Young infants process prediction errors at the theta rhythm

Event-Related Spectral Perturbations differences analyzed in standard-deviant tone sequences presented in passive and active conditions

The predictive coding theory, although a well-supported framework for understanding brain processing, remains elusive regarding how different brain rhythms contribute to error prediction and modify the a priori probabilities of predictive events. This study addresses this issue by analyzing Event-Related Spectral Perturbations (ERSP) generated during an auditory oddball paradigm presented in both a passive and active condition. The design involved sequences of four tones, where the last tone was either predictable (standard, S), completing the scale, or less predictable (deviant, D) when the first tone was occasionally repeated. In the passive condition, participants were instructed to ignore the sounds, whereas, in the active condition, they were asked to press the up or down arrow on a keyboard depending on whether the last tone of the sequence presented a higher or lower frequency than the previous one. This experimental design aimed to bias cognitive processing towards predictable (S) or unpredictable scenarios (D) in two different conditions: passive and attentional. EEG data from 13 channels were analyzed with Morlet wavelets, revealing event-related synchronization (ERS) and desynchronization (ERD) induced by the stimuli. Early theta activity was key in computing prediction errors and updating next-trial expectations. In the active condition, theta responses were higher in D than in S trials, indicating enhanced prediction error processing with attention. Early beta activity also increased during D, likely reflecting motor adjustments. These findings emphasize the critical role of early theta rhythms and the amplifying effect of attention on prediction error processing.

EEG time-frequency dynamics of early cognitive control development

Cognitive control is crucial for goal-directed behavior, and essential for other aspects of cognitive and socioemotional development. This review examines when and how the neural dynamics of cognitive control emerge and develop, focusing on electroencephalography measures used to study cognitive control in infants and children. We argue that time-frequency analyses are uniquely able to capture two distinct components of cognitive control: 1) the detection that control is needed, and 2) the instantiation of control. Starting in infancy and increasing across childhood and adolescence, studies suggest the signal strength and consistency of midfrontal theta and delta oscillations are involved in processes that detect the need for control. For control instantiation, there is evidence that theta band connectivity between midfrontal and lateral-frontal cortices is present from early childhood. There is also evidence for the involvement of midfrontal theta power in the instantiation of control in infancy. We further review emerging evidence that indicates individual differences in midfrontal theta are not only proximally related to behavior, but also sensitive to variations in early experience and risk for psychopathology, providing a neural mechanism linking early adversity to future psychopathology. We discuss needed future steps, including novel paradigms, computational models, and aperiodic/periodic modeling of EEG.

Oscillatory But Not Aperiodic Frontal Brain Activity Predicts the Development of Executive Control From Infancy to Toddlerhood

Executive control (EC) emerges in the first year of life, with the ability to inhibit prepotent responses (inhibitory control [IC]) and to flexibly readapt (cognitive flexibility [CF]) steadily improving. Simultaneously, electrophysiological brain activity undergoes profound reconfiguration, which has been linked to individual variability in EC. However, most studies exploring this relationship have used relative/absolute power and tasks that combine different executive processes. In addition, brain activity conflates aperiodic and oscillatory activity, which hinders the interpretation of the relationship between power and cognition. In the current study, we used the Early Childhood Inhibitory Touchscreen Task (ECITT) to examine the development of EC skills from 9 to 16 months in a longitudinal sample, and related performance of the task to resting-state EEG (rs-EEG) power, separating oscillatory and aperiodic activity. Our results showed improvement in IC but not in CF with age. In addition, alpha and theta oscillatory activity were concurrent (9-mo.) and longitudinal predictors of CF in toddlerhood, whereas the aperiodic exponent of the EEG signal did not contribute to EC. These findings demonstrate the relevance of oscillatory brain activity for cognitive development and provide an early brain marker for the early development of EC.

Coregistration of EEG and eye-tracking in infants and developing populations

Infants cannot be instructed where to look; therefore, infant researchers rely on observation of their participant's gaze to make inferences about their cognitive processes. They therefore started studying infant attention in the real world from early on. Developmental researchers were early adopters of methods combining observations of gaze and behaviour with electroencephalography (EEG) to study attention and other cognitive functions. However, the direct combination of eye-tracking methods and EEG to test infants is still rare, as it includes specific challenges. The current article reviews the development of co-registration research in infancy. It points out specific challenges of co-registration in infant research and suggests ways to overcome them. It ends with recommendations for implementing the co-registration of EEG and eye-tracking in infant research to maximise the benefits of the two measures and their combination and to orient on Open Science principles while doing so. In summary, this work shows that the co-registration of EEG and eye-tracking in infant research can be beneficial to studying natural and real-world behaviour despite its challenges.

