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Determining the Overlap between Latent Behavioral and Neural Changes in Executive Control in Middle School

Research Team


Principal Investigator: Carrie Clark

Funding Information

Funding Agency: National Institutes of Health (NIH)

Award Date: Aug 8, 2019

End Date: May 31, 2021


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. 

This study will capitalize on behavioral and resting state fMRI data from wave 1 of the Adolescent Brain and Cognitive Development (ABCD) Study, which includes more than 11,000 U.S. representative, 9- to 10-year-olds. A sophisticated latent statistical modeling approach will be used to determine whether EC can be clearly segregated and differentiated from other cognitive skills — e.g., language, episodic memory — that develop rapidly during this age period.

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. 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. 

The study will also 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. 

The goal is to provide a clearer picture of the nature of these critically important EC processes in this key period of transition to between childhood and adolescence. The study also aims to clarify whether the process of EC specialization and segregation may be marker of risk for psychopathology, thereby pinpointing promising targets for developmental assessment and early intervention.

Academic Intervention & Learning

Carrie Clark, assistant professor of educational psychology