Distinct Cerebral Pathways for Object Identity and Number in Human Infants

All humans, regardless of their culture and education, possess an intuitive understanding of number. Behavioural evidence suggests that numerical competence may be present early on in infancy. Here, we present brain-imaging evidence for distinct cerebral coding of number and object identity in 3-mo-old infants. We compared the visual event-related potentials evoked by unforeseen changes either in the identity of objects forming a set, or in the cardinal of this set. In adults and 4-y-old children, number sense relies on a dorsal system of bilateral intraparietal areas, different from the ventral occipitotemporal system sensitive to object identity. Scalp voltage topographies and cortical source modelling revealed a similar distinction in 3-mo-olds, with changes in object identity activating ventral temporal areas, whereas changes in number involved an additional right parietoprefrontal network. These results underscore the developmental continuity of number sense by pointing to early functional biases in brain organization that may channel subsequent learning to restricted brain areas

Structural encoding of body and face in human infants and adults

Most studies on visual perception of human beings have focused on perception of faces. However, bodies are another important visual element, which help us to identify a member of our species in the visual scene. In order to study whether similar configural information processing is used in body and face perception, we recorded high-density even-related potentials (ERPs) to normal and distorted faces and bodies in adults and 3-month-old infants. In adults, the N1 responses evoked by bodies and faces were similar in amplitude but differed slightly in latency. The voltage topography of N1 also differed in concordance with fMRI data showing that two distinct areas are involved in face and body perception. Distortion affected ERPs to faces and bodies similarly from N1 on, although the effect was significant earlier for bodies than for faces. These results suggest that fast processing of configural information is not specific to faces but it also occurs for bodies. In 3-month-old infants, distortion decreased the amplitude of P400 around 450 msec, showing no interaction with image category. This result demonstrates that infants are not only able to recognize the normal configuration of faces, but also that of bodies. This could either be related to an innate knowledge of this particular type of biological object, or to fast learning through intense exposure during the first months of life

Subject-level Joint Parcellation-Detection-Estimation in fMRI

Brain parcellation is one of the most important issues in functional MRI (fMRI) data analysis. This parcellation allows establishing homogeneous territories that share the same functional properties. This paper presents a model-based approach to perform a subject-level parcellation into hemodynamic territories with similar hemodynamic features which are known to vary between brain regions. We specifically investigate the use of the Joint Parcellation-Detection-Estimation (JPDE) model initially proposed in [1] to separate brain regions that match different hemodynamic response function (HRF) profiles. A hierarchical Bayesian model is built and a variational expectation maximiza-tion (VEM) algorithm is deployed to perform inference. A more complete version of the JPDE model is detailed. Validation on synthetic data shows the robustness of this model to varying signal-to-noise ratio (SNR) as well as to different initializations. Our results also demonstrate that good parcellation performance is achieved even though the parcels do not involve the same amount of activation. On real fMRI data acquired in children during a language paradigm, we retrieved a parcellation along the superior temporal sulcus of the left hemisphere that matches the gradient of activation dynamics already reported in the literature

Hemodynamic-Informed Parcellation of fMRI Data in a Joint Detection Estimation Framework

Submitted to IEEE Transactions on Medical ImagingIdentifying brain hemodynamics in event-related functional MRI (fMRI) data is a crucial issue to disentangle the vascular response from the neuronal activity in the BOLD signal. This question is usually addressed by estimating the so-called Hemodynamic Response Function (HRF). Voxelwise or region-/parcelwise inference schemes have been proposed to achieve this goal but so far all known contributions commit to pre-specified spatial supports for the hemodynamic territories by defining these supports either as individual voxels or a priori fixed brain parcels. In this paper, we introduce a Joint Parcellation-Detection-Estimation (JPDE) procedure that incorporates an adaptive parcel identification step based upon local hemodynamic properties. Efficient inference of both evoked activity, HRF shapes and supports is then achieved using variational approximations. Validation on synthetic and real fMRI data demonstrates the JPDE performance over standard detection estimation schemes and suggests it as a new brain exploration tool