Neural Markers of Attention at 6 Months Associate With Later Attentional Control Performance

Attentional control is key to the development of executive functions. Previous research indicates that individual differences in attentional control behaviour may be stable from 6 months. Here, we analyse electroencephalogram data collected from 59 6-month-olds to gain insights into the neural processes underlying attentional control in infancy. First, we examine the neural activity preceding distinct looking behaviours in an attentional control task at 6 months. Second, we test whether those neural markers show predictive associations to behavioural measures of attentional control (Freeze-Frame task) and executive function (A-not-B task) in the same infants at 9 months. Whilst our data do not show evidence that 6-9 Hz power is implicated in attentional control at 6 months, or that the P1 ERP component plays a role in our attentional control task, we do find evidence that corroborates and extends research linking 3-6 Hz power to attentional control. At the group level, frontal 3-6 Hz power recorded whilst looking to a central target before the onset of a peripheral distractor was greater during trials where infants subsequently looked to the distractor, compared with trials where they did not look. Higher 3-6 Hz power in trials where the infant did not look to a peripheral distractor was predictive of less distractibility at 9 months, and higher 3 Hz power in trials where infants did look to the distractor strengthened the predictive association from 6-month EEG to 9-month behaviour. We suggest 3-6 Hz activity may be sensitive to multiple processes, such as anticipatory attention, and the ability to maintain attention on a target.

From Infancy to Childhood: A Comprehensive Review of Event- and Task-Related Brain Oscillations

Brain development from infancy through childhood involves complex structural and functional changes influenced by both internal and external factors. This review provides a comprehensive analysis of event and task-related brain oscillations, focusing on developmental changes across different frequency bands, including delta, theta, alpha, beta, and gamma. Electroencephalography (EEG) studies highlight that these oscillations serve as functional building blocks for sensory and cognitive processes, with significant variations observed across different developmental stages. Delta oscillations, primarily associated with deep sleep and early cognitive demands, gradually diminish as children age. Theta rhythms, crucial for attention and memory, display a distinct pattern in early childhood, evolving with cognitive maturation. Alpha oscillations, reflecting thalamocortical interactions and cognitive performance, increase in complexity with age. Beta rhythms, linked to active thinking and problem-solving, show developmental differences in motor and cognitive tasks. Gamma oscillations, associated with higher cognitive functions, exhibit notable changes in response to sensory stimuli and cognitive tasks. This review underscores the importance of understanding oscillatory dynamics to elucidate brain development and its implications for sensory and cognitive processing in childhood. The findings provide a foundation for future research on developmental neuroscience and potential clinical applications.

Infants evaluate informativeness of evidence and predict causal events as revealed in theta oscillations and predictive looking

This study investigates 16-month-old infants' sensitivity to the informativeness of evidence and its potential link to infants' ability to draw accurate causal inferences and predict unfolding events. Employing concurrent EEG and eye tracking, data from 66 infants revealed significantly increased theta oscillatory activity when infants expected to see causally unconfounded evidence compared to confounded evidence, suggesting heightened cognitive engagement in anticipation of informative evidence. Crucially, this difference was more pronounced in the subset of infants who later made correct predictions, suggesting that they had correctly inferred the causal structure based on the evidence presented. This research sheds light on infants' motivation to seek explanatory causal information, suggesting that even at 16 months, infants can strategically direct attention to situations conducive to acquiring informative evidence, potentially laying the groundwork for the impressive abilities of humans to rapidly acquire knowledge and develop causal theories of the world.

Interictal EEG features as computational biomarkers of West syndrome

BACKGROUND

West syndrome (WS) is a devastating epileptic encephalopathy with onset in infancy and early childhood. It is characterized by clustered epileptic spasms, developmental arrest, and interictal hypsarrhythmia on electroencephalogram (EEG). Hypsarrhythmia is considered the hallmark of WS, but its visual assessment is challenging due to its wide variability and lack of a quantifiable definition. This study aims to analyze the EEG patterns in WS and identify computational diagnostic biomarkers of the disease.

METHOD

Linear and non-linear features derived from EEG recordings of 31 WS patients and 20 age-matched controls were compared. Subsequently, the correlation of the identified features with structural and genetic abnormalities was investigated.

