Dynamic Network Analysis Demonstrates the Formation of Stable Functional Networks During Rule Learning.

Variations in the functional connectivity of large-scale cortical brain networks may explain individual differences in learning ability. We used a dynamic network analysis of fMRI data to identify changes in functional brain networks that are associated with context-dependent rule learning. During fMRI scanning, naïve subjects performed a cognitive task designed to test their ability to learn context-dependent rules. Notably, subjects were given minimal instructions about the task prior to scanning. We identified several key network characteristics associated with fast and accurate rule learning. First, consistent with the formation of stable functional networks, a dynamic community detection analysis revealed regionally specific reductions in flexible switching between different functional communities in successful learners. Second, successful rule learners showed decreased centrality of ventral attention regions and increased assortative mixing of cognitive control regions as the rules were learned. Finally, successful subjects showed greater decoupling of default and attention communities throughout the entire task, whereas ventral attention and cognitive control regions became more connected during learning. Overall, the results support a framework by which a stable ventral attention community and more flexible cognitive control community support sustained attention and the formation of rule representations in successful learners.

Converging meta-analytic and connectomic evidence for functional subregions within the human retrosplenial region.

Interest in the retrosplenial cortex (RSC) has surged in recent years, as this region has been implicated in a range of cognitive processes. Previously reported anatomical and functional definitions of the human RSC encompass a larger area than expected from underlying cytoarchitectonic profiles. Here, we used a large-scale, unbiased, and data-driven approach combining functional MRI meta-analysis and resting-state functional connectivity (rsFC) methods to test the nature of this heterogeneity. The automated toolset Neurosynth was used to conduct meta-analyses in order to (a) identify heterogeneous areas in the retrosplenial region (RS region) associated with one or more cognitive domains, and (b) contrast the activation profiles related to these domains. These analyses yielded several functional subregions across the RS region, highlighting differences between anterior RS regions associated with episodic memory and posterior RS regions in the parietal-occipital sulcus associated with scenes and navigation. These regions were subsequently used as seeds to conduct whole brain rsFC analyses using data from the Human Connectome Project. In support of the meta-analysis findings, rsFC revealed divergent connectivity profiles, with anterior regions demonstrating connectivity to the default mode network (DMN) and posterior regions demonstrating connectivity to visual regions. Anterior RS regions and the parietal-occipital sulcus connected to different subnetworks of the DMN. This convergent evidence supports the conclusion that the broad cortical RS region incorporating both anatomical and functional RSC consists of functionally heterogeneous subregions. This study combines two large databases to provide a novel methodological blueprint for understanding brain function in the RS region and beyond. (PsycINFO Database Record (c) 2018 APA, all rights reserved).