Lauren L. Emberson

Top-down modulation in the infant brain: Learning-induced expectations rapidly affect the sensory cortex at 6 months

Significance Although infants are excellent learners, it is unclear whether infants use neural strategies similar to those of adults to track changes in their environment. One adult neural strategy is to use feedback connections to modulate sensory cortices based on their expectations. The current study provides, to our knowledge, the first evidence that the fundamental architecture required for sensory feedback is already in place in infancy. This top-down modulation is especially impressive because the study employs an audiovisual task that requires the flexible use of long-range neural connections, and the infant brain is dominated by short-range neural connections with weak (e.g., unmyelinated) long-range connections. These results suggest that learners can use sophisticated top-down feedback neural strategies from an early age. Recent theoretical work emphasizes the role of expectation in neural processing, shifting the focus from feed-forward cortical hierarchies to models that include extensive feedback (e.g., predictive coding). Empirical support for expectation-related feedback is compelling but restricted to adult humans and nonhuman animals. Given the considerable differences in neural organization, connectivity, and efficiency between infant and adult brains, it is a crucial yet open question whether expectation-related feedback is an inherent property of the cortex (i.e., operational early in development) or whether expectation-related feedback develops with extensive experience and neural maturation. To determine whether infants’ expectations about future sensory input modulate their sensory cortices without the confounds of stimulus novelty or repetition suppression, we used a cross-modal (audiovisual) omission paradigm and used functional near-infrared spectroscopy (fNIRS) to record hemodynamic responses in the infant cortex. We show that the occipital cortex of 6-month-old infants exhibits the signature of expectation-based feedback. Crucially, we found that this region does not respond to auditory stimuli if they are not predictive of a visual event. Overall, these findings suggest that the young infant’s brain is already capable of some rudimentary form of expectation-based feedback.

Hemodynamic Correlates of Cognition in Human Infants

Over the past 20 years, the field of cognitive neuroscience has relied heavily on hemodynamic measures of blood oxygenation in local regions of the brain to make inferences about underlying cognitive processes. These same functional magnetic resonance imaging (fMRI) and functional near-infrared spectroscopy (fNIRS) techniques have recently been adapted for use with human infants. We review the advantages and disadvantages of these two neuroimaging methods for studies of infant cognition, with a particular emphasis on their technical limitations and the linking hypotheses that are used to draw conclusions from correlational data. In addition to summarizing key findings in several domains of infant cognition, we highlight the prospects of improving the quality of fNIRS data from infants to address in a more sophisticated way how cognitive development is mediated by changes in underlying neural mechanisms.

Combining fMRI and behavioral measures to examine the process of human learning

Prior to the advent of fMRI, the primary means of examining the mechanisms underlying learning were restricted to studying human behavior and non-human neural systems. However, recent advances in neuroimaging technology have enabled the concurrent study of human behavior and neural activity. We propose that the integration of behavioral response with brain activity provides a powerful method of investigating the process through which internal representations are formed or changed. Nevertheless, a review of the literature reveals that many fMRI studies of learning either (1) focus on outcome rather than process or (2) are built on the untested assumption that learning unfolds uniformly over time. We discuss here various challenges faced by the field and highlight studies that have begun to address them. In doing so, we aim to encourage more research that examines the process of learning by considering the interrelation of behavioral measures and fMRI recording during learning.

Learning to sample: Eye tracking and fmri indices of changes in object perception