RESULTS

WS patients showed significantly elevated alpha-band activity (0.2516 vs. 0.1914, p < 0.001) and decreased delta-band activity (0.5117 vs. 0.5479, p < 0.001), particularly in the occipital region, as well as globally strengthened theta-band activity (0.2145 vs. 0.1655, p < 0.001) in power spectrum analysis. Moreover, wavelet-bicoherence analysis revealed significantly attenuated cross-frequency coupling in WS patients. Additionally, bi-channel coherence analysis indicated minor connectivity alterations in WS patients. Among the four non-linear characteristics of the EEG data (i.e., approximate entropy, sample entropy, permutation entropy, and wavelet entropy), permutation entropy showed the most prominent global reduction in the EEG of WS patients compared to controls (1.4411 vs. 1.5544, p < 0.001). Multivariate regression results suggested that genetic etiologies could influence the EEG profiles of WS, whereas structural factors could not.

SIGNIFICANCE

A combined global strengthening of theta activity and global reduction of permutation entropy can serve as computational EEG biomarkers for WS. Implementing these biomarkers in clinical practice may expedite diagnosis and treatment in WS, thereby improving long-term outcomes.

Theta activity and cognitive functioning: Integrating evidence from resting-state and task-related developmental electroencephalography (EEG) research

The theta band is one of the most prominent frequency bands in the electroencephalography (EEG) power spectrum and presents an interesting paradox: while elevated theta power during resting state is linked to lower cognitive abilities in children and adolescents, increased theta power during cognitive tasks is associated with higher cognitive performance. Why does theta power, measured during resting state versus cognitive tasks, show differential correlations with cognitive functioning? This review provides an integrated account of the functional correlates of theta across different contexts. We first present evidence that higher theta power during resting state is correlated with lower executive functioning, attentional abilities, language skills, and IQ. Next, we review research showing that theta power increases during memory, attention, and cognitive control, and that higher theta power during these processes is correlated with better performance. Finally, we discuss potential explanations for the differential correlations between resting/task-related theta and cognitive functioning, and offer suggestions for future research in this area.

The Development of Cognitive Control in Preschoolers and Kindergarteners: The Case of Post-Error Slowing and Delayed Disinhibition

This study aimed to investigate two specific behavioral manifestations of the executive attention systems in preschoolers and kindergarteners, beyond the unique contribution of intelligence. We tested post-error slowing [RT¯Post-error trial-RT¯Not post-error trial] as a marker of reactive control and delayed disinhibition as a novel marker for proactive control. One hundred and eighty preschool- and kindergarten-aged children, as well as their mothers (final sample: 155 children and 174 mothers), performed an adapted task based on Go/NoGo and Stroop-like paradigms-the emotional day-night task. The children showed reliable post-error slowing and delayed disinhibition (mean size effects of 238.18 ms and 58.31 ms, respectively), while the adult size effects were 40-50% smaller. The post-error slowing effect was present for both sexes in all the tested ages, while the delayed disinhibition effect was present only for girls. Both effects showed large individual differences that became smaller in adulthood. Our findings emphasize the earlier maturation of reactive control compared to proactive control, and the earlier maturation of proactive cognitive control in girls compared to boys.

Neural correlates involved in perspective-taking in early childhood

Learning to consider another person's perspective is pivotal in early social development. Still, little is known about the neural underpinnings involved in perspective-taking in early childhood. In this EEG study, we examined 4-year-old children's brain activity during a live, social interaction that involved perspective-taking. Children were asked to pass one of two toys to another person. To decide which toy to pass, they had to consider either their partner's perspective (perspective-taking) or visual features unrelated to their partner's perspective (control). We analyzed power changes in midfrontal and temporal-parietal EEG channels. The results indicated that children showed higher power around 7 Hz at right temporal-parietal channels for perspective-taking compared to control trials. This power difference was positively correlated with children's perspective-taking performance, specifically for trials in which they needed to pass the toy their partner could not see. A similar power difference at right temporal-parietal channels was seen when comparing perspective-taking trials where children's visual access mismatched rather than matched that of their partner. No differences were detected for midfrontal channels. In sum, we identified distinct neural activity as 4-year-olds considered another person's perspective in a live interaction; this activity converges with neural findings of adults' social processing network.

