Association between resting-state coactivation in the parieto-frontal network and intelligence during late childhood and adolescence

Individualized prediction of multi-domain intelligence quotient in bipolar disorder patients using resting-state functional connectivity

BACKGROUND

Although accumulating studies have explored the neural underpinnings of intelligence quotient (IQ) in patients with bipolar disorder (BD), these studies utilized a classification/comparison scheme that emphasized differences between BD and healthy controls at a group level. The present study aimed to infer BD patients' IQ scores at the individual level using a prediction model.

METHODS

We applied a cross-validated Connectome-based Predictive Modeling (CPM) framework using resting-state fMRI functional connectivity (FCs) to predict BD patients' IQ scores, including verbal IQ (VIQ), performance IQ (PIQ), and full-scale IQ (FSIQ). For each IQ domain, we selected the FCs that contributed to the predictions and described their distribution across eight widely-recognized functional networks. Moreover, we further explored the overlapping patterns of the contributed FCs for different IQ domains.

RESULTS

The CPM achieved statistically significant prediction performance for three IQ domains in BD patients. Regarding the contributed FCs, we observed a widespread distribution of internetwork FCs across somatomotor, visual, dorsal attention, and ventral attention networks, demonstrating their correspondence with aberrant FCs correlated to cognition deficits in BD patients. A convergent pattern in terms of contributed FCs for different IQ domains was observed, as evidenced by the shared-FCs with a leftward hemispheric dominance.

CONCLUSIONS

The present study preliminarily explored the feasibility of inferring individual IQ scores in BD patients using the FCs-based CPM framework. It is a step toward the development of applicable techniques for quantitative and objective cognitive assessment in BD patients and contributes novel insights into understanding the complex neural mechanisms underlying different IQ domains.

A comprehensive systematic review of fMRI studies on brain connectivity in healthy children and adolescents: Current insights and future directions

This systematic review considered evidence of children's and adolescents' typical brain connectivity development studied through resting-state functional magnetic resonance imaging (rs-fMRI). With aim of understanding the state of the art, what has been researched thus far and what remains unknown, this paper reviews 58 studies from 2013 to 2023. Considering the results, rs-fMRI stands out as an appropriate technique for studying language and attention within cognitive domains, and personality traits such as impulsivity and empathy. The most used analyses encompass seed-based, independent component analysis (ICA), the amplitude of the low frequency fluctuations (ALFF), and fractional ALFF (fALFF). The findings highlight key themes, including age-related changes in intrinsic connectivity, sex-specific patterns, and the relevance of the Default Mode Network (DMN). Overall, there is a need for longitudinal approaches to trace the typical developmental trajectory of neural networks from childhood through adolescence with fMRI at rest.

Functional brain hubs are related to age: A primer study with rs-fMRI

Background/Objective

Research on the ontogenetic development of brain networks using resting state has shown to be useful for understanding age-associated changes in brain connectivity. This work aimed to analyze the relationship between brain connectivity, age and intelligence.

Methods

A sample of 26 children and adolescents between 6 and 18 years of both sexes underwent a resting-state functional magnetic resonance imaging study. We estimated the values of fractional Amplitude low-frequency fluctuations (fALFF) and the values of Regional homogeneity (ReHo) in a voxelwise analysis to later correlate them with age and intelligence quotient (IQ).

Results

No significant correlations were found with IQ, but it was found that the fALFF values of the left precentral cortex (premotor cortex and supplementary motor area), as well as the ReHo values of the medial frontal gyrus, and the precentral cortex of the left hemisphere, correlate with age. Conclusions: Hubs related to various "task positive" networks closely related to cognitive functioning would present a development more related to age and relatively independent of individual differences in intelligence. These findings suggest that the premotor cortex and supplementary motor cortex could be a cortical hub that develops earlier than previously reported and that it would be more related to age than to intelligence level.

