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Brain Dynamics Underlying the Development of Cognitive Flexibility Please do not remove this page Brain Dynamics Underlying the Development of Cognitive Flexibility Kupis, Lauren https://scholarship.miami.edu/discovery/delivery/01UOML_INST:ResearchRepository/12381228840002976?l#13381228830002976 Kupis, L. (2021). Brain Dynamics Underlying the Development of Cognitive Flexibility [University of Miami]. https://scholarship.miami.edu/discovery/fulldisplay/alma991031583588402976/01UOML_INST:ResearchR epository Open Downloaded On 2021/09/24 08:01:55 -0400 Please do not remove this page UNIVERSITY OF MIAMI BRAIN DYNAMICS UNDERLYING THE DEVELOPMENT OF COGNITIVE FLEXIBILITY By Lauren Kupis A THESIS Submitted to the Faculty of the University of Miami in partial fulfillment of the requirements for the degree of Master of Science Coral Gables, Florida August 2021 ©2021 Lauren Kupis All Rights Reserved UNIVERSITY OF MIAMI A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science BRAIN DYNAMICS UNDERLYING THE DEVELOPMENT OF COGNITIVE FLEXIBILITY Lauren Kupis Approved: Lucina Uddin, Ph.D. Aaron Heller, Ph.D. Professor of Psychology Professor of Psychology Manish Saggar, Ph.D. Guillermo Prado, Ph.D. Stanford University Dean of the Graduate School LAUREN KUPIS (M.S., Psychology) Brain Dynamics Underlying the Development (August 2021) of Cognitive Flexibility Abstract of a thesis at the University of Miami. Thesis supervised by Professor Lucina Uddin. No. of pages in text. (68) Cognitive flexibility, or the ability to mentally switch according to changing environmental demands, supports optimal outcomes across development. Despite the importance of cognitive flexibility for development, little is known regarding the neural mechanisms underlying it. The goal of the current study was to uncover developmental differences in the neural systems supporting cognitive flexibility using a functional MRI task designed to elicit switching mechanisms in both children and adults and by using a novel method called co-activation pattern (CAP) analysis. The current study examined neural differences in brain activation and dynamic brain states between children and adults during a cognitive flexibility task, and the relationships between brain dynamics and behavior. The CAP analysis revealed that children as compared with adults dwelled longer in brain states consisting of hybrid brain states consisting of between-network coupling. Additionally, in both children and adults, more frequent occurrence of a brain state consisting of coupling between the default and central executive networks was associated with better cognitive flexibility as measured by the Behavior Rating Inventory of Executive Function. This study provides the first evidence of the developmental changes associated with brain dynamic changes during cognitive flexibility and links brain function with a real-world measure of cognitive flexibility, thereby paving the way for future research of neurodevelopmental disorders characterized by atypical cognitive flexibility. TABLE OF CONTENTS Page LIST OF FIGURES .................................................................................................................. iv LIST OF TABLES ................................................................................................................... v Chapter 1 BACKGROUND ......................................................................................................... 1 Cognitive flexibility… ................................................................................................. 1 Executive functions needed to implement cognitive flexibility… .................................. 6 Development of cognitive flexibility ............................................................................ 11 Brain network findings in cognitive flexibility .............................................................. 19 Specific aims and hypotheses ....................................................................................... 23 2 METHODS ................................................................................................................. 26 Behavioral measures ................................................................................................... 27 Data acquisition .......................................................................................................... 30 Data preprocessing ...................................................................................................... 30 Analytic plan............................................................................................................... 32 3 RESULTS ................................................................................................................... 34 Brain activation ........................................................................................................... 34 Co-activation pattern analysis (CAP)........................................................................... 38 Age differences in CAPs ............................................................................................. 38 Brain-behavior relationships with CAPs ...................................................................... 39 4 DISCUSSION ............................................................................................................. 41 Brain activation ........................................................................................................... 41 Co-activation pattern analysis (CAP) ........................................................................... 43 Limitations and future directions ................................................................................. 48 Conclusion .................................................................................................................. 49 FIGURES ................................................................................................................................ 50 REFERENCES ......................................................................................................................... 56 iii LIST OF FIGURES FIGURE 1…………………………………………………………………………….. 50 FIGURE 2…………………………………………………………………………….. 51 FIGURE 3…………………………………………………………………………….. 52 FIGURE 4…………………………………………………………………………….. 53 FIGURE 5…………………………………………………………………………….. 54 iv LIST OF TABLES TABLE 1…………………………………………………………………………….. 26 TABLE 2…………………………………………………………………………….. 35 v CHAPTER 1: BACKGROUND Flexible cognition and behavior are required to adaptively respond to changing environmental demands. This process is enabled by cognitive flexibility, the mental readiness to switch to initiate flexible behavioral responses (Dajani & Uddin, 2015). Cognitive flexibility is a core feature of executive functioning (Diamond, 2013; Logue & Gould, 2014) and is associated with positive life outcomes including the successful transition into adulthood (Burt & Paysnick, 2012), resilience to negative life events (Genet & Siemer, 2011), and better quality of life (Davis et al., 2010). Cognitive flexibility is also critical for developmental outcomes, including reading and math skills (Yeniad et al., 2013), social competence (Ciairano et al., 2006), and overall academic achievement (Titz & Karbach, 2014). Despite the importance of cognitive flexibility across the lifespan, little is known regarding the neural mechanisms supporting the development of this ability. Cognitive flexibility Examples of cognitive flexibility include the ability to think differently about a situation, and quickly switch between tasks or strategies to solve a problem. Being flexible ultimately aids creativity (Lu et al., 2017, 2019), problem-solving (Ionescu, 2012), learning (Kehagia et al., 2010), and resilience to negative life events (Genet & Siemer, 2011). Cognitive flexibility benefits adaptation via the ability to quickly transition from different activities or change perspective. Therefore, cognitive flexibility is an important feature of daily functioning. Cognitive flexibility is also associated with positive life outcomes including academic achievement such as reading and math skills (Yeniad et al., 2013), and the 1 2 successful transition into adulthood (Burt & Paysnick, 2012). Conversely, cognitive inflexibility may be a risk factor for repetitive or ruminative thoughts (Deveney & Deldin, 2006; Genet et al., 2013; Whitmer & Banich, 2007), which underlie psychological disorders such as anxiety, depression, obsessive-compulsive disorder (OCD), and autism spectrum disorder (ASD) (Keenan et al., 2018; McDougle et al., 1995; van Steensel et al., 2011). Ultimately, cognitive flexibility is important during childhood and adolescence because these periods are accompanied by learning, susceptibility to psychological disorders (e.g., anxiety and depression; (Côté et al., 2009), and increased substance use (Rose et al., 2019). In all cases, cognitive flexibility may buffer against negative effects. Although cognitive flexibility contributes to positive adaptation and learning across development, the underlying brain regions supporting developmental changes of cognitive flexibility are not fully understood. Characterizing the brain regions involved in cognitive flexibility across development may clarify the mechanisms underlying the cognitive and behavioral changes observed. The lateral frontoparietal network (FPN) has been found to be important in the development of executive function broadly (Dajani & Uddin, 2015). Further, flexible interactions among brain regions and neural
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