The superior temporal sulcus (STS) plays a central role in auditory and linguistic processing and undergoes rapid development during the last trimester of gestation. Yet, the extent to which its development is shaped by early sensory experience remains unclear. Premature birth offers a unique opportunity to address this question, as it exposes the brain to an extra-uterine auditory environment at a critical stage of network maturation. We analyzed resting-state fMRI data in 116 neonates (63 males), scanned at term-equivalent age but born at varying gestational age (24.3 to 41.7 weeks gestational age) using the developing Human Connectome Project (dHCP) database. Functional connectivity was computed in native space using regions of interest based on each infant’s sulcal anatomy to assess the respective contributions of STS subregions. Our analyses reveal a functional division between the inferior and superior banks of the STS, with the inferior bank showing stronger connectivity to distant parietal and frontal areas along the dorsal language pathway. The left posterior STS emerged as a functional hub, displaying broad inter-area connectivity. Longer gestations correlated with increased local connectivity, notably in the right temporal region, despite equal age at scan. Additionally, female neonates exhibited stronger connectivity from the left posterior STS compared to males. These findings highlight the early emergence of adult-like auditory-linguistic networks and their sensitivity to the in-utero environment. Further research is needed to investigate the consequences of these early differences and to determine which postnatal interventions might help compensate, if necessary.

Interest in statistical learning in developmental studies stems from the observation that 8-month-olds were able to extract words from a monotone speech stream solely using the transition probabilities (TP) between syllables (Saffran et al., 1996). A simple mechanism was thus part of the human infant’s toolbox for discovering regularities in language. Since this seminal study, observations on statistical learning capabilities have multiplied across domains and species, challenging the hypothesis of a dedicated mechanism for language acquisition. Here, we leverage the two dimensions conveyed by speech –speaker identity and phonemes– to examine (1) whether neonates can compute TPs on one dimension despite irrelevant variation on the other and (2) whether the linguistic dimension enjoys an advantage over the voice dimension. In two experiments, we exposed neonates to artificial speech streams constructed by concatenating syllables while recording EEG. The sequence had a statistical structure based either on the phonetic content, while the voices varied randomly (Experiment 1) or on voices with random phonetic content (Experiment 2). After familiarisation, neonates heard isolated duplets adhering, or not, to the structure they were familiarised with. In both experiments, we observed neural entrainment at the frequency of the regularity and distinct Event-Related Potentials (ERP) to correct and incorrect duplets, highlighting the universality of statistical learning mechanisms and suggesting it operates on virtually any dimension the input is factorised. However, only linguistic duplets elicited a specific ERP component, potentially an N400 precursor, suggesting a lexical stage triggered by phonetic regularities already at birth. These results show that, from birth, multiple input regularities can be processed in parallel and feed different higher-order networks.

The emergence of symbolic thinking has been proposed as a dominant cognitive criterion to distinguish humans from other primates during hominisation. Although the proper definition of a symbol has been the subject of much debate, one of its simplest features is bidirectional attachment: the content is accessible from the symbol, and vice versa. Behavioural observations scattered over the past four decades suggest that this criterion might not be met in non-human primates, as they fail to generalise an association learned in one temporal order (A to B) to the reverse order (B to A). Here, we designed an implicit fMRI test to investigate the neural mechanisms of arbitrary audio–visual and visual–visual pairing in monkeys and humans and probe their spontaneous reversibility. After learning a unidirectional association, humans showed surprise signals when this learned association was violated. Crucially, this effect occurred spontaneously in both learned and reversed directions, within an extended network of high-level brain areas, including, but also going beyond, the language network. In monkeys, by contrast, violations of association effects occurred solely in the learned direction and were largely confined to sensory areas. We propose that a human-specific brain network may have evolved the capacity for reversible symbolic reference.

At the physical level, the experience of pitch has a single determinant: the repetition rate of a waveform in the acoustic signal. Yet, psychologists describe pitch as composed of two perceptual dimensions, height and chroma. Chroma accounts for octave equivalence, whereby sounds with fundamental frequencies at a 1:2 ratio are perceived as sharing the same pitch. A current controversy debates whether chroma is a basic perceptual property dependent on biological constraints or a higher-order cognitive construct shaped by culture. Here, we used high-density electroencephalography (EEG) and time-resolved multivariate pattern analyses to characterize pitch processing in humans at 3 months of age. We found that, when exposed to repetitive sequences of orchestral tones, infants encode two separate pitch-related dimensions automatically and with divergent dynamics. Namely, our classifiers isolated height-specific information from the neural signal rapidly after the onset of the auditory sequences. Beyond approximately 600 ms, the performance of pitch height decoders fell to chance level and did not recover. In contrast, neural patterns displaying octave equivalence were retrieved later in the trial, over multiple time windows throughout the unfolding of the auditory sequence, and after sequence offset. Overall, this study reveals that very early in human development, the pitch of naturally rich tones is processed over two distinct encoding stages, capturing not only their absolute height but also their relative position in the octave. We speculate that separate encoding mechanisms reflect distinct functional roles carried by the two dimensions.

