Polygenic risk for depression and anterior and posterior hippocampal volume in children and adolescents.

BACKGROUND: Depression has frequently been associated with smaller hippocampal volume. The hippocampus varies in function along its anterior-posterior axis, with the anterior hippocampus more strongly associated with stress and emotion processing. The goals of this study were to examine the associations among parental history of anxiety/depression, polygenic risk scores for depression (PGS-DEP), and anterior and posterior hippocampal volumes in children and adolescents. To examine specificity to PGS-DEP, we examined associations of educational attainment polygenic scores (PGS-EA) with anterior and posterior hippocampal volume. METHODS: Participants were 350 3- to 21-year-olds (46 % female). PGS-DEP and PGS-EA were computed based on recent, large-scale genome-wide association studies. High-resolution, T1-weighted magnetic resonance imaging (MRI) data were acquired, and a semi-automated approach was used to segment the hippocampus into anterior and posterior subregions. RESULTS: Children and adolescents with higher polygenic risk for depression were more likely to have a parent with a history of anxiety/depression. Higher polygenic risk for depression was significantly associated with smaller anterior but not posterior hippocampal volume. PGS-EA was not associated with anterior or posterior hippocampal volumes. LIMITATIONS: Participants in these analyses were all of European ancestry. CONCLUSIONS: Polygenic risk for depression may lead to smaller anterior but not posterior hippocampal volume in children and adolescents, and there may be specificity of these effects to PGS-DEP rather than PGS-EA. These findings may inform the earlier identification of those in need of support and the design of more effective, personalized treatment strategies. DECLARATIONS OF INTEREST: none. DECLARATIONS OF INTEREST: None.

Fluctuations in Sustained Attention Explain Moment-to-Moment Shifts in Children's Memory Formation.

Why do children's memories often differ from adults' after the same experience? Whereas prior work has focused on children's immature memory mechanisms to answer this question, here we focus on the costs of attentional lapses for learning. We track sustained attention and memory formation across time in 7- to 10-year-old children and adults (n = 120) to show that sustained attention causally shapes the fate of children's individual memories. Moreover, children's attention lapsed twice as frequently as adults', and attention fluctuated with memory formation more closely in children than adults. In addition, although attentional lapses impaired memory for expected events in both children and adults, they impaired memory for unexpected events in children only. Our work reveals that sustained attention is an important cognitive factor that controls access to children's long-term memory stores. Our work also raises the possibility that developmental differences in cognitive performance stem from developmental shifts in the ability to sustain attention.

Memories of structured input become increasingly distorted across development.

Trajectories of cognitive and neural development suggest that, despite early emergence, the ability to extract environmental patterns changes across childhood. Here, 5- to 9-year-olds and adults (N = 211, 110 females, in a large Canadian city) completed a memory test assessing what they remembered after watching a stream of shape triplets: the particular sequence in which the shapes occurred and/or their group-level structure. After accounting for developmental improvements in overall memory, all ages remembered specific transitions, while memory for group membership was only observed in older children and adults (age by test-type interaction η2 = .05). Thus, while young children form memories for specifics of structured experience, memory for derived associations is refined later-underscoring that adults and young children form different memories despite identical experience.

Neither Enhanced Nor Lost: The Unique Role of Attention in Children's Neural Representations.

A defining feature of children's cognition is the especially slow development of their attention. Despite a rich behavioral literature characterizing the development of attention, little is known about how developing attentional abilities modulate neural representations in children. This information is critical to understanding how attentional development shapes the way children process information. One possibility is that attention might be less likely to shape neural representations in children as compared with adults. In particular, representations of attended items may be less likely to be enhanced relative to unattended items. To investigate this possibility, we measured brain activity using fMRI while children (seven to nine years; male and female) and adults (21-31 years; male and female) performed a one-back task in which they were directed to attend to either motion direction or an object in a display where both were present. We used multivoxel pattern analysis to compare decoding accuracy of attended and unattended information. Consistent with attentional enhancement, we found higher decoding accuracy for task-relevant information (i.e., objects in the object-attended condition) than for task-irrelevant information (i.e., motion in the object-attended condition) in adults' visual cortices. However, in children's visual cortices, both task-relevant and task-irrelevant information were decoded equally well. What is more, whole-brain analysis showed that the children represented task-irrelevant information more than adults in multiple regions across the brain, including the prefrontal cortex. These findings show that (1) attention does not modulate neural representations in the child visual cortex, and (2) developing brains can, and do, represent more information than mature brains.SIGNIFICANCE STATEMENT Children have been shown to struggle with maintaining their attention to specific information, and at the same time, can show better learning of "distractors." While these are critical properties of childhood, their underlying neural mechanisms are unknown. To fill in this critical knowledge gap, we explored how attention shapes what is represented in children's and adults' brains using fMRI while both were asked to focus on just one of two things (objects and motion). We found that unlike adults, who prioritize the information they were asked to focus on, children represent both what they were asked to prioritize and what they were asked to ignore. This shows that attention has a fundamentally different impact on children's neural representations.

