Functional network integration and attention skills in young children.
Ontology highlight
ABSTRACT:
SUBMITTER: Rohr CS
PROVIDER: S-EPMC6969078 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Attention deficit hyperactivity disorder (ADHD) is a prevalent childhood neurodevelopmental disorder. Given the profound brain changes that occur during childhood and adolescence, it is important to examine longitudinal changes of both functional and structural brain connectivity across development in ADHD. This study aimed to examine the development of functional and structural connectivity in children with ADHD compared to controls using graph metrics. One hundred and seventy five individuals (91 children with ADHD and 84 non-ADHD controls) participated in a longitudinal neuroimaging study with up to three waves. Graph metrics were derived from 370 resting state fMRI (197 Control, 173 ADHD) and 297 diffusion weighted imaging data (152 Control, 145 ADHD) acquired between the ages of 9 and 14. For functional connectivity, children with ADHD (compared to typically developing children) showed lower degree, local efficiency and betweenness centrality predominantly in parietal, temporal and visual cortices and higher degree, local efficiency and betweenness centrality in frontal, parietal, and temporal cortices. For structural connectivity, children with ADHD had lower local efficiency in parietal and temporal cortices and, higher degree and betweenness centrality in frontal, parietal and temporal cortices. Further, differential developmental trajectories of functional and structural connectivity for graph measures were observed in higher-order cognitive and sensory regions. Our findings show that topology of functional and structural connectomes matures differently between typically developing controls and children with ADHD during childhood and adolescence. Specifically, functional and structural neural circuits associated with sensory and various higher order cognitive functions are altered in children with ADHD.
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Project description:In early 2020, in-person data collection dramatically slowed or was completely halted across the world as many labs were forced to close due to the COVID-19 pandemic. Developmental researchers who assess looking time (especially those who rely heavily on in-lab eye-tracking or live coding techniques) were forced to re-think their methods of data collection. While a variety of remote or online platforms are available for gathering behavioral data outside of the typical lab setting, few are specifically designed for collecting and processing looking time data in infants and young children. To address these challenges, our lab developed several novel approaches for continuing data collection and coding for a remotely administered audiovisual looking time protocol. First, we detail a comprehensive approach for successfully administering the Multisensory Attention Assessment Protocol (MAAP), developed by our lab to assess multisensory attention skills (MASks; duration of looking, speed of shifting/disengaging, accuracy of audiovisual matching). The MAAP is administered from a distance (remotely) by using Zoom, Gorilla Experiment Builder, an internet connection, and a home computer. This new data collection approach has the advantage that participants can be tested in their homes. We discuss challenges and successes in implementing our approach for remote testing and data collection during an ongoing longitudinal project. Second, we detail an approach for estimating gaze direction and duration collected remotely from webcam recordings using a post processing toolkit (OpenFace) and demonstrate its effectiveness and precision. However, because OpenFace derives gaze estimates without translating them to an external frame of reference (i.e., the participant's screen), we developed a machine learning (ML) approach to overcome this limitation. Thus, third, we trained a ML algorithm [(artificial neural network (ANN)] to classify gaze estimates from OpenFace with respect to areas of interest (AOI) on the participant's screen (i.e., left, right, and center). We then demonstrate reliability between this approach and traditional coding approaches (e.g., coding gaze live). The combination of OpenFace and ML will provide a method to automate the coding of looking time for data collected remotely. Finally, we outline a series of best practices for developmental researchers conducting remote data collection for looking time studies.
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Project description:Attention problems are common in school-age children born very preterm (VPT; < 32 weeks gestational age), but the contribution of aberrant functional brain connectivity to these problems is not known. As part of a prospective longitudinal study, brain functional connectivity (fc) was assessed alongside behavioral measures of selective, sustained, and executive attention in 58 VPT and 65 full-term (FT) born children at corrected-age 12 years. VPT children had poorer sustained, shifting, and divided attention than FT children. Within the VPT group, poorer attention scores were associated with between-network connectivity in ventral attention, visual, and subcortical networks, whereas between-network connectivity in the frontoparietal, cingulo-opercular, dorsal attention, salience and motor networks was associated with attention functioning in FT children. Network-level differences were also evident between VPT and FT children in specific attention domains. Findings contribute to our understanding of fc networks that potentially underlie typical attention development and suggest an alternative network architecture may help support attention in VPT children.
