Large-Scale Brain Networks Underlying Successful and Unsuccessful Encoding, Maintenance, and Retrieval of Everyday Scenes in Visuospatial Working Memory

Front Psychol. 2019 Feb 12;10:233. doi: 10.3389/fpsyg.2019.00233. eCollection 2019.


Recent research on working memory (WM) identified the contribution of several large-scale brain networks operating during WM tasks, such as the frontoparietal attention network (AN), the default mode network (DMN), and the salience network (SN). To date, however, the dynamical interplay among these networks is largely unexplored during successful or unsuccessful WM performance, especially with complex and ecological stimuli. Here we systematically characterized the selective contribution of these networks during a visuospatial WM task requiring the encoding, maintenance and retrieval of real-life scenes. While undergoing fMRI scans, participants were presented with everyday life visual scenes for 4 s (encoding phase). After a delay of 8 s (maintenance phase), participants were presented with a target-object extracted from the previous scene. Participants had to judge whether the target-object was presented at the same or in a different location compared to the original scene (retrieval phase) and then provide a confidence judgment. Using the independent component analysis (ICA), we found that subsequent remembering was associated with the activity of the AN at encoding, the attention and SN at maintenance, plus the visual network at retrieval. Conversely, subsequent forgetting was associated with the activity of the DMN at maintenance, and the SN at retrieval. Overall, these findings reveal a dynamical interplay between large-scale brain networks during visuospatial WM performance related to complex, real-life stimuli.

Keywords: Independent Component Analysis (ICA); default mode; everyday life scenes; frontoparietal; network; salience; working memory.