What sticks after statistical learning: The persistence of implicit versus explicit memory traces.

Statistical learning is a powerful mechanism that extracts even subtle regularities from our information-dense worlds. Recent theories argue that statistical learning can occur through multiple mechanisms-both the conventionally assumed automatic process that precipitates unconscious learning, and an attention-dependent process that brings regularities into conscious awareness. While this view has gained popularity, there are few empirical dissociations of the hypothesized implicit and explicit forms of statistical learning. Here we provide strong evidence for this dissociation in two ways. First, we show in healthy adults (N = 60) that implicit and explicit traces have divergent consolidation trajectories, with implicit knowledge of structure strengthened over a 24-h period, while precise explicit representations tend to decay. Second, we demonstrate that repeated testing strengthens the retention of explicit representations but that implicit statistical learning is uninfluenced by testing. Together these dissociations provide much needed support for the reconceptualization of statistical learning as a multi-component construct.

Pay attention and you might miss it: Greater learning during attentional lapses.

Attentional lapses have been found to impair everything from basic perception to learning and memory. Yet, despite the well-documented costs of lapses on cognition, recent work suggests that lapses might unexpectedly confer some benefits. One potential benefit is that lapses broaden our learning to integrate seemingly irrelevant content that could later prove useful-a benefit that prior research focusing only on goal-relevant memory would miss. Here, we measure how fluctuations in sustained attention influence the learning of seemingly goal-irrelevant content that competes for attention with target content. Participants completed a correlated flanker task in which they categorized central targets (letters or numbers) while ignoring peripheral flanking symbols that shared hidden probabilistic relationships with the targets. We found that across participants, higher rates of attentional lapses correlated with greater learning of the target-flanker relationships. Moreover, within participants, learning was more evident during attentional lapses. These findings address long-standing theoretical debates and reveal a benefit of attentional lapses: they expand the scope of learning and decisions beyond the strictly relevant.

Attention Shifts to More Complex Structures With Experience.

Our environments are saturated with learnable information. What determines which of this information is prioritized for limited attentional resources? Although previous studies suggest that learners prefer medium-complexity information, here we argue that what counts as medium should change as someone learns an input's structure. Specifically, we examined the hypothesis that attention is directed toward more complicated structures as learners gain more experience with the environment. College students watched four simultaneous streams of information that varied in complexity. RTs to intermittent search trials (Experiment 1, N = 75) and eye tracking (Experiment 2, N = 45) indexed where participants attended during the experiment. Using two participant- and trial-specific measures of complexity, we demonstrated that participants attended to increasingly complex streams over time. Individual differences in structure learning also predicted attention allocation, with better learners attending to complex structures earlier in learning, suggesting that the ability to prioritize different information over time is related to learning success.

The Sweet Spot: When Children's Developing Abilities, Brains, and Knowledge Make Them Better Learners Than Adults.

Cognitive development is marked by age-related improvements across a number of domains, as young children perform worse than their older counterparts on most tasks. However, there are cases in which young children, and even infants, outperform older children and adults. So when, and why, does being young sometimes confer an advantage? This article provides a comprehensive examination of the peculiar cases in which younger children perform better. First, we outline the specific instances in which younger is better across domains, including mastering language, using probabilistic information, detecting causal relations, remembering certain information, and even solving problems. We then examine how children's reduced cognitive abilities, ongoing brain development, more limited prior knowledge, and heightened tendency to explore benefits their learning, reasoning, perception, and memory from a mechanistic perspective. We hold that considering all of these factors together is essential for understanding the ways in which children's learning is unique and that science has much to learn from a careful consideration of childhood.

General precedes specific in memory representations for structured experience.