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Project description:Sustained attention is a critical cognitive ability that improves over the course of development and predicts important real-world outcomes, such as academic achievement. However, the majority of work demonstrating links between sustained attention and academic skills has been conducted in lab-based settings that lack the ecological validity of a more naturalistic environment, like school. Further, most studies focus on targeted academic measures of specific sub-skills and have not fully examined whether this relationship generalizes to broad measures of academic achievement that are used for important, real-world, academic advancement decisions, such as standardized test scores. To address this gap, we examined the role of sustained attention in predicting targeted and broad assessments of academic abilities, where all skills were assessed in group-based environments in schools. In a sample of over 700 students aged 9-14, we showed that attention was positively related to performance on targeted assessments (math fluency and reading comprehension), as well as broad academic measures (statewide standardized test scores). Moreover, we found that attention was more predictive of targeted math sub-skills compared to assessments of broad math abilities, but was equally predictive of reading for both types of measures. Our findings add to our understanding of how sustained attention is linked to academic skills assessed in more 'real-world', naturalistic school environments and have important implications for designing tools to support student's academic success.
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Project description:PurposeTo identify the social-ecological correlates associated with fundamental movement skills at the child, family, and environment levels in young children.MethodsPreschool children from 4 Colorado Head Start/preschool centers were recruited from 2010 to 2012. Two hundred twenty-eight children (128 girls; age = 56.08 ± 4.09 months; body mass index (BMI) z-score = 0.53 ± 1.12 (mean ± SD); 42.1% Hispanic/Latino) and 159 families were included in the final analysis. Children's perceived competence and fundamental movement skills were assessed via the Pictorial Scale of Perceived Competence and Social Acceptance and the Bruininks-Oseretsky Test of Motor Proficiency, 2nd edition. Data on the number of children in the family, parent age, BMI, education, employment status, family income, perception of child coordination, and home physical activity environment were collected via a questionnaire. Linear regressions adjusted for child BMI, age, sex, and school site were performed at each level.ResultsChild perceived cognitive competence was positively associated with locomotor skills (p = 0.04; adjusted R 2 = 0.035) and object-control skills (p = 0.003; adjusted R 2 = 0.083) at the child level. Parent education, BMI, and perception of child coordination were positively associated with locomotor skills and explained 8.8% of variance, but only parent education was significant (p = 0.04) at the family level. In addition, physical environment was positively associated with locomotor skills (p = 0.02) and explained 5.5% of variance at the environment level.ConclusionSocial-ecological correlates associated with young children's fundamental movement skills are multidimensional and differ according to skill category at the child, family, and environment levels.
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Project description:How do children allocate their attention? There is too much information in the world to encode it all, so children must pick and choose. How do they organize their sampling to make the most of the learning opportunities that surround them? Previous work shows infants actively seek intermediately predictable information. Here we employ eye-tracking and computational modeling to examine the impact of stimulus predictability across early childhood (ages 3-6 years, n = 72, predominantly Non-Hispanic White, middle- to upper-middle-income), by chronological age and cognitive ability. Results indicated that children prefer attending to stimuli of intermediate predictability, with no differences in this pattern based on age or cognitive ability. The consistency may suggest a robust general information-processing mechanism that operates across the lifespan.
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Project description:This study explored whether young children with Down syndrome show praxis deficits that impact activities of daily living, and whether these deficits are specific to Down syndrome. We compared the performance of young children with Down syndrome, a mental age-matched group of children with developmental disabilities of mixed or unknown etiologies, and a group of typically developing infants and toddlers on praxis tasks and overall adaptive behavior (Vineland Adaptive Behavior Scales). Children with Down syndrome showed poorer overall motor functioning than the developmental disabilities comparison group as measured by the Vineland Adaptive Behavior Scales, F(2, 47) = 5.24, p < .01 (using one-way analysis of variance [ANOVA]). A one-way multivariate analysis of variance also showed that children with Down syndrome performed significantly worse overall than the developmental disabilities comparison group on a battery of praxis tasks, F(7, 18) = 2.95, p < .05, and a series of object retrieval tasks, F(7, 18) = 2.95, p < .05, suggesting a deficit in praxis that is specific to Down syndrome. Children with Down syndrome elicited significantly more help than both comparison groups during object retrieval trials, F(2, 48) = 4.94, p < .01 (using one-way ANOVA). When chronological age was partialled out, a strong relationship was observed between praxis and adaptive functioning in Down syndrome, r(8) = .69, p < .05. These findings suggest that young children with Down syndrome may need targeted interventions that focus on both praxis skills and motivational orientation.
