Anatomical correlates of category-selective visual regions have distinctive signatures of connectivity in neonates

Helpless infants are learning a foundation model

Humans have a protracted postnatal helplessness period, typically attributed to human-specific maternal constraints causing an early birth when the brain is highly immature. By aligning neurodevelopmental events across species, however, it has been found that humans are not born with especially immature brains compared with animal species with a shorter helpless period. Consistent with this, the rapidly growing field of infant neuroimaging has found that brain connectivity and functional activation at birth share many similarities with the mature brain. Inspired by machine learning, where deep neural networks also benefit from a 'helpless period' of pre-training, we propose that human infants are learning a foundation model: a set of fundamental representations that underpin later cognition with high performance and rapid generalisation.

Predicting high-level visual areas in the absence of task fMRI

The ventral visual stream is organized into units, or functional regions of interest (fROIs), specialized for processing high-level visual categories. Task-based fMRI scans ("localizers") are typically used to identify each individual's nuanced set of fROIs. The unique landscape of an individual's functional activation may rely in large part on their specialized connectivity patterns; recent studies corroborate this by showing that connectivity can predict individual differences in neural responses. We focus on the ventral visual stream and ask: how well can an individual's resting state functional connectivity localize their fROIs for face, body, scene, and object perception? And are the neural processors for any particular visual category better predicted by connectivity than others, suggesting a tighter mechanistic relationship between connectivity and function? We found, among 18 fROIs predicted from connectivity for each subject, all but one were selective for their preferred visual category. Defining an individual's fROIs based on their connectivity patterns yielded regions that were more selective than regions identified from previous studies or atlases in nearly all cases. Overall, we found that in the absence of a domain-specific localizer task, a 10-min resting state scan can be reliably used for defining these fROIs.

Multivariate and regional age-related change in basal ganglia iron in neonates

In the perinatal period, reward and cognitive systems begin trajectories, influencing later psychiatric risk. The basal ganglia is important for reward and cognitive processing but early development has not been fully characterized. To assess age-related development, we used a measure of basal ganglia physiology, specifically brain tissue iron, obtained from nT2* signal in resting-state functional magnetic resonance imaging (rsfMRI), associated with dopaminergic processing. We used data from the Developing Human Connectome Project (n = 464) to assess how moving from the prenatal to the postnatal environment affects rsfMRI nT2*, modeling gestational and postnatal age separately for basal ganglia subregions in linear models. We did not find associations with tissue iron and gestational age [range: 24.29-42.29] but found positive associations with postnatal age [range:0-17.14] in the pallidum and putamen, but not the caudate. We tested if there was an interaction between preterm birth and postnatal age, finding early preterm infants (GA < 35 wk) had higher iron levels and changed less over time. To assess multivariate change, we used support vector regression to predict age from voxel-wise-nT2* maps. We could predict postnatal but not gestational age when maps were residualized for the other age term. This provides evidence subregions differentially change with postnatal experience and preterm birth may disrupt trajectories.

Consciousness in the cradle: on the emergence of infant experience

Although each of us was once a baby, infant consciousness remains mysterious and there is no received view about when, and in what form, consciousness first emerges. Some theorists defend a 'late-onset' view, suggesting that consciousness requires cognitive capacities which are unlikely to be in place before the child's first birthday at the very earliest. Other theorists defend an 'early-onset' account, suggesting that consciousness is likely to be in place at birth (or shortly after) and may even arise during the third trimester. Progress in this field has been difficult, not just because of the challenges associated with procuring the relevant behavioral and neural data, but also because of uncertainty about how best to study consciousness in the absence of the capacity for verbal report or intentional behavior. This review examines both the empirical and methodological progress in this field, arguing that recent research points in favor of early-onset accounts of the emergence of consciousness.

The development of human cortical scene processing

Decades of research have uncovered the neural basis of place (or "scene") processing in adulthood, revealing a set of three regions that respond selectively to visual scene information, each hypothesized to support distinct functions within scene processing (e.g., recognizing a particular kind of place versus navigating through it). Despite this considerable progress, surprisingly little is known about how these cortical regions develop. Here we review the limited evidence to date, highlighting the first few studies exploring the origins of cortical scene processing in infancy, and the several studies addressing when the scene regions reach full maturity, unfortunately with inconsistent findings. This inconsistency likely stems from common pitfalls in pediatric functional magnetic resonance imaging, and accordingly, we discuss how these pitfalls may be avoided. Furthermore, we point out that almost all studies to date have focused only on general scene selectivity and argue that greater insight could be gleaned by instead exploring the more distinct functions of each region, as well as their connectivity. Finally, with this last point in mind, we offer a novel hypothesis that scene regions supporting navigation (including the occipital place area and retrosplenial complex) mature later than those supporting scene categorization (including the parahippocampal place area).