Decades of work has shown that learners rapidly extract structure from their environment, later leveraging their knowledge of what is more versus less consistent with prior experience to guide behavior. However, open questions remain about exactly what is remembered after exposure to structure. Memory for specific associations-transitions that unfold over time-is considered a prime candidate for guiding behavior. However, other factors could influence behavior, such as memory for general features like reliable groupings or within-group positions. We also do not yet know whether memory depends upon the amount of experience with the input structure, leaving us with an incomplete understanding of how statistical learning supports behavior. In 4 experiments, we tracked the emergence of memory for item-item transitions, order-independent groups, and positions by having 400 adults watch a stream of shape triplets followed by a recognition memory test. We manipulated how closely test sequences corresponded to the input along each dimension of interest, allowing us to isolate the contribution of each factor. Both item-item transitions and order-independent group information influenced behavior, highlighting statistical learning as a mechanism through which we form both specific and generalized representations. Moreover, these factors drove behavior after different amounts of experience: With limited exposure, only group information impacted old-new judgments specific transitions gained importance later. Our findings suggest statistical learning proceeds by first forming a general representation of structure, with memory being later refined to include specifics after more experience. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Events structure information accessibility less in children than adults.

To manage the onslaught of continuously unfolding information in our complex environments, we adults are known to carve up our continuous experience into meaningful events, a process referred to as event segmentation. This segmentation directly shapes how our everyday experiences are construed: content experienced within an event is held mentally in an accessible state, which is then dropped after an event boundary. The greater accessibility of event-specific information has been shown to influence-at its most basic level-how information is processed and remembered. However, it is as yet unknown if accessibility is similarly influenced by event boundaries in children, who are still developing the working memory capacity and semantic knowledge thought to support event segmentation. Here, we tested seven- to nine-year-old children's and adults' recognition of objects experienced either within or across event boundaries of two cartoons. We found that children and adults were both more accurate and faster to correctly recognize objects that last occurred within events versus across event boundaries. We, however, additionally observed an interaction such that children's access to recent experience was less influenced by event boundaries than adults'. Thus, while the spontaneous segmentation of complex events emerges by middle childhood, event structure shapes the active contents of children's minds less reliably than adults'.

Children automatically abstract categorical regularities during statistical learning.

Statistical learning allows us to discover myriad structures in our environment, which is saturated with information at many different levels-from items to categories. How do children learn different levels of information-about regularities that pertain to items and the categories they come from-and how does this differ from adults? Studies on category learning and memory have suggested that children may be more focused on items than adults. If this is also the case for statistical learning, children may not extract and learn the multi-level regularities that adults can. We report three experiments showing that children and adults extract both item- and category-level regularities in statistical learning. In Experiments 1 and 2, we show that both children and adults can learn structure at the item and category levels when they are measured independently. In Experiment 3, we show that both children and adults learn about categories even when exposure does not require this: both are able to generalize their learning from the item to the category level. Results indicate that statistical learning operates across multi-level structure in children and adults alike, enabling generalization of learning from specific items to exemplars from categories of those items that observers have never seen. Even though children may be more focused on items during other forms of learning, they learn about categories from item-level input during statistical learning.

Children's family income is associated with cognitive function and volume of anterior not posterior hippocampus.

Children from lower income backgrounds tend to have poorer memory and language abilities than their wealthier peers. It has been proposed that these cognitive gaps reflect the effects of income-related stress on hippocampal structure, but the empirical evidence for this relationship has not been clear. Here, we examine how family income gaps in cognition relate to the anterior hippocampus, given its high sensitivity to stress, versus the posterior hippocampus. We find that anterior (but not posterior) hippocampal volumes positively correlate with family income up to an annual income of ~$75,000. Income-related differences in the anterior (but not posterior) hippocampus also predicted the strength of the gaps in memory and language. These findings add anatomical specificity to current theories by suggesting a stronger relationship between family income and anterior than posterior hippocampal volumes and offer a potential mechanism through which children from different income homes differ cognitively.

Evidence of stable individual differences in implicit learning.