The theta-gamma code in predictive processing and mnemonic updating

Predictive processing has become a leading theory about how the brain works. Yet, it remains an open question how predictive processes are realized in the brain. Here I discuss theta-gamma coupling as one potential neural mechanism for prediction and model updating. Building on Lisman and colleagues SOCRATIC model, theta-gamma coupling has been associated with phase precession and learning phenomena in medio-temporal lobe of rodents, where it completes and retains a sequence of places or items (i.e., predictive models). These sequences may be updated upon prediction errors (i.e., model updating), signaled by dopaminergic inputs from prefrontal networks. This framework, spanning the molecular to the network level, matches excitingly well with recent findings on predictive processing, mnemonic updating, and perceptual foraging for the theta-gamma code in human cognition. In sum, I use the case of theta-gamma coupling to link the predictive processing account, a very general concept of how the brain works, to specific neural processes which may implement predictive processing and model updating at the cognitive, network, cellular and molecular level.

Communicative signals during joint attention promote neural processes of infants and caregivers

Communicative signals such as eye contact increase infants' brain activation to visual stimuli and promote joint attention. Our study assessed whether communicative signals during joint attention enhance infant-caregiver dyads' neural responses to objects, and their neural synchrony. To track mutual attention processes, we applied rhythmic visual stimulation (RVS), presenting images of objects to 12-month-old infants and their mothers (n = 37 dyads), while we recorded dyads' brain activity (i.e., steady-state visual evoked potentials, SSVEPs) with electroencephalography (EEG) hyperscanning. Within dyads, mothers either communicatively showed the images to their infant or watched the images without communicative engagement. Communicative cues increased infants' and mothers' SSVEPs at central-occipital-parietal, and central electrode sites, respectively. Infants showed significantly more gaze behaviour to images during communicative engagement. Dyadic neural synchrony (SSVEP amplitude envelope correlations, AECs) was not modulated by communicative cues. Taken together, maternal communicative cues in joint attention increase infants' neural responses to objects, and shape mothers' own attention processes. We show that communicative cues enhance cortical visual processing, thus play an essential role in social learning. Future studies need to elucidate the effect of communicative cues on neural synchrony during joint attention. Finally, our study introduces RVS to study infant-caregiver neural dynamics in social contexts.

Rhythmic visual stimulation as a window into early brain development: A systematic review

Rhythmic visual stimulation (RVS), the periodic presentation of visual stimuli to elicit a rhythmic brain response, is increasingly applied to reveal insights into early neurocognitive development. Our systematic review identified 69 studies applying RVS in 0- to 6-year-olds. RVS has long been used to study the development of the visual system and applications have more recently been expanded to uncover higher cognitive functions in the developing brain, including overt and covert attention, face and object perception, numeral cognition, and predictive processing. These insights are owed to the unique benefits of RVS, such as the targeted frequency and stimulus-specific neural responses, as well as a remarkable signal-to-noise ratio. Yet, neural mechanisms underlying the RVS response are still poorly understood. We discuss critical challenges and avenues for future research, and the unique potentials the method holds. With this review, we provide a resource for researchers interested in the breadth of developmental RVS research and hope to inspire the future use of this cutting-edge method in developmental cognitive neuroscience.

Infants are sensitive to the social signaling value of shared inefficient behaviors

Actions that are blatantly inefficient to achieve non-social goals are often used to convey information about agents' social affiliation, as in the case of rituals. We argue that when reproduced, actions that are individually inefficient acquire a social signaling value owing to the mechanisms that support humans' intuitive analysis of actions. We tested our hypothesis on 15-month-old infants who were familiarized with an agent that reproduced or merely observed the actions of efficient and inefficient individuals. Subsequently, we measured the infants' expectations of the agent's preferences for efficient and inefficient individuals. Our results confirmed that when agents act alone, infants expect a third-party to prefer efficient over inefficient agents. However, this pattern is entirely flipped if the third-party reproduces the agents' actions. In that case, infants expect inefficient agents to be preferred over efficient ones. Thus, reproducing actions whose rational basis is elusive can serve a critical social signaling function, accounting for why such behaviors are pervasive in human groups.

Alpha and theta brain activity in 9-month-old infants during a live referential gaze paradigm

The ability to establish a connection between the direction of the other's gaze and the object that is observed has important implications in the development of social cognition and learning. In this study, we analyzed alpha and theta band oscillations in one group of 9-month-old infants by implementing a face-to-face live paradigm, which presented the infants with a triadic social interaction with a real human being. We compared neural activations in two experimental conditions: Congruent and Incongruent gaze shift following the appearance of an object. In the Incongruent object-gaze shift condition, we observed an increase of the theta power in comparison with the Congruent condition. We also found an enhancement of the alpha activity during the Congruent versus the Incongruent object-gaze condition. These findings confirm the involvement of the theta and alpha band activity in the detection of the gaze of others when it shifts toward a referential target. We consider that the theta band modulation could be associated with the processing of unexpected events. Furthermore, the increase of the alpha band activity during the Congruent object-gaze condition seems to be in agreement with prior findings on the mechanisms of internally controlled attention that emerge before the first year of life. The implementation of a live paradigm elicited a partially different oscillatory pattern in comparison with non-live standard paradigms, supporting the importance of an ecological set-up reproducing real-life conditions to study the development of social cognition.