Plato’s Republic, Einstein’s Theory of relativity, Vilvadi’s Four Seasons are all remarkable examples of humans’ unique ability to create and manipulate complex abstract structures, whether in language, mathematics or music. Yet the mechanisms by which children develop such abstract thinking, and the role of education and structured experiences such as musical practice in shaping these abilities remain unclear. To explore these questions, we conducted cross-sectional behavioral experiments with 566 children aged 4 to 8, spanning four educational grades, half of whom participated in a violin training program since the age of four. Two experiments examined how children encode, process and compress auditory sequences and visual patterns, while a third examined their sensitivity to geometric regularities. Our results reveal the emergence of symbolic reasoning as early as the start of formal schooling, yet with deeper abstraction as a function of grade. By first grade, children encoded complex auditory sequences within a Language of Thought (LoT) similar to adults. Additionally, when confronted with quadrilaterals, children showed increasing sensitivity to geometric regularities, suggesting a developmental transition from perceptual to symbolic reasoning. However, we did not observe significant impact of musical practice on abstraction abilities across any of the domains tested. We discuss whether and how the impact of education and extracurricular activities such as music could be enhanced. ### Competing Interest Statement The authors have declared no competing interest.

The need for attention to enable statistical learning is debated. Testing individuals with impaired consciousness offers valuable insight, but very few studies have been conducted due to the difficulties inherent in such studies. Here, we examined the ability of patients with varying levels of disorders of consciousness (DOC) to extract statistical regularities from an artificial language composed of randomly concatenated pseudowords by measuring frequency tagging in EEG. The objectives were firstly, to assess the automaticity of the segmentation process and the correlations between the level of covert consciousness and statistical learning capacities; secondly, to identify potential new diagnostic indicators. We observed that segmentation abilities were preserved in some minimally conscious patients, suggesting that auditory statistical learning is an inherently automatic low-level process. Due to significant inter-individual variability, word segmentation might not be robust enough for clinical use. In contrast, temporal accuracy of auditory syllable responses correlates strongly with coma severity.

Networks are a useful mathematical tool for capturing the complexity of the world. In a previous behavioral study, we showed that human adults were sensitive to the high-level network structure underlying auditory sequences, even when presented with incomplete information. Their performance was best explained by a mathematical model compatible with associative learning principles, based on the integration of the transition probabilities between adjacent and nonadjacent elements with a memory decay. In the present study, we explored the neural correlates of this hypothesis via magnetoencephalography (MEG). Participants (N = 23, 16 females) passively listened to sequences of tones organized in a sparse community network structure comprising two communities. An early difference (∼150 ms) was observed in the brain responses to tone transitions with similar transition probability but occurring either within or between communities. This result implies a rapid and automatic encoding of the sequence structure. Using time-resolved decoding, we estimated the duration and overlap of the representation of each tone. The decoding performance exhibited exponential decay, resulting in a significant overlap between the representations of successive tones. Based on this extended decay profile, we estimated a long-horizon associative learning novelty index for each transition and found a correlation of this measure with the MEG signal. Overall, our study sheds light on the neural mechanisms underlying human sensitivity to network structures and highlights the potential role of Hebbian-like mechanisms in supporting learning at various temporal scales.

The superior temporal sulcus (STS), one of the first sulci visible during brain development, is a key region for human communication, notably hosting linguistic functions in the left hemisphere. Fetuses and premature newborns already process external sound, but the auditory environment is vastly different in-utero and ex-utero. Does this have an impact on the development of the auditory and linguistic networks? To answer this question, we studied the functional connectivity of regions bordering the STS, delimited in each individual including full-term and preterm male and female neonates born at different gestational ages but all scanned at term. We found that in addition to the expected contralateral connectivity, various STS parts were more strongly connected to specific distant regions, revealing the typical auditory/linguistic division across the two banks of the STS reported in adults. Furthermore, the right posterior STS was more connected to the contralateral hemisphere than the left. Finally, sex and premature birth had effects on both STS volume and connectivity. Female neonates displayed a lesser left-right asymmetry in STS depth, and heightened connectivity from the left posterior STS compared to males. Most importantly, despite equivalent scan age, full-term newborns had deeper sulci compared with preterms, and local connectivity in the right temporal region increased linearly with gestation length. These results emphasize the impact of both sex and early auditory environment on the setting up of the cerebral networks that might contribute to explain the milder impact of premature birth on language in females.### Competing Interest StatementThe authors have declared no competing interest.

