an innovative video-based method for estimating the probes' positions relative to the participant's head, which is fast, motion-resilient, and automatic. Our method builds on capitalizing the advantages and understanding the limitations of cutting-edge computer vision and machine learning tools. We validate our method on 10 adult subjects and provide proof of feasibility with infant subjects. Results: We show that our method is both reliable and valid compared to existing state-of-the-art methods by estimating probe positions in a single measurement and by tracking their translation and consistency across sessions. Finally, we show that our automatic method is able to estimate the position of probes on an infant head without lengthy offline procedures, a task that has been considered challenging until now. Conclusions: Our proposed method allows, for the first time, the use of automated spatial co-registration methods on developmental and clinical populations, where lengthy, motion-sensitive measurement methods routinely fail.

Cortical Transformation of Stimulus Space in Order to Linearize a Linearly Inseparable Task.

The human brain is able to learn difficult categorization tasks, even ones that have linearly inseparable boundaries; however, it is currently unknown how it achieves this computational feat. We investigated this by training participants on an animal categorization task with a linearly inseparable prototype structure in a morph shape space. Participants underwent fMRI scans before and after 4 days of behavioral training. Widespread representational changes were found throughout the brain, including an untangling of the categories' neural patterns that made them more linearly separable after behavioral training. These neural changes were task dependent, as they were only observed while participants were performing the categorization task, not during passive viewing. Moreover, they were found to occur in frontal and parietal areas, rather than ventral temporal cortices, suggesting that they reflected attentional and decisional reweighting, rather than changes in object recognition templates. These results illustrate how the brain can flexibly transform neural representational space to solve computationally challenging tasks.

Memory integration into visual perception in infancy, childhood, and adulthood.

We compared the influence of prior knowledge on visual perception in infants, children, and adults in order to explore the developmental trajectory by which prior knowledge is integrated with new sensory input. Using an identical task across age groups, we tested how participants' accumulated experience affected their ability to judge the relative saturation levels within a pair of sequentially-presented stimuli. We found that infants and children, relative to adults, showed greater influence of the current observation and reduced influence of memory in their perception. In fact, infants and children outperformed adults in discriminating between different levels of saturation, and their performance was less biased by previously-experienced exemplars. Thus, the development of perceptual integration of memory leads to less precise discrimination in the moment, but allows observers to make use of their prior experience in interpreting a complex sensory environment.

A Computational Role for Top-Down Modulation from Frontal Cortex in Infancy.

Recent findings have shown that full-term infants engage in top-down sensory prediction, and these predictions are impaired as a result of premature birth. Here, we use an associative learning model to uncover the neuroanatomical origins and computational nature of this top-down signal. Infants were exposed to a probabilistic audiovisual association. We find that both groups (full term, preterm) have a comparable stimulus-related response in sensory and frontal lobes and track prediction error in their frontal lobes. However, preterm infants differ from their full-term peers in weaker tracking of prediction error in sensory regions. We infer that top-down signals from the frontal lobe to the sensory regions carry information about prediction error. Using computational learning models and comparing neuroimaging results from full-term and preterm infants, we have uncovered the computational content of top-down signals in young infants when they are engaged in a probabilistic associative learning.

Opposing Timing Constraints Severely Limit the Use of Pupillometry to Investigate Visual Statistical Learning.

Majority of visual statistical learning (VSL) research uses only offline measures, collected after the familiarization phase (i.e., learning) has occurred. Offline measures have revealed a lot about the extent of statistical learning (SL) but less is known about the learning mechanisms that support VSL. Studies have shown that prediction can be a potential learning mechanism for VSL, but it is difficult to examine the role of prediction in VSL using offline measures alone. Pupil diameter is a promising online measure to index prediction in VSL because it can be collected during learning, requires no overt action or task and can be used in a wide-range of populations (e.g., infants and adults). Furthermore, pupil diameter has already been used to investigate processes that are part of prediction such as prediction error and updating. While the properties of pupil diameter have the potentially to powerfully expand studies in VSL, through a series of three experiments, we find that the two are not compatible with each other. Our results revealed that pupil diameter, used to index prediction, is not related to offline measures of learning. We also found that pupil differences that appear to be a result of prediction, are actually a result of where we chose to baseline instead. Ultimately, we conclude that the fast-paced nature of VSL paradigms make it incompatible with the slow nature of pupil change. Therefore, our findings suggest pupillometry should not be used to investigate learning mechanisms in fast-paced VSL tasks.

The blowfish effect: children and adults use atypical exemplars to infer more narrow categories during word learning.

Learners preferentially interpret novel nouns at the basic level ('dog') rather than at a more narrow level ('Labrador'). This 'basic-level bias' is mitigated by statistics: children and adults are more likely to interpret a novel noun at a more narrow label if they witness 'a suspicious coincidence' - the word applied to three exemplars of the same narrow category. Independent work has found that exemplar typicality influences learners' inferences and category learning. We bring these lines of work together to investigate whether the content (typicality) of a single exemplar affects the level of interpretation of words and whether an atypicality effect interacts with input statistics. Results demonstrate that both four- to five-year-olds and adults tend to assign a narrower interpretation to a word if it is exemplified by an atypical category member. This atypicality effect is roughly as strong as, and independent of, the suspicious coincidence effect, which is replicated.