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Project description:UNLABELLED:Recent work has demonstrated that human whole-brain functional connectivity patterns measured with fMRI contain information about cognitive abilities, including sustained attention. To derive behavioral predictions from connectivity patterns, our group developed a connectome-based predictive modeling (CPM) approach (Finn et al., 2015; Rosenberg et al., 2016). Previously using CPM, we defined a high-attention network, comprising connections positively correlated with performance on a sustained attention task, and a low-attention network, comprising connections negatively correlated with performance. Validating the networks as generalizable biomarkers of attention, models based on network strength at rest predicted attention-deficit/hyperactivity disorder (ADHD) symptoms in an independent group of individuals (Rosenberg et al., 2016). To investigate whether these networks play a causal role in attention, here we examined their strength in healthy adults given methylphenidate (Ritalin), a common ADHD treatment, compared with unmedicated controls. As predicted, individuals given methylphenidate showed patterns of connectivity associated with better sustained attention: higher high-attention and lower low-attention network strength than controls. There was significant overlap between the high-attention network and a network with greater strength in the methylphenidate group, and between the low-attention network and a network with greater strength in the control group. Network strength also predicted behavior on a stop-signal task, such that participants with higher go response rates showed higher high-attention and lower low-attention network strength. These results suggest that methylphenidate acts by modulating functional brain networks related to sustained attention, and that changing whole-brain connectivity patterns may help improve attention. SIGNIFICANCE STATEMENT:Recent work identified a promising neuromarker of sustained attention based on whole-brain functional connectivity networks. To investigate the causal role of these networks in attention, we examined their response to a dose of methylphenidate, a common and effective treatment for attention-deficit/hyperactivity disorder, in healthy adults. As predicted, individuals on methylphenidate showed connectivity signatures of better sustained attention: higher high-attention and lower low-attention network strength than controls. These results suggest that methylphenidate acts by modulating strength in functional brain networks related to attention, and that changing whole-brain connectivity patterns may improve attention.
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Project description:Accumulating evidence suggests brain network dysfunction in attention-deficit/hyperactivity disorder (ADHD). Whether large-scale brain network connectivity patterns reflect clinical heterogeneity in ADHD remains to be fully understood. This study aimed to characterize the differential within- and between-network functional connectivity (FC) changes in children with ADHD combined (ADHD-C) or inattentive (ADHD-I) subtypes and their associations with ADHD symptoms. We studied the task-free functional magnetic resonance imaging (fMRI) data of 58 boys with ADHD and 28 demographically matched healthy controls. We measured within- and between-network connectivity of both low-level (sensorimotor) and high-level (cognitive) large-scale intrinsic connectivity networks and network modularity. We found that children with ADHD-C but not those with ADHD-I exhibited hyper-connectivity within the anterior default mode network (DMN) compared with controls. Additionally, children with ADHD-C had higher inter-network FC between the left executive control (ECN) and the salience (SN) networks, between subcortical and visual networks, and between the DMN and left auditory networks than controls, while children with ADHD-I did not show differences compared with controls. Similarly, children with ADHD-C but not ADHD-I showed lower network modularity compared with controls. Importantly, these observed abnormal inter-network connectivity and network modularity metrics were associated with Child Behavioral Checklist (CBCL) attention-deficit/hyperactivity problems and internalizing problems in children with ADHD. This study revealed relatively greater loss of brain functional network segregation in childhood ADHD combined subtype compared to the inattentive subtype, suggesting differential large-scale functional brain network topology phenotype underlying childhood ADHD heterogeneity.
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