Abstract Young children’s linguistic and communicative abilities are foundational for their academic achievement and overall well-being. We present the positive outcomes of a brief tablet-based intervention aimed at teaching toddlers and preschoolers new word-object and letter-sound associations. We conducted two experiments, one involving toddlers ( ~ 24 months old, n = 101) and the other with preschoolers ( ~ 42 months old, n = 152). Using a pre-post equivalent group design, we measured the children’s improvements in language and communication skills resulting from the intervention. Our results showed that the intervention benefited toddlers’ verbal communication and preschoolers’ speech comprehension. Additionally, it encouraged vocalizations in preschoolers and enhanced long-term memory for the associations taught in the study for all participants. In summary, our study demonstrates that the use of a ludic tablet-based intervention for teaching new vocabulary and pre-reading skills can improve young children’s linguistic and communicative abilities, which are essential for future development.

Perceptual awareness in infants during the first year of life is understudied, despite the philosophical, scientific, and clinical importance of understanding how and when consciousness emerges during human brain development. Although parents are undoubtedly convinced that their infant is conscious, the lack of adequate experimental paradigms to address this question in preverbal infants has been a hindrance to research on this topic. However, recent behavioral and brain imaging studies have shown that infants are engaged in complex learning from an early age and that their brains are more structured than traditionally thought. I will present a rapid overview of these results, which might provide indirect evidence of early perceptual awareness and then describe how a more systematic approach to this question could stand within the framework of global workspace theory, which identifies specific signatures of conscious perception in adults. Relying on these brain signatures as a benchmark for conscious perception, we can deduce that it exists in the second half of the first year, whereas the evidence before the age of 5 months is less solid, mainly because of the paucity of studies. The question of conscious perception before term remains open, with the possibility of short periods of conscious perception, which would facilitate early learning. Advances in brain imaging and growing interest in this subject should enable us to gain a better understanding of this important issue in the years to come.

Atypical prosody in speech production is a core feature of Autism Spectrum Disorder (ASD) that can impact everyday life communication. Because the ability to modulate prosody develops around the age of speech acquisition, it might be affected by ASD symptoms and developmental delays that emerge at the same period. Here, we investigated the existence of a prosodic signature of developmental level and ASD symptom severity in a sample of 74 autistic preschoolers. We first developed an original diarization pipeline to extract preschoolers' vocalizations from recordings of naturalistic social interactions. Using this novel approach, we then found a robust voice quality signature of ASD developmental difficulties in preschoolers. Furthermore, some prosodic measures were associated with one year later outcome in participants who had not acquired speech yet. Altogether, our results highlight the potential benefits of automatized diarization algorithms and prosodic metrics for digital phenotyping in psychiatry, helping clinicians establish early diagnosis and prognosis.

Successive auditory inputs are rarely independent, their relationships ranging from local transitions between elements to hierarchical and nested representations. In many situations, humans retrieve these dependencies even from limited datasets. However, this learning at multiple scale levels is poorly understood. Here, we used the formalism proposed by network science to study the representation of local and higher-order structures and their interaction in auditory sequences. We show that human adults exhibited biases in their perception of local transitions between elements, which made them sensitive to high-order network structures such as communities. This behavior is consistent with the creation of a parsimonious simplified model from the evidence they receive, achieved by pruning and completing relationships between network elements. This observation suggests that the brain does not rely on exact memories but on a parsimonious representation of the world. Moreover, this bias can be analytically modeled by a memory/efficiency trade-off. This model correctly accounts for previous findings, including local transition probabilities as well as high-order network structures, unifying sequence learning across scales. We finally propose putative brain implementations of such bias.

In carefully designed experimental paradigms, cognitive scientists interpret the mean event-related potentials (ERP) in terms of cognitive operations. However, the huge signal variability from one trial to the next, questions the representability of such mean events. We explored here whether this variability is an unwanted noise, or an informative part of the neural response. We took advantage of the rapid changes in the visual system during human infancy and analyzed the variability of visual responses to central and lateralized faces in 2-to 6-month-old infants compared to adults using high-density electroencephalography (EEG). We observed that neural trajectories of individual trials always remain very far from ERP components, only moderately bending their direction with a substantial temporal jitter across trials. However, single trial trajectories displayed characteristic patterns of acceleration and deceleration when approaching ERP components, as if they were under the active influence of steering forces causing transient attraction and stabilization. These dynamic events could only partly be accounted for by induced microstate transitions or phase reset phenomena. Importantly, these structured modulations of response variability, both between and within trials, had a rich sequential organization, which in infants, was modulated by the task difficulty and age. Our approaches to characterize Event Related Variability (ERV) expand on classic ERP analyses and provide the first evidence for the functional role of ongoing neural variability in human infants.