Dynamic transient brain states in preschoolers mirror parental report of behavior and emotion regulation

The temporal dynamics of resting-state networks may represent an intrinsic functional repertoire supporting cognitive control performance across the lifespan. However, little is known about brain dynamics during the preschool period, which is a sensitive time window for cognitive control development. The fast timescale of synchronization and switching characterizing cortical network functional organization gives rise to quasi-stable patterns (i.e., brain states) that recur over time. These can be inferred at the whole-brain level using hidden Markov models (HMMs), an unsupervised machine learning technique that allows the identification of rapid oscillatory patterns at the macroscale of cortical networks. The present study used an HMM technique to investigate dynamic neural reconfigurations and their associations with behavioral (i.e., parental questionnaires) and cognitive (i.e., neuropsychological tests) measures in typically developing preschoolers (4-6 years old). We used high-density EEG to better capture the fast reconfiguration patterns of the HMM-derived metrics (i.e., switching rates, entropy rates, transition probabilities and fractional occupancies). Our results revealed that the HMM-derived metrics were reliable indices of individual neural variability and differed between boys and girls. However, only brain state transition patterns toward prefrontal and default-mode brain states, predicted differences on parental-report questionnaire scores. Overall, these findings support the importance of resting-state brain dynamics as functional scaffolds for behavior and cognition. Brain state transitions may be crucial markers of individual differences in cognitive control development in preschoolers.

Functional connectivity directionality between large-scale resting-state networks across typical and non-typical trajectories in children and adolescence

Mental disorders often emerge during adolescence and have been associated with age-related differences in connection strengths of brain networks (static functional connectivity), manifesting in non-typical trajectories of brain development. However, little is known about the direction of information flow (directed functional connectivity) in this period of functional brain progression. We employed dynamic graphical models (DGM) to estimate directed functional connectivity from resting state functional magnetic resonance imaging data on 1143 participants, aged 6 to 17 years from the healthy brain network (HBN) sample. We tested for effects of age, sex, cognitive abilities and psychopathology on estimates of direction flow. Across participants, we show a pattern of reciprocal information flow between visual-medial and visual-lateral connections, in line with findings in adults. Investigating directed connectivity patterns between networks, we observed a positive association for age and direction flow from the cerebellar to the auditory network, and for the auditory to the sensorimotor network. Further, higher cognitive abilities were linked to lower information flow from the visual occipital to the default mode network. Additionally, examining the degree networks overall send and receive information to each other, we identified age-related effects implicating the right frontoparietal and sensorimotor network. However, we did not find any associations with psychopathology. Our results suggest that the directed functional connectivity of large-scale resting-state brain networks is sensitive to age and cognition during adolescence, warranting further studies that may explore directed relationships at rest and trajectories in more fine-grained network parcellations and in different populations.

Brain structural parameters correlate with University Selection Test outcomes in Chilean high school graduates

How well students learn and perform in academic contexts is a focus of interest for the students, their families, and the entire educational system. Although evidence has shown that several neurobiological factors are involved in scholastic achievement (SA), specific brain measures associated with academic outcomes and whether such associations are independent of other factors remain unclear. This study attempts to identify the relationship between brain structural parameters, and the Chilean national University Selection Test (PSU) results in high school graduates within a multidimensional approach that considers socio-economic, intellectual, nutritional, and demographic variables. To this end, the brain morphology of a sample of 102 students who took the PSU test was estimated using Magnetic Resonance Imaging. Anthropometric parameters, intellectual ability (IA), and socioeconomic status (SES) were also measured. The results revealed that, independently of sex, IA, gray matter volume, right inferior frontal gyrus thickness, and SES were significantly associated with SA. These findings highlight the role of nutrition, health, and socioeconomic variables in academic success.

Adolescents with a concussion have altered brain network functional connectivity one month following injury when compared to adolescents with orthopedic injuries

Concussion is a mild traumatic brain injury (mTBI) with increasing prevalence among children and adolescents. Functional connectivity (FC) within and between the default mode network (DMN), central executive network (CEN) and salience network (SN) has been shown to be altered post-concussion. Few studies have investigated connectivity within and between these 3 networks following a pediatric concussion. The present study explored whether within and between-network FC differs between a pediatric concussion and orthopedic injury (OI) group aged 10-18. Participants underwent a resting-state functional magnetic resonance imaging (rs-fMRI) scan at 4 weeks post-injury. One-way ANCOVA analyses were conducted between groups with the seed-based FC of the 3 networks. A total of 55 concussion and 27 OI participants were included in the analyses. Increased within-network FC of the CEN and decreased between-network FC of the DMN-CEN was found in the concussion group when compared to the OI group. Secondary analyses using spherical SN regions of interest revealed increased within-network FC of the SN and increased between-network FC of the DMN-SN and CEN-SN in the concussion group when compared to the OI group. This study identified differential connectivity patterns following a pediatric concussion as compared to an OI 4 weeks post-injury. These differences indicate potential adaptive brain mechanisms that may provide insight into recovery trajectories and appropriate timing of treatment within the first month following a concussion.