We used an fMRI/eye-tracking approach to examine the mechanisms involved in learning to segment a novel, occluded object in a scene. Previous research has suggested a role for effective visual sampling and prior experience in the development of mature object perception. However, it remains unclear how the naive system integrates across variable sampled experiences to induce perceptual change. We generated a Target Scene in which a novel occluded Target Object could be perceived as either “disconnected” or “complete.” We presented one group of participants with this scene in alternating sequence with variable visual experience: three Paired Scenes consisting of the same Target Object in variable rotations and states of occlusion. A second control group was presented with similar Paired Scenes that did not incorporate the Target Object. We found that, relative to the Control condition, participants in the Training condition were significantly more likely to change their percept from “disconnected” to “connected,” as indexed by pretraining and posttraining test performance. In addition, gaze patterns during Target Scene inspection differed as a function of variable object exposure. We found increased looking to the Target Object in the Training compared with the Control condition. This pattern was not restricted to participants who changed their initial “disconnected” object percept. Neuroimaging data suggest an involvement of the hippocampus and BG, as well as visual cortical and fronto-parietal regions, in using ongoing regular experience to enable changes in amodal completion.

Using fNIRS to examine occipital and temporal responses to stimulus repetition in young infants: Evidence of selective frontal cortex involvement

How does the developing brain respond to recent experience? Repetition suppression (RS) is a robust and well-characterized response of to recent experience found, predominantly, in the perceptual cortices of the adult brain. We use functional near-infrared spectroscopy (fNIRS) to investigate how perceptual (temporal and occipital) and frontal cortices in the infant brain respond to auditory and visual stimulus repetitions (spoken words and faces). In Experiment 1, we find strong evidence of repetition suppression in the frontal cortex but only for auditory stimuli. In perceptual cortices, we find only suggestive evidence of auditory RS in the temporal cortex and no evidence of visual RS in any ROI. In Experiments 2 and 3, we replicate and extend these findings. Overall, we provide the first evidence that infant and adult brains respond differently to stimulus repetition. We suggest that the frontal lobe may support the development of RS in perceptual cortices.

Statistical learning is constrained to less abstract patterns in complex sensory input (but not the least).

The influence of statistical information on behavior (either through learning or adaptation) is quickly becoming foundational to many domains of cognitive psychology and cognitive neuroscience, from language comprehension to visual development. We investigate a central problem impacting these diverse fields: when encountering input with rich statistical information, are there any constraints on learning? This paper examines learning outcomes when adult learners are given statistical information across multiple levels of abstraction simultaneously: from abstract, semantic categories of everyday objects to individual viewpoints on these objects. After revealing statistical learning of abstract, semantic categories with scrambled individual exemplars (Exp. 1), participants viewed pictures where the categories as well as the individual objects predicted picture order (e.g., bird1—dog1, bird2—dog2). Our findings suggest that participants preferentially encode the relationships between the individual objects, even in the presence of statistical regularities linking semantic categories (Exps. 2 and 3). In a final experiment we investigate whether learners are biased towards learning object-level regularities or simply construct the most detailed model given the data (and therefore best able to predict the specifics of the upcoming stimulus) by investigating whether participants preferentially learn from the statistical regularities linking individual snapshots of objects or the relationship between the objects themselves (e.g., bird_picture1— dog_picture1, bird_picture2—dog_picture2). We find that participants fail to learn the relationships between individual snapshots, suggesting a bias towards object-level statistical regularities as opposed to merely constructing the most complete model of the input. This work moves beyond the previous existence proofs that statistical learning is possible at both very high and very low levels of abstraction (categories vs. individual objects) and suggests that, at least with the current categories and type of learner, there are biases to pick up on statistical regularities between individual objects even when robust statistical information is present at other levels of abstraction. These findings speak directly to emerging theories about how systems supporting statistical learning and prediction operate in our structure-rich environments. Moreover, the theoretical implications of the current work across multiple domains of study is already clear: statistical learning cannot be assumed to be unconstrained even if statistical learning has previously been established at a given level of abstraction when that information is presented in isolation.