There is a fundamental psychological and neuropsychological distinction between explicit and implicit memory, and it has been proposed that whereas there are stable trait individual differences in explicit memory ability, there are not such differences across people for implicit learning. There is, however, little evidence about whether or not there are stable trait differences in implicit learning. Here we performed a test-retest reliability study with healthy young adults in which they performed four implicit learning tasks (artificial grammar learning, probabilistic classification, serial response, and implicit category learning) twice, about a week apart. We found medium (by Cohen's guidelines) test-retest reliability for three of the tasks: probabilistic classification, serial response, and implicit category learning, suggesting that differences in implicit learning ability are more stable than originally thought. In addition, implicit learning on all tasks was unrelated to explicit measures: we did not find any correlation between implicit learning measures and independent measures of IQ, working memory, or explicit learning ability. These findings indicate that implicit learning, like explicit learning, varies reliably across individuals.

Associations between cortical thickness and reasoning differ by socioeconomic status in development.

Although lower socioeconomic status (SES) is generally negatively associated with performance on cognitive assessments, some children from lower-SES backgrounds perform as well as their peers from higher-SES backgrounds. Yet little research has examined whether the neural correlates of individual differences in cognition vary by SES. The current study explored whether relationships between cortical structure and fluid reasoning differ by SES in development. Fluid reasoning, a non-verbal component of IQ, is supported by a distributed frontoparietal network, with evidence for a specific role of rostrolateral prefrontal cortex (RLPFC). In a sample of 115 4-7-year old children, bilateral thickness of RLPFC differentially related to reasoning by SES: thicker bilateral RLPFC positively correlated with reasoning ability in children from lower-SES backgrounds, but not in children from higher-SES backgrounds. Similar results were found in an independent sample of 59 12-16-year old adolescents. Furthermore, young children from lower-SES backgrounds with strong reasoning skills were the only group to show a positive relationship between RLPFC thickness and age. In sum, we found that relationships between cortical thickness and cognition differ by SES during development.

Superior learning in synesthetes: Consistent grapheme-color associations facilitate statistical learning.

In synesthesia activation in one sensory domain, such as smell or sound, triggers an involuntary and unusual secondary sensory or cognitive experience. In the present study, we ask whether the added sensory experience of synesthesia can aid statistical learning-the ability to track environmental regularities in order to segment continuous information. To investigate this, we measured statistical learning outcomes, using an aurally presented artificial language, in two groups of synesthetes alongside controls and simulated the multimodal experience of synesthesia in non-synesthetes. One group of synesthetes exclusively had grapheme-color (GC) synesthesia, in which the experience of color is automatically triggered by exposure to written or spoken graphemes. The other group had both grapheme-color and sound-color (SC+) synesthesia, in which the experience of color is also triggered by the waveform properties of a voice, such as pitch, timbre, and/or musical chords. Unlike GC-only synesthetes, the experience of color in the SC+ group is not perfectly consistent with the statistics that signal word boundaries. We showed that GC-only synesthetes outperformed both non-synesthetes and SC+ synesthetes, likely because the visual concurrents for GC-only synesthetes are highly consistent with the artificial language. We further observed that our simulations of GC synesthesia, but not SC+ synesthesia produced superior statistical learning, showing that synesthesia likely boosts learning outcomes by providing a consistent secondary cue. Findings are discussed with regard to how multimodal experience can improve learning, with the present data indicating that this boost is more likely to occur through explicit, as opposed to implicit, learning systems.

Prefrontal and Hippocampal Structure Predict Statistical Learning Ability in Early Childhood.

Statistical learning can be used to gain sensitivity to many important regularities in our environment, including structure that is foundational to language and visual perception. As yet, little is known about how statistical learning takes place in the human brain, especially in children's developing brains and with regard to the broader neurobiology of learning and memory. We therefore explored the relationship between statistical learning and the thickness and volume of structures that are traditionally implicated in declarative and procedural memory, focusing specifically on the left inferior PFC, the hippocampus, and the caudate during early childhood (ages 5-8.5 years). We found that the thickness of the left inferior frontal cortex and volume of the right hippocampus predicted statistical learning ability in young children. Importantly, these regions did not change in thickness or volume with age, but the relationship between learning and the right hippocampus interacted with age such that older children's hippocampal structure more strongly predicted performance. Overall, the data show that children's statistical learning is supported by multiple neural structures that are more broadly implicated in learning and memory, especially declarative memory (hippocampus) and attention/top-down control (the PFC).

Dimensions of childhood adversity have distinct associations with neural systems underlying executive functioning.