The core knowledge hypothesis postulates that infants automatically analyze their environment along abstract dimensions, including numbers. According to this view, approximate numbers should be encoded quickly, pre-attentively, and in a supra-modal manner by the infant brain. Here, we directly tested this idea by submitting the neural responses of sleeping 3-month-old infants, measured with high-density electroencephalography (EEG), to decoders designed to disentangle numerical and non-numerical information. The results show the emergence, in approximately 400 ms, of a decodable number representation, independent of physical parameters, that separates auditory sequences of 4 vs. 12 tones and generalizes to visual arrays of 4 vs. 12 objects. Thus, the infant brain contains a number code that transcends sensory modality, sequential or simultaneous presentation, and arousal state.

Electrophysiology recordings are frequently affected by artifacts (e.g., subject motion or eye movements), which reduces the number of available trials and affects the statistical power. When artifacts are unavoidable and data are scarce, signal reconstruction algorithms that allow for the retention of sufficient trials become crucial. Here, we present one such algorithm that makes use of large spatiotemporal correlations in neural signals and solves the low-rank matrix completion problem, to fix artifactual entries. The method uses a gradient descent algorithm in lower dimensions to learn the missing entries and provide faithful reconstruction of signals. We carried out numerical simulations to benchmark the method and estimate optimal hyperparameters for actual EEG data. The fidelity of reconstruction was assessed by detecting event-related potentials (ERP) from a highly artifacted EEG time series from human infants. The proposed method significantly improved the standardized error of the mean in ERP group analysis and a between-trial variability analysis compared to a state-of-the-art interpolation technique. This improvement increased the statistical power and revealed significant effects that would have been deemed insignificant without reconstruction. The method can be applied to any time-continuous neural signal where artifacts are sparse and spread out across epochs and channels, increasing data retention and statistical power.

Is hemisphere lateralization for speech processing linked to handedness? To answer this question, we compared hemisphere lateralization for speech processing and handedness in 18-month-old infants, the age at which infants start to produce words and reach a stable pattern of handedness. To assess hemisphere lateralization for speech perception, we coupled event-related potential (ERP) recordings with a syllable-discrimination paradigm and measured response differences to a change in phoneme or voice (different speaker) in the left and right clusters of electrodes. To assess handedness, we gave a 15-item grasping test to infants. We also evaluated infants’ range of vocabulary to assess whether it was associated with direction and degree of handedness and language brain asymmetries. Brain signals in response to a change in phoneme and voice were left- and right-lateralized, respectively, indicating functional brain lateralization for speech processing in infants. Handedness and brain asymmetry for speech processing were not related. In addition, there were no interactions between the range of vocabulary and asymmetry in brain responses, even for a phoneme change. Together, a high degree of right-handedness and greater vocabulary range were associated with an increase in ERP amplitudes in voice condition, irrespective of hemisphere side, suggesting that they influence discrimination during voice processing.

During the last trimester of gestation, fetuses and preterm neonates begin to respond to sensory stimulation and to discover the structure of their environment. Yet, neuronal migration is still ongoing. This late migration notably concerns the supra-granular layers neurons, which are believed to play a critical role in encoding predictions and detecting regularities. In order to gain a deeper understanding of how the brain processes and perceives regularities during this stage of development, we conducted a study in which we recorded event-related potentials (ERP) in 31-wGA preterm and full-term neonates exposed to alternating auditory sequences (e.g. “ba ga ba ga ba”), when the regularity of these sequences was violated by a repetition (e.g., ``ba ga ba ga ga''). We compared the ERPs in this case to those obtained when violating a simple repetition pattern (“ga ga ga ga ga” vs. “ga ga ga ga ba”). Our results indicated that both preterm and full-term neonates were able to detect violations of regularity in both types of sequences, indicating that as early as 31 weeks gestational age, human neonates are sensitive to the conditional statistics between successive auditory elements. Full-term neonates showed an early and similar mismatch response (MMR) in the repetition and alternating sequences. In contrast, 31-wGA neonates exhibited a two-component MMR. The first component which was only observed for simple sequences with repetition, corresponded to sensory adaptation. It was followed much later by a deviance-detection component that was observed for both alternation and repetition sequences. This pattern confirms that MMRs detected at the scalp may correspond to a dual cortical process and shows that deviance detection computed by higher-level regions accelerates dramatically with brain maturation during the last weeks of gestation to become indistinguishable from bottom-up sensory adaptation at term.