Brain Structural Correlates of Intelligence in Attention Deficit Hyperactivity Disorder (ADHD) Individuals

Introduction

Neuroimaging evidence has shown the relationship of intelligence with several structural brain properties in normal individuals. However, this relationship with attention deficit hyperactivity disorder (ADHD) needs to be investigated.

Methods

We estimated grey matter (GM) density of the brain using magnetic resonance imaging (MRI) scan on 56 ADHD individuals, including 30 combined individuals (Mean±SD age: 10.44±2.41, intelligence quotient: [IQ]=112.13±13.15, male, 24 right hands) and 26 inattentive individuals (mean age =11.39±2.1, IQ=107.44±13.98, male, 28 right hands) as well as 30 IQ matched healthy control group (mean age=11.08±2.15, IQ=115±13.56, male, 23 right hands).

Results

In this study, two statistical approaches were used. In the first approach, region-based as well as the whole association patterns between full-scale IQ and GM were computed and compared between groups. The second approach was to examine the differential pattern of GM density without considering IQ in three groups.

Conclusion

Results showed significant differences between the ADHD group and the control. This finding could indicate that intelligence is not purely based on the density of GM in certain brain regions; it is a dynamic phenomenon and drastically changes neurodevelopmental disorders.

Highlights

In ADHDs as compared to healthy controls the relation between GM and IQ was decreased at right hemisphere;In ADHDs as compared to healthy controls the relation between GM and IQ was increased at left hemisphere;Differenceses of the observed relation between control group and IQ matched ADHDs suggest a compensatory mechanism in ADHDs to maintaine an adequate cognitive performance;GM is not the only determiner of intelligence. IQ score may be affected by neural dynamic of the brain; therefore, the structural covariate could be a better alternative for GM density.

Plain Language Summary

In this study, we estimated the relation between GM density and IQ score in 2 subtypes of ADHD (combined and inattentive) and IQ matched healthy control group. We compared the association between groups and found that the pattern of association in ADHDs were different from controls. In the other words, the decreased association at right hemisphere, were compensated by increased association at left hemisphere in ADHDs to maintaine adequate performance. We conclude that, the brain structure is not the single determiner of intelligence, rather intelligence may underpine by neural dynamics of the brain. Therefore, the structural covariate may be a better alternative for GM density.

Brain network coupling associated with cognitive performance varies as a function of a child's environment in the ABCD study

Prior research indicates that lower resting-state functional coupling between two brain networks, lateral frontoparietal network (LFPN) and default mode network (DMN), relates to cognitive test performance, for children and adults. However, most of the research that led to this conclusion has been conducted with non-representative samples of individuals from higher-income backgrounds, and so further studies including participants from a broader range of socioeconomic backgrounds are required. Here, in a pre-registered study, we analyzed resting-state fMRI from 6839 children ages 9-10 years from the ABCD dataset. For children from households defined as being above poverty (family of 4 with income > $25,000, or family of 5+ with income > $35,000), we replicated prior findings; that is, we found that better performance on cognitive tests correlated with weaker LFPN-DMN coupling. For children from households defined as being in poverty, the direction of association was reversed, on average: better performance was instead directionally related to stronger LFPN-DMN connectivity, though there was considerable variability. Among children in households below poverty, the direction of this association was predicted in part by features of their environments, such as school type and parent-reported neighborhood safety. These results highlight the importance of including representative samples in studies of child cognitive development.

High-definition transcranial direct current stimulation modulates performance and alpha/beta parieto-frontal connectivity serving fluid intelligence

