Poster Session E, Monday, March 25, 2:30 – 4:30 pm, Pacific Concourse
Dynamic Functional Connectivity Measures Fail to Predict “Real World” Classroom Learning
Adam Weinberger1, Robert Cortes1, Adam Green1; 1Georgetown University
Learning is a complex process of adaptation, adjustment, and regulative change. In recent years, dynamic functional connectivity analyses have been used to examine brief changes in patterns of connectivity. Because the brain exists in a constant state of reconfigurations – and how and when these reconfigurations take place are likely to have behavioral ramifications – some have hypothesized that dynamic, short-term modulations of functional connectivity may be used to predict and assess learning. Notably, the majority of research within this burgeoning field has examined learning over short periods of time following brief training periods conducted in the laboratory environment. Thus, it is currently unknown whether dynamic functional connectivity can be used to better understand “real world” and/or classroom-based learning. Here, we recruited a group of high school students before and after participation in a year-long high school course (the GeoSpatial Semester; GSS) designed to build spatial thinking and project management skills through the use of geospatial technology. Students came to Georgetown University to complete an fMRI scanning session before and after the course. Dynamic functional connectivity metrics were calculated at rest and as students completed a number of spatially-based tasks. In contrast to the current literature, dynamic functional connectivity metrics were not able to effectively predict learning during the year-long course.
Topic Area: THINKING: Reasoning