# Determining the overlap between latent behavioral and neural changes in executive control in middle childhood

> **NIH NIH R03** · UNIVERSITY OF NEBRASKA LINCOLN · 2020 · $75,093

## Abstract

Almost all forms of mental illness involve impairments in executive control (EC), the higher-level cognitive
processes that support adaptive, self-regulated, goal-directed behavior. During middle childhood, both the
cognitive EC system and the brain networks that support self-regulation undergo dramatic growth and
reorganization. Sophisticated latent statistical modeling techniques show that children progressively draw on a
wider array of specialized, proactive processes, including working memory and flexible attention, to perform
executive tasks. At a neural level, children also show more clearly differentiated activity between task-positive
central executive and dorsal attention networks, which support top-down, externally focused attention, and the
task-negative default mode network, which supports internal self-awareness, episodic memory, and reflection.
What remains unknown is whether observed changes in the structure of behaviorally-measured EC are
reflective of these changes in neural network organization and whether measures of this specialization process
may help to identify children at risk for psychopathology. To address these questions, the proposed study will
capitalize on behavioral and resting state fMRI data from wave 1 of the Adolescent Brain and Cognitive
Development (ABCD) Study, which includes over 11,000, US representative, 9 to 10 year-olds. First, the study
will use sophisticated latent statistical modeling to determine whether a unique, specialized EC construct can
be clearly segregated and differentiated from other cognitive skills (language, episodic memory) that also are
developing rapidly during this age period. This modeling approach will produce a more refined measure of EC
that is situated within the cognitive system as a whole. Second, this robust measure of latent, behavioral EC
will be correlated with measures of functional neural network segregation to test the hypothesis that higher
levels of EC are associated with higher levels of neural network specialization and flexibility. Specifically,
analyses will determine whether children with higher latent EC, independent of other cognitive abilities, show
more negative correlations between task-positive and task-negative neural networks. Finally, the study will
examine whether lower gestational age, a well-established risk factor for atypical neural development, EC
impairments, and psychopathology, is associated with lower levels of specialization and differentiation of EC
and associated neural networks. By accomplishing these objectives, the study will provide a clearer picture of
the nature of these critically important EC processes in this key period of transition to between childhood and
adolescence. Through its unprecedented integration of complex latent statistical modeling at the behavioral
level with network analysis at the level of the brain, the study will also clarify whether the process of EC
specialization and segregation may be marker of risk for psych...

## Key facts

- **NIH application ID:** 9991947
- **Project number:** 5R03MH120381-02
- **Recipient organization:** UNIVERSITY OF NEBRASKA LINCOLN
- **Principal Investigator:** Caron Ann Campbell Clark
- **Activity code:** R03 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $75,093
- **Award type:** 5
- **Project period:** 2019-08-08 → 2021-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9991947

## Citation

> US National Institutes of Health, RePORTER application 9991947, Determining the overlap between latent behavioral and neural changes in executive control in middle childhood (5R03MH120381-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9991947. Licensed CC0.

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