Fluid intelligence (Gƒ) includes logical reasoning abilities and is an essential component of normative cognition. Despite the broad consensus that parieto-prefrontal connectivity is critical for Gƒ (e.g. the parieto-frontal integration theory of intelligence, P-FIT), the dynamics of such functional connectivity during logical reasoning remains poorly understood. Further, given the known importance of these brain regions for Gƒ, numerous studies have targeted one or both of these areas with non-invasive stimulation with the goal of improving Gƒ, but to date there remains little consensus on the overall stimulation-related effects. To examine this, we applied high-definition direct current anodal stimulation to the left and right dorsolateral prefrontal cortex (DLPFC) of 24 healthy adults for 20 min in three separate sessions (sham, left, and right active). Following stimulation, participants completed a logical reasoning task during magnetoencephalography (MEG). Significant neural responses at the sensor-level were imaged using a beamformer, and peak task-induced activity was subjected to dynamic functional connectivity analyses to evaluate the impact of distinct stimulation montages on network activity. We found that participants responded faster following right DLPFC stimulation vs. sham. Moreover, our neural findings followed a similar trajectory of effects such that left parieto-frontal connectivity decreased following right and left DLPFC stimulation compared to sham, with connectivity following right stimulation being significantly correlated with the faster reaction times. Importantly, our findings are consistent with P-FIT, as well as the neural efficiency hypothesis (NEH) of intelligence. In sum, this study provides evidence for beneficial effects of right DLPFC stimulation on logical reasoning. KEY POINTS: Logical reasoning is an indispensable component of fluid intelligence and involves multispectral oscillatory activity in parietal and frontal regions. Parieto-frontal integration is well characterized in logical reasoning; however, its direct neural quantification and neuromodulation by brain stimulation remain poorly understood. High-definition transcranial direct current stimulation of dorsolateral prefrontal cortex (DLPFC) had modulatory effects on task performance and neural interactions serving logical reasoning, with right stimulation showing beneficial effects. Right DLPFC stimulation led to a decrease in the response time (i.e. better task performance) and left parieto-frontal connectivity with a marginal positive association between behavioural and neural metrics. Other modes of targeted stimulation of DLPFC (e.g. frequency-specific) can be employed in future studies.

Pediatric Moderate-Severe Traumatic Brain Injury and Gray Matter Structural Covariance Networks: A Preliminary Longitudinal Investigation

Pediatric traumatic brain injury (TBI) is prevalent and can disrupt ongoing brain maturation. However, the long-term consequences of pediatric TBI on the brain's network architecture are poorly understood. Structural covariance networks (SCN), based on anatomical correlations between brain regions, may provide important insights into brain topology following TBI. Changes in global SCN (default-mode network [DMN], central executive network [CEN], and salience network [SN]) were compared sub-acutely (<90 days) and in the long-term (approximately 12-24 months) after pediatric moderate-severe TBI (n = 16), and compared to typically developing children assessed concurrently (n = 15). Gray matter (GM) volumes from selected seeds (DMN: right angular gyrus [rAG], CEN: right dorsolateral prefrontal cortex [rDLPFC], SN: right anterior insula) were extracted from T1-weighted images at both timepoints. No group differences were found sub-acutely; at the second timepoint, the TBI group showed significantly reduced structural covariance within the DMN seeded from the rAG and the (1) right middle frontal gyrus, (2) left superior frontal gyrus, and (3) left fusiform gyrus. Reduced structural covariance was also found within the CEN, that is, between the rDLPFC and the (1) calcarine sulcus, and (2) right occipital gyrus. In addition, injury severity was positively associated with GM volumes in the identified CEN regions. Over time, there were no significant changes in SCN in either group. The findings, albeit preliminary, suggest for the first time a long-term effect of pediatric TBI on SCN. SCN may be a complementary approach to characterize the global effect of TBI on the developing brain. Future work needs to further examine how disruptions of these networks relate to behavioral and cognitive difficulties.

Enhanced functional connectivity between habenula and salience network in medication-overuse headache complicating chronic migraine positions it within the addiction disorders: an ICA-based resting-state fMRI study

Background

Medication-overuse headache (MOH) is a relatively frequently occurring secondary headache caused by overuse of analgesics and/or acute migraine medications. It is believed that MOH is associated with dependence behaviors and substance addiction, in which the salience network (SN) and the habenula may play an important role. This study aims to investigate the resting-state (RS) functional connectivity between the habenula and the SN in patients with MOH complicating chronic migraine (CM) compared with those with episodic migraine (EM) and healthy controls (HC).

Methods

RS-fMRI and 3-dimensional T1-weighted images of 17 patients with MOH + CM, 18 patients with EM and 30 matched healthy HC were obtained. The RS-fMRI data were analyzed using the independent component analysis (ICA) method to investigate the group differences of functional connectivity between the habenula and the SN in three groups. Correlation analysis was performed thereafter with all clinical variables by Pearson correlation.

Results

Increased functional connectivity between bilateral habenula and SN was detected in patients with MOH + CM compared with patients with EM and HC respectively. Correlation analysis showed significant correlation between medication overuse duration and habenula-SN connectivity in MOH + CM patients.

Conclusions

The current study supported MOH to be lying within a spectrum of dependence and addiction disorder. The enhanced functional connectivity of the habenula with SN may correlate to the development or chronification of MOH. Furthermore, the habenula may be an indicator or treatment target for MOH for its integrative role involved in multiple aspects of MOH.