Gestational and postnatal age associations for striatal tissue iron deposition in early infancy

Striatal development is crucial for later motor, cognitive, and reward behavior, but age-related change in striatal physiology during the neonatal period remains understudied. An MRI-based measure of tissue iron deposition, T2*, is a non-invasive way to probe striatal physiology neonatally, linked to dopaminergic processing and cognition in children and adults. Striatal subregions have distinct functions that may come online at different time periods in early life. To identify if there are critical periods before or after birth, we measured if striatal iron accrued with gestational age at birth [range= 34.57-41.85 weeks] or postnatal age at scan [range= 5-64 days], using MRI to probe the T2* signal in N = 83 neonates in three striatal subregions. We found iron increased with postnatal age in the pallidum and putamen but not the caudate. No significant relationship between iron and gestational age was observed. Using a subset of infants scanned at preschool age (N = 26), we show distributions of iron shift between time points. In infants, the pallidum had the least iron of the three regions but had the most by preschool age. Together, this provides evidence of distinct change for striatal subregions, a possible differentiation between motor and cognitive systems, identifying a mechanism that may impact future trajectories.

Gestational and postnatal age associations for striatal tissue iron deposition in early infancy

Striatal development is crucial for later motor, cognitive, and reward behavior, but age-related change in striatal physiology during the neonatal period remains understudied. An MRI-based measure of tissue iron deposition, T2*, is a non-invasive way to probe striatal physiology neonatally, linked to dopaminergic processing and cognition in children and adults. Striatal subregions have distinct functions that may come online at different time periods in early life. To identify if there are critical periods before or after birth, we measured if striatal iron accrued with gestational age at birth [range=34.57-41.85 weeks] or postnatal age at scan [range=5-64 days], using MRI to probe the T2* signal in N=83 neonates in three striatal subregions. We found iron increased with postnatal age in the pallidum and putamen but not the caudate. No significant relationship between iron and gestational age was observed. Using a subset of infants scanned at preschool age (N=26), we show distributions of iron shift between timepoints. In infants, the pallidum had the least iron of the three regions but had the most by preschool age. Together, this provides evidence of distinct change for striatal subregions, a possible differentiation between motor and cognitive systems, identifying a mechanism that may impact future trajectories.

Highlights

Neonatal striatal tissue iron can be measured using the T2* signal from rsfMRInT2* changed with postnatal age in the pallidum and putamen but not in the caudatenT2* did not change with gestational age in any of the three regionsPatterns of iron deposition (nT2*) among regions shift from infancy to preschool.

The development of intrinsic timescales: A comparison between the neonate and adult brain

In human adults and other mammals, different brain regions have distinct intrinsic timescales over which they integrate information, from shorter in unimodal sensory-motor regions to longer in transmodal higher-order regions. These have been related to cognitive performance and clinical symptoms, but it remains unclear how they develop. We asked if there are regional differences in timescales at birth that could shape learning by acting as an inductive bias, or if they develop later as the temporal statistics of the environment are learned. We used resting-state fMRI to characterise timescales in human neonates and adults. They were highly consistent across two independent neonatal groups, but in both sensory-motor and higher order areas, timescales were longer in infants compared to adults, as might be expected from their less developed myelination, and recent evidence of longer neural segments in infants watching naturalistic stimuli. In adults, we replicated the finding that transmodal areas have longer timescales than sensory-motor areas, but in infants the opposite pattern was found, driven by long infant timescales in the somotomotor network. Across regions within single brain networks, both positive (limbic) and negative (visual) correlations were found between neonates and adults. In conclusion, neonatal timescales were found to be highly structured, but distinct from adults, suggesting they act as an inductive bias that favours learning on longer timescales, particularly in unimodal regions and then develop with experience or maturation. This "take it slow" initial approach might help human infants to create more regularised, holistic representations of the input less bound to fleeting details, which would favour the development of abstract and contextual representations.