Decoding the infant mind: Multivariate pattern analysis (MVPA) using fNIRS

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). FNIRS is a neuroimaging modality that records the same physiological signal as fMRI but without the constraints of MRI, and with better spatial localization than EEG. However, research in the fNIRS community largely lacks the analytic sophistication of analogous fMRI work, restricting the application of this imaging technology. The current paper presents a method of multivariate pattern analysis for fNIRS that allows the authors to decode the infant mind (a key fNIRS population). Specifically, multivariate pattern analysis (MVPA) employs a correlation-based decoding method where a group model is constructed for all infants except one; both average patterns (i.e., infant-level) and single trial patterns (i.e., trial-level) of activation are decoded. Between subjects decoding is a particularly difficult task, because each infant has their own somewhat idiosyncratic patterns of neural activation. The fact that our method succeeds at across-subject decoding demonstrates the presence of group-level multi-channel regularities across infants. The code for implementing these analyses has been made readily available online to facilitate the quick adoption of this method to advance the methodological tools available to the fNIRS researcher.

Isolating the effects of surface vasculature in infant neuroimaging using short-distance optical channels: a combination of local and global effects

Abstract. Functional near-infrared spectroscopy (fNIRS) records hemodynamic changes in the cortex arising from neurovascular coupling. However, (noninvasive) fNIRS recordings also record surface vascular signals arising from noncortical sources (e.g., in the skull, skin, dura, and other tissues located between the sensors and the brain). A current and important focus in the fNIRS community is determining how to remove these noncortical vascular signals to reduce noise and to prevent researchers from erroneously attributing responses to cortical sources. The current study is the first to test a popular method for removing signals from the surface vasculature (removing short, 1 cm, channel recordings from long, 3 cm, channel recordings) in human infants, a population frequently studied using fNIRS. We find evidence that this method does remove surface vasculature signals and indicates the presence of both local and global surface vasculature signals. However, we do not find that the removal of this information changes the statistical inferences drawn from the data. This latter result not only questions the importance of removing surface vasculature responses for empiricists employing this method, but also calls for future research using other tasks (e.g., ones with a weaker initial result) with this population and possibly additional methods for removing signals arising from the surface vasculature in infants.

The Lateral Occipital Cortex (LOC) is Selective for Object Shape, not Texture/Color, at 6 months

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. We use functional near-infrared spectroscopy (fNIRS), an emerging optical method for recording cortical hemodynamics, to perform neuroimaging with this very young population. Whereas previous fNIRS studies have suffered from imprecise neuroanatomical localization, we rely on the most rigorous MR coregistration of fNIRS data to date to image the infant LOC. We find surprising evidence that at 6 months the LOC has functional specialization that is highly similar to adults. Following Cant and Goodale (2007), we investigate whether the LOC tracks shape information and not other cues to object identity (e.g., texture/material). This finding extends evidence of LOC specialization from early childhood into infancy and earlier than developmental trajectories of high-level visual regions. SIGNIFICANCE STATEMENT Understanding visual development is crucial to understanding the nature of visual representations in the human brain. Previous studies of visual development have investigated children (4 years and older) and high-level visual areas. This study expands our knowledge of visual development by investigating the functional development of mid-level vision [lateral occipital cortex (LOC)] early in infancy. We find surprisingly adult-like functional specialization of the LOC by 6 months of age: infants exhibit shape selectivity, but not object selectivity, in this region.

Tracing trajectories of audio-visual learning in the infant brain.

Although infants begin learning about their environment before they are born, little is known about how the infant brain changes during learning. Here, we take the initial steps in documenting how the neural responses in the brain change as infants learn to associate audio and visual stimuli. Using functional near-infrared spectroscopy (fNRIS) to record hemodynamic responses in the infant cortex (temporal, occipital, and frontal cortex), we find that across the infant brain, learning is characterized by an increase in activation followed by a decrease. We take this U-shaped response as evidence of repetition enhancement during early stages of learning and repetition suppression during later stages, a result that mirrors the Hunter and Ames model of infant visual preference. Furthermore, we find that the neural response to violations of the learned associations can be predicted by the shape of the learning curve in temporal and occipital cortex. These data provide the first look at the shape of the neural response during audio-visual associative learning in infancy establishing that diverse regions of the infant brain exhibit systematic changes across the time-course of learning.