Correlates of intelligence via resting-state functional connectivity of the amygdala in healthy adults

Intelligence is a form of advanced cognition that includes reasoning, problem solving, pattern recognition, and establishing relationships among items. The amygdala plays an important role in cognitive processing, but the relationship between amygdalar function and intelligence has rarely been explored directly. Here, we investigated the relationship between resting-state functional connectivity (RSFC) of the amygdala and intelligence test performance in a large sample of healthy adults (N = 197). We found that two pairs of RSFCs were significantly increased in the high IQ group compared with that of the general IQ group. One of these RSFCs consisted of the right amygdala and the right superior parietal lobule, whereas the other RSFC consisted of the right amygdala and the left middle cingulum. In addition, we found that the brain regions in which the strength of RSFC significantly correlated with full IQ (FIQ) were mainly distributed in the parietal and limbic lobes. What's more, a further mediation analysis indicated that the functional connectivity of the right amygdala and the right superior parietal lobule significantly mediated the correlation between comprehension and object assembly, whereas the functional connectivity of the right amygdala and the left middle cingulum mediated the association between similarities and digit symbol. These findings suggest that amygdalar RSFC may reflect individual differences in intelligence and mediate specific relationships among different intellectual abilities.

Distinct Patterns of Atypical Functional Connectivity in Lower-Functioning Autism

BACKGROUND

Functional magnetic resonance imaging research on autism spectrum disorders (ASDs) has been largely limited to individuals with near-average intelligence. Although cognitive impairment is common in ASDs, functional network connectivity in this population remains poorly understood. Specifically, it remains unknown whether lower-functioning individuals exhibit exacerbated connectivity abnormalities similar to those previously detected in higher-functioning samples or specific divergent patterns of connectivity.

METHODS

Resting-state functional magnetic resonance imaging data from 88 children (44 ASD, 44 typically developing; average age: 11 years) were included. Based on IQ, individuals with ASDs were assigned to either a lower-functioning group (mean IQ = 77 ± 6) or a higher-functioning group (mean IQ = 123 ± 8). Two typically developing comparison groups were matched to these groups on head motion, handedness, and age. Seeds in the medial prefrontal cortex, posterior cingulate cortex, posterior superior temporal sulcus, insula, and amygdala were used to contrast whole-brain functional connectivity across groups.

RESULTS

Lower-functioning ASD participants (compared with higher-functioning ASD participants) showed significant underconnectivity within the default mode network and the ventral visual stream. Higher-functioning ASD participants (compared with matched typically developing participants) showed significantly decreased anticorrelations among default mode, salience, and task-positive regions. Effect sizes of detected differences were large (Cohen's d > 1.46).

CONCLUSIONS

Lower- and higher-functioning individuals with ASDs demonstrated distinct patterns of atypical connectivity. Findings suggest a gross pattern of predominantly reduced network integration in lower-functioning ASDs (affecting default mode and visual networks) and predominantly reduced network segregation in higher-functioning ASDs. Results indicate the need for stratification by general functional level in studies of functional connectivity in ASDs.

Correlation Between Resting-state Electroencephalographic Characteristics and Shooting Performance

According to the theories of neural plasticity and neural efficiency, professional skill training improves performance by strengthening the underlying neural mechanisms. Therefore, subjects trained professionally may exhibit changes in resting-state neurophysiological characteristics closely related to performance. To test this notion, the resting-state electroencephalogram (EEG) was measured from 35 rifle shooters after the same training regimen, and resting-state EEG characteristics were analyzed for correlations with shooting performance. The results showed a significant linear correlation between shooting performance and the coherence of electrode channels C3 and T3 in the beta1 band (r = 0.74, P < 4.2 × 10^-6). There was also a significant linear correlation between the characteristic path length of the resting-state theta band brain network and shooting performance (r = 0.56, P < 0.0005). This study identifies potential neural mechanisms underlying successful shooting and a new method for predicting and evaluating performance based on EEG characteristics.