Childhood adversity is associated with increased risk for psychopathology. Neurodevelopmental pathways underlying this risk remain poorly understood. A recent conceptual model posits that childhood adversity can be deconstructed into at least two underlying dimensions, deprivation and threat, that are associated with distinct neurocognitive consequences. This model argues that deprivation (i.e., a lack of cognitive stimulation and learning opportunities) is associated with poor executive function (EF), whereas threat is not. We examine this hypothesis in two studies measuring EF at multiple levels: performance on EF tasks, neural recruitment during EF, and problems with EF in daily life. In Study 1, deprivation (low parental education and child neglect) was associated with greater parent-reported problems with EF in adolescents (N = 169; 13-17 years) after adjustment for levels of threat (community violence and abuse), which were unrelated to EF. In Study 2, low parental education was associated with poor working memory (WM) performance and inefficient neural recruitment in the parietal and prefrontal cortex during high WM load among adolescents (N = 51, 13-20 years) after adjusting for abuse, which was unrelated to WM task performance and neural recruitment during WM. These findings constitute strong preliminary evidence for a novel model of the neurodevelopmental consequences of childhood adversity.

Functional brain organization of working memory in adolescents varies in relation to family income and academic achievement.

Working memory (WM) capacity reflects executive functions associated with performance on a wide range of cognitive tasks and education outcomes, including mathematics achievement, and is associated with dorsolateral prefrontal and parietal cortices. Here we asked if family income is associated with variation in the functional brain organization of WM capacity among adolescents, and whether that variation is associated with performance on a statewide test of academic achievement in mathematics. Participants were classified into higher-income and lower-income groups based on family income, and performed a WM task with a parametric manipulation of WM load (N-back task) during functional magnetic resonance imaging (fMRI). Behaviorally, the higher-income group had greater WM capacity and higher mathematics achievement scores. Neurally, the higher-income group showed greater activation as a function of WM load in bilateral prefrontal, parietal, and other regions, although the lower-income group exhibited greater activation at the lowest load. Both groups exhibited positive correlations between parietal activations and mathematics achievement scores, but only the higher-income group exhibited a positive correlation between prefrontal activations and mathematics scores. Most of these findings were maintained when higher- and lower-income groups were matched on WM task performance or nonverbal IQ. Findings indicate that the functional neural architecture of WM varies with family income and is associated with education measures of mathematics achievement.

Native-language N400 and P600 predict dissociable language-learning abilities in adults.

Language learning aptitude during adulthood varies markedly across individuals. An individual's native-language ability has been associated with success in learning a new language as an adult. However, little is known about how native-language processing affects learning success and what neural markers of native-language processing, if any, are related to success in learning. We therefore related variation in electrophysiology during native-language processing to success in learning a novel artificial language. Event-related potentials (ERPs) were recorded while native English speakers judged the acceptability of English sentences prior to learning an artificial language. There was a trend towards a double dissociation between native-language ERPs and their relationships to novel syntax and vocabulary learning. Individuals who exhibited a greater N400 effect when processing English semantics showed better future learning of the artificial language overall. The N400 effect was related to syntax learning via its specific relationship to vocabulary learning. In contrast, the P600 effect size when processing English syntax predicted future syntax learning but not vocabulary learning. These findings show that distinct neural signatures of native-language processing relate to dissociable abilities for learning novel semantic and syntactic information.

Media multitasking in adolescence.

Media use has been on the rise in adolescents overall, and in particular, the amount of media multitasking-multiple media consumed simultaneously, such as having a text message conversation while watching TV-has been increasing. In adults, heavy media multitasking has been linked with poorer performance on a number of laboratory measures of cognition, but no relationship has yet been established between media-multitasking behavior and real-world outcomes. Examining individual differences across a group of adolescents, we found that more frequent media multitasking in daily life was associated with poorer performance on statewide standardized achievement tests of math and English in the classroom, poorer performance on behavioral measures of executive function (working memory capacity) in the laboratory, and traits of greater impulsivity and lesser growth mindset. Greater media multitasking had a relatively circumscribed set of associations, and was not related to behavioral measures of cognitive processing speed, implicit learning, or manual dexterity, or to traits of grit and conscientiousness. Thus, individual differences in adolescent media multitasking were related to specific differences in executive function and in performance on real-world academic achievement measures: More media multitasking was associated with poorer executive function ability, worse academic achievement, and a reduced growth mindset.