Variability in the brain’s functional network connectivity is associated with differences in cognition. The degree to which brain networks flexibly reconfigure, or alternatively remain stable, can differ across regions of cortex, across time, and across individuals. The goal of this dissertation was to investigate how the brain’s functional network architecture is reconfigured to support abstract reasoning and rule learning. I proposed that flexibility within frontoparietal cortex, combined with a stable network core, is beneficial for effective reasoning and rule learning.
Experiment One investigated the activation patterns and dynamic community structure of brain networks associated with shifting task demands during abstract reasoning. Twenty-seven subjects underwent fMRI scanning during resting state and during a subsequent abstract reasoning task. When quantifying network reconfiguration between resting and task states, I found a stable system within default and somatomotor networks alongside a more flexible frontoparietal control network. The results motivated a novel understanding of how the brain performs reasoning tasks: an underlying stable functional network acts as a cognitive control mechanism, priming task-active nodes within frontoparietal cortex to variably activate for unique task conditions.
Experiment Two used a dynamic network analysis to identify changes in functional brain networks that were associated with context-dependent rule learning. During fMRI scanning, twenty-nine naïve subjects were challenged to learn a set of context-dependent rules. Successful learners showed greater stability in ventral attention and somatomotor regions, increased assortative mixing of cognitive control regions as rules were learned, and greater segregation of attention networks throughout the entire task. The results suggested that a stable ventral attention network and a flexible frontoparietal control network support sustained attention and the formation of rule representations.
In Experiment Three, I carried out a separate analysis of data from Experiment 2 to characterize the functional connectivity patterns with the hippocampus that emerged during successful rule learning. The results demonstrated that the hippocampal head became increasingly functionally connected to the lateral frontal pole and caudate in successful learners. Additionally, the entire hippocampus exhibited decreased functional connectivity with the mid-cingulate and precuneus in successful learners.
These three experiments demonstrated that stable functional connectivity in somatomotor and ventral attention networks, combined with flexible reconfiguration of frontoparietal cortex, is advantageous for successful rule learning and abstract reasoning. Altogether, this dissertation demonstrated that individual differences in dynamic functional connectivity are associated with learning, and that stability of brain networks across time and tasks supports higher order cognition. / 2025-01-23T00:00:00Z
| Identifer | oai:union.ndltd.org:bu.edu/oai:open.bu.edu:2144/45511 |
| Date | 24 January 2023 |
| Creators | Morin, Thomas M. |
| Contributors | Stern, Chantal E. |
| Source Sets | Boston University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
| Rights | Attribution 4.0 International, http://creativecommons.org/licenses/by/4.0/ |
Page generated in 0.8599 seconds