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.

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.

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.

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.

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.

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.

Infants use knowledge of emotions to augment face perception: Evidence of top-down modulation of perception early in life.

While top-down modulation is believed to be central to adult perception, the developmental origins of this ability are unclear. Here, we present a direct, behavioral investigation of top-down modulation of perception in infancy using emotional face perception as a test case. We investigated whether 9-month-olds can modulate their face perception based on predictive, auditory emotional cues without any training or familiarization procedure. Infants first heard a 3-second emotional vocal sound (happy/angry) while their gaze was held in the center of the screen. Then, they were presented with a pair of emotional and neutral faces images without any audio sound. The faces were small (4.70° × 5.80°) and presented in randomized locations outside their focus of attention. We measured the initial latency to shift gaze to look at a congruent emotional face as an index of infants' pre-attentive perception of these faces. We found that infants' face perception was augmented by preceding emotional cues: They were faster to look at the emotional face after hearing an emotionally congruent sound than an incongruent one. Moreover, the emotional sounds boosted perception of congruent faces 200 ms after the onset of the faces. These top-down effects were robust for both happy and angry emotions, indicating a flexible and active control of perception based on different top-down cues. A control study further supported the view that the Congruency effect is due to a top-down influence on face perception rather than a rapid matching of cross-modal emotional signals. Together, these findings demonstrate that top-down modulation of perception is already quite sophisticated early in development. Raw data is available on Github (https://github.com/naiqixiao/CuedEmotion.git).

Comparing statistical learning across perceptual modalities in infancy: An investigation of underlying learning mechanism(s).

Statistical learning (SL), sensitivity to probabilistic regularities in sensory input, has been widely implicated in cognitive and perceptual development. Little is known, however, about the underlying mechanisms of SL and whether they undergo developmental change. One way to approach these questions is to compare SL across perceptual modalities. While a decade of research has compared auditory and visual SL in adults, we present the first direct comparison of visual and auditory SL in infants (8-10 months). Learning was evidenced in both perceptual modalities but with opposite directions of preference: Infants in the auditory condition displayed a novelty preference, while infants in the visual condition showed a familiarity preference. Interpreting these results within the Hunter and Ames model (1988), where familiarity preferences reflect a weaker stage of encoding than novelty preferences, we conclude that there is weaker learning in the visual modality than the auditory modality for this age. In addition, we found evidence of different developmental trajectories across modalities: Auditory SL increased while visual SL did not change for this age range. The results suggest that SL is not an abstract, amodal ability; for the types of stimuli and statistics tested, we find that auditory SL precedes the development of visual SL and is consistent with recent work comparing SL across modalities in older children.

Prediction in infants and adults: A pupillometry study.

Adults use both bottom-up sensory inputs and top-down signals to generate predictions about future sensory inputs. Infants have also been shown to make predictions with simple stimuli and recent work has suggested top-down processing is available early in infancy. However, it is unknown whether this indicates that top-down prediction is an ability that is continuous across the lifespan or whether an infant's ability to predict is different from an adult's, qualitatively or quantitatively. We employed pupillometry to provide a direct comparison of prediction abilities across these disparate age groups. Pupil dilation response (PDR) was measured in 6-month olds and adults as they completed an identical implicit learning task designed to help learn associations between sounds and pictures. We found significantly larger PDR for visual omission trials (i.e. trials that violated participants' predictions without the presentation of new stimuli to control for bottom-up signals) compared to visual present trials (i.e. trials that confirmed participants' predictions) in both age groups. Furthermore, a computational learning model that is closely linked to prediction error (Rescorla-Wagner model) demonstrated similar learning trajectories suggesting a continuity of predictive capacity and learning across the two age groups.

Expectation affects neural repetition suppression in infancy.

Recent work provides evidence that the infant brain is able to make top-down predictions, but this has been explored only in limited contexts and domains. We build upon this evidence of predictive processing in infants using a new paradigm to examine auditory repetition suppression (RS). RS is a well-documented neural phenomenon in which repeated presentations of the same stimulus result in reduced neural activation compared to non-repeating stimuli. Many theories explain RS using bottom-up mechanisms, but recent work has posited that top-down expectation and predictive coding may bias, or even explain, RS. Here, we investigate whether RS in the infant brain is similarly sensitive to top-down mechanisms. We use fNIRS to measure infants' neural response in two experimental conditions, one in which variability in stimulus presentation is expected (occurs 75% of the time) and a control condition where variability and repetition are equally likely (50% of the time). We show that 6-month-old infants exhibit attenuated frontal lobe response to blocks of variable auditory stimuli during contexts when variability is expected as compared to the control condition. These findings suggest that young infants' neural responses are modulated by predictions gained from experience and not simply by bottom-up mechanisms.

The emergence of top-down, sensory prediction during learning in infancy: A comparison of full-term and preterm infants.

Prematurity alters developmental trajectories in preterm infants even in the absence of medical complications. Here, we use fNIRS and learning tasks to probe the nature of the developmental differences between preterm and full-term born infants. Our recent work has found that prematurity disrupts the ability to engage in top-down sensory prediction after learning. We now examine the neural changes during the learning that precede prediction. In full-terms, we found modulation of all cortical regions examined during learning (temporal, frontal, and occipital). By contrast, preterm infants had no evidence of neural changes in the occipital lobe selectively. This is striking as the learning task leads to the emergence of visual prediction. Moreover, the shape of individual infants' occipital lobe trajectories (regardless of prematurity) predicts subsequent visual prediction abilities. These results suggest that modulation of sensory cortices during learning is closely related to the emergence of top-down signals and further indicates that developmental differences in premature infants may be associated with deficits in top-down processing.