Atlas-Free Surface Reconstruction of the Cortical Grey-White Interface in Infants

BACKGROUND: The segmentation of the cortical interface between grey and white matter in magnetic resonance images (MRI) is highly challenging during the first post-natal year. First, the heterogeneous brain maturation creates important intensity fluctuations across regions. Second, the cortical ribbon is highly folded creating complex shapes. Finally, the low tissue contrast and partial volume effects hamper cortex edge detection in parts of the brain. METHODS AND FINDINGS: We present an atlas-free method for segmenting the grey-white matter interface of infant brains in T2-weighted (T2w) images. We used a broad characterization of tissue using features based not only on local contrast but also on geometric properties. Furthermore, inaccuracies in localization were reduced by the convergence of two evolving surfaces located on each side of the inner cortical surface. Our method has been applied to eleven brains of one- to four-month-old infants. Both quantitative validations against manual segmentations and sulcal landmarks demonstrated good performance for infants younger than two months old. Inaccuracies in surface reconstruction increased with age in specific brain regions where the tissue contrast decreased with maturation, such as in the central region. CONCLUSIONS: We presented a new segmentation method which achieved good to very good performance at the grey-white matter interface depending on the infant age. This method should reduce manual intervention and could be applied to pathological brains since it does not require any brain atlas

Language ability in preterm children is associated with arcuate fasciculi microstructure at term

In the mature human brain, the arcuate fasciculus mediates verbal working memory, word learning, and sublexical speech repetition. However, its contribution to early language acquisition remains unclear. In this work, we aimed to evaluate the role of the direct segments of the arcuate fasciculi in the early acquisition of linguistic function. We imaged a cohort of 43 preterm born infants (median age at birth of 30 gestational weeks; median age at scan of 42 postmenstrual weeks) using high b value high-angular resolution diffusion-weighted neuroimaging and assessed their linguistic performance at 2 years of age. Using constrained spherical deconvolution tractography, we virtually dissected the arcuate fasciculi and measured fractional anisotropy (FA) as a metric of white matter development. We found that term equivalent FA of the left and right arcuate fasciculi was significantly associated with individual differences in linguistic and cognitive abilities in early childhood, independent of the degree of prematurity. These findings suggest that differences in arcuate fasciculi microstructure at the time of normal birth have a significant impact on language development and modulate the first stages of language learning

Interoperable atlases of the human brain

International audienceThe last two decades have seen an unprecedented development of human brain mapping approaches at various spatial and temporal scales. Together, these have provided a large fundus of information on many different as-pects of the human brain including micro-and macrostructural segregation, regional specialization of function, connectivity, and temporal dynamics. Atlases are central in order to integrate such diverse information in a topo-graphically meaningful way. It is noteworthy, that the brain mapping field has been developed along several major lines such as structure vs. function, postmortem vs. in vivo, individual features of the brain vs. population-based aspects, or slow vs. fast dynamics. In order to understand human brain organization, however, it seems inevitable that these different lines are integrated and combined into a multimodal human brain model. To this aim, we held a workshop to determine the constraints of a multi-modal human brain model that are needed to enable (i) an integration of different spatial and temporal scales and data modalities into a common reference system, and (ii) efficient data exchange and analysis. As detailed in this report, to arrive at fully interoperable atlases of the human brain will still require much work at the frontiers of data acquisition, analysis, and represen-tation. Among them, the latter may provide the most challenging task, in particular when it comes to representing features of vastly different scales of space, time and abstraction. The potential benefits of such endeavor, however, clearly outweigh the problems, as only such kind of multi-modal human brain atlas may provide a starting point from which the complex relationships between structure, function, and connectivity may be explored

À l'origine du langage dans le cerveau humain

Dehaene-Lambertz Ghislaine. À l'origine du langage dans le cerveau humain. In: L'Information Grammaticale, N. 133, 2012. pp. 9-14

Perceptual awareness in human infants: What is the evidence?

International audiencePerceptual 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