Publications by authors named "Lauren L Emberson"

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.

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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.

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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.

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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.

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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.

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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.

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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.

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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).

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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.

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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).

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: We propose a video-based, motion-resilient, and fast method for estimating the position of optodes on the scalp. : Measuring the exact placement of probes (e.g.

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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.

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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.

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Majority of visual statistical learning (VSL) research uses only offline measures, collected after the familiarization phase (i.e., learning) has occurred.

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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.

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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.

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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.

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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.

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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.

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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.

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Behavioral evidence has shown that humans automatically develop internal representations adapted to the temporal and spatial statistics of the environment. Building on prior fMRI studies that have focused on statistical learning of temporal sequences, we investigated the neural substrates and mechanisms underlying statistical learning from scenes with a structured spatial layout. Our goals were twofold: (1) to determine discrete brain regions in which degree of learning (i.

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This study uses representational similarity-based neural decoding to test whether semantic information elicited by words and pictures is encoded in functional near-infrared spectroscopy (fNIRS) data. In experiment 1, subjects passively viewed eight audiovisual word and picture stimuli for 15 min. Blood oxygen levels were measured using the Hitachi ETG-4000 fNIRS system with a posterior array over the occipital lobe and a left lateral array over the temporal lobe.

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The MRI environment restricts the types of populations and tasks that can be studied by cognitive neuroscientists (e.g., young infants, face-to-face communication).

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Understanding how the human visual system develops is crucial to understanding the nature and organization of our complex and varied visual representations. However, previous investigations of the development of the visual system using fMRI are primarily confined to a subset of the visual system (high-level vision: faces, scenes) and relatively late in visual development (starting at 4-5 years of age). The current study extends our understanding of human visual development by presenting the first systematic investigation of a mid-level visual region [the lateral occipital cortex (LOC)] in a population much younger than has been investigated in the past: 6 month olds.

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A prominent theoretical view is that the brain is inherently predictive [1, 2] and that prediction helps drive the engine of development [3, 4]. Although infants exhibit neural signatures of top-down sensory prediction [5, 6], in order to establish that prediction supports development, it must be established that deficits in early prediction abilities alter trajectories. We investigated prediction in infants born prematurely, a leading cause of neuro-cognitive impairment worldwide [7].

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