Beyond Infant's Looking: The Neural Basis for Infant Prediction Errors

Contemporary conceptualizations on infant cognitive development focus on predictive processes; the basic idea is that the brain continuously creates predictions about what is expected and that the divergence between predicted and actual perceived data yields a prediction error. This prediction error updates the model from which the predictions are generated and therefore is a basic mechanism for learning and adaptation to the dynamics of the ever-changing environment. In this article, we review the types of available empirical evidence supporting the idea that predictive processes can be found in infancy, especially emphasizing the contribution of electrophysiology as a potential method for testing the similarity of the brain mechanisms for processing prediction errors in infants to those of adults. In infants, as with older children, adolescents, and adults, predictions involve synchronization bursts of middle-central theta reflecting brain activity in the anterior cingulate cortex. We discuss how early in development such brain mechanisms develop and open questions that still remain to be empirically investigated.

Rhythms of human attention and memory: An embedded process perspective

It remains a dogma in cognitive neuroscience to separate human attention and memory into distinct modules and processes. Here we propose that brain rhythms reflect the embedded nature of these processes in the human brain, as evident from their shared neural signatures: gamma oscillations (30-90 Hz) reflect sensory information processing and activated neural representations (memory items). The theta rhythm (3-8 Hz) is a pacemaker of explicit control processes (central executive), structuring neural information processing, bit by bit, as reflected in the theta-gamma code. By representing memory items in a sequential and time-compressed manner the theta-gamma code is hypothesized to solve key problems of neural computation: (1) attentional sampling (integrating and segregating information processing), (2) mnemonic updating (implementing Hebbian learning), and (3) predictive coding (advancing information processing ahead of the real time to guide behavior). In this framework, reduced alpha oscillations (8-14 Hz) reflect activated semantic networks, involved in both explicit and implicit mnemonic processes. Linking recent theoretical accounts and empirical insights on neural rhythms to the embedded-process model advances our understanding of the integrated nature of attention and memory - as the bedrock of human cognition.

Intuitive physics learning in a deep-learning model inspired by developmental psychology

'Intuitive physics' enables our pragmatic engagement with the physical world and forms a key component of 'common sense' aspects of thought. Current artificial intelligence systems pale in their understanding of intuitive physics, in comparison to even very young children. Here we address this gap between humans and machines by drawing on the field of developmental psychology. First, we introduce and open-source a machine-learning dataset designed to evaluate conceptual understanding of intuitive physics, adopting the violation-of-expectation (VoE) paradigm from developmental psychology. Second, we build a deep-learning system that learns intuitive physics directly from visual data, inspired by studies of visual cognition in children. We demonstrate that our model can learn a diverse set of physical concepts, which depends critically on object-level representations, consistent with findings from developmental psychology. We consider the implications of these results both for AI and for research on human cognition.

Enhancing reproducibility in developmental EEG research: BIDS, cluster-based permutation tests, and effect sizes

Developmental research using electroencephalography (EEG) offers valuable insights in brain processes early in life, but at the same time, applying this sensitive technique to young children who are often non-compliant and have short attention spans comes with practical limitations. It is thus of particular importance to optimally use the limited resources to advance our understanding of development through reproducible and replicable research practices. Here, we describe methodological approaches that help maximize the reproducibility of developmental EEG research. We discuss how to transform EEG data into the standardized Brain Imaging Data Structure (BIDS) which organizes data according to the FAIR data sharing principles. We provide a tutorial on how to use cluster-based permutation testing to analyze developmental EEG data. This versatile test statistic solves the multiple comparison problem omnipresent in EEG analysis and thereby substantially decreases the risk of reporting false discoveries. Finally, we describe how to quantify effect sizes, in particular of cluster-based permutation results. Reporting effect sizes conveys a finding's impact and robustness which in turn informs future research. To demonstrate these methodological approaches to data organization, analysis and report, we use a publicly accessible infant EEG dataset and provide a complete copy of the analysis code.