Mechanisms of automaticity and anticipatory control in fluid intelligence

The constructs of fluid (Gf) and crystalized (Gc) intelligence represent an early attempt to describe the mechanisms of problem solving in the vertebrate brain. Modern neuroscience demonstrates that problem solving involves interplay between the mechanisms of automaticity and anticipatory control, enabling nature's elegant solution to the challenges animals face in their environment. Studies of neural functioning are making clear the primary role of cortical-subcortical interactions in the manifestation of intelligent behavior in humans and other vertebrates. A tridimensional model of intelligent problem solving is explored, wherein the basal ganglia system (BGS) and cerebrocerebellar system (CCS) interact within large scale brain networks. The BGS and CCS work together to enable automaticity to occur. The BGS enables the organism to learn what to do through a powerful instrumental learning system. The BGS also regulates when behavior is released through an inhibitory system which is incredibly sensitive to context. The CCS enables the organism to learn how to perform adaptive behaviors. Internal cerebellar models enable gradual improvements in the quality of behavioral output. The BGS and CCS interact within large scale brain networks, including the dorsal attention network (DAN), ventral attention network (VAN), default mode network (DMN) and frontoparietal network (FPN). The interactions of these systems enable vertebrate organisms to develop a vast array of complex adaptive behaviors. The benefits and importance of developing clinical tests to measure the integrity of these systems is considered.

Peer Influence Via Instagram: Effects on Brain and Behavior in Adolescence and Young Adulthood

Mobile social media often feature the ability to "Like" content posted by others. This study examined the effect of Likes on youths' neural and behavioral responses to photographs. High school and college students (N = 61, ages 13-21) viewed theirs and others' Instagram photographs while undergoing functional Magnetic Resonance Imaging (fMRI). Participants more often Liked photographs that appeared to have received many (vs. few) Likes. Popular photographs elicited greater activity in multiple brain regions, including the nucleus accumbens (NAcc), a hub of the brain's reward circuitry. NAcc responsivity increased with age for high school but not college students. When viewing images depicting risk-taking (vs. nonrisky photographs), high school students, but not college students, showed decreased activation of neural regions implicated in cognitive control.

Iodine Deficiency and the Brain: Effects and Mechanisms

Iodine is an essential micronutrient needed in human diets. As iodine is an integral component of thyroid hormone, it mediates the effects of thyroid hormone on brain development. Iodine deficiency is the most prevalent and preventable cause of mental impairment in the world. The exact mechanism through which iodine influences the brain is unclear, but is generally thought to begin with genetic expression. Many brain structures and systems appear to be affected with iodine deficiency, including areas such as the hippocampus, microstructures such as myelin, and neurotransmitters. The clearest evidence comes from the studies examining cognition in the cases of iodine deprivation or interventions involving iodine supplementation. Nevertheless, there are many inconsistencies and gaps in the literature of iodine deficiency, especially over the lifespan. This paper summarizes the literature on this topic, suggests a causal mechanism for iodine's effect on the brain, and indicates areas for the future research (e.g., using magnetic resonance imaging (MRI) and functional MRI to examine how iodine supplementation facilitates cognitive functioning).

Evolutionary and developmental changes in the lateral frontoparietal network: a little goes a long way for higher-level cognition

Relational thinking, or the ability to represent the relations between items, is widespread in the animal kingdom. However, humans are unparalleled in their ability to engage in the higher-order relational thinking required for reasoning and other forms of abstract thought. Here we propose that the versatile reasoning skills observed in humans can be traced back to developmental and evolutionary changes in the lateral frontoparietal network (LFPN). We first identify the regions within the LFPN that are most strongly linked to relational thinking, and show that stronger communication between these regions over the course of development supports improvements in relational reasoning. We then explore differences in the LFPN between humans and other primate species that could explain species differences in the capacity for relational reasoning. We conclude that fairly small neuroanatomical changes in specific regions of the LFPN and their connections have led to big ontogenetic and phylogenetic changes in cognition.

Development of the default mode and central executive networks across early adolescence: a longitudinal study

The mature brain is organized into distinct neural networks defined by regions demonstrating correlated activity during task performance as well as rest. While research has begun to examine differences in these networks between children and adults, little is known about developmental changes during early adolescence. Using functional magnetic resonance imaging (fMRI), we examined the Default Mode Network (DMN) and the Central Executive Network (CEN) at ages 10 and 13 in a longitudinal sample of 45 participants. In the DMN, participants showed increasing integration (i.e., stronger within-network correlations) between the posterior cingulate cortex (PCC) and the medial prefrontal cortex. During this time frame participants also showed increased segregation (i.e., weaker between-network correlations) between the PCC and the CEN. Similarly, from age 10 to 13, participants showed increased connectivity between the dorsolateral prefrontal cortex and other CEN nodes, as well as increasing DMN segregation. IQ was significantly positively related to CEN integration at age 10, and between-network segregation at both ages. These findings highlight early adolescence as a period of significant maturation for the brain's functional architecture and demonstrate the utility of longitudinal designs to investigate neural network development.