0069 Sleep Efficiency and Memory-Related Brain Functional Connectivity

Abstract Introduction Sleep plays a critical role in memory consolidation, yet the impact of chronic sleep deficiency on functional connectivity (FC) in key memory-related regions, such as the hippocampus (HPC) and posterior cingulate cortex (PCC), remains unclear. Traditional BOLD fMRI suffers from signal dropout near air-tissue interfaces, limiting its ability to reliably assess FC in the HPC. Dynamic arterial spin labeling (DASL) offers a potential solution by providing more robust perfusion-based measures of FC. In this preliminary study, we examine how sleep efficiency relates to HPC and PCC FC using both BOLD and DASL imaging. Methods Fourteen patients (60±16 years; 8 females) who underwent clinical polysomnography (PSG) were recruited, and sleep efficiency was scored by certified technicians. MRI data were acquired on a 3T Siemens Prisma and included a 5-minute BOLD scan, a 5-minute DASL scan using background-suppressed pseudo-continuous arterial spin labeling (PCASL), and a high-resolution T1-weighted structural image. Seed-based FC for the PCC and left HPC (LHPC) was calculated using voxel-wise Pearson correlations followed by Fisher z-transformation. Associations between sleep efficiency and FC were assessed using multiple linear regression with ANCOVA controlling for global signals, along with correction applied for multiple comparisons. Results Sleep efficiency was significantly associated with FC in both the PCC and LHPC. Using BOLD, higher sleep efficiency was associated with increased PCC FC in the anterior cingulate and medial orbitofrontal cortex, regions within the default mode network (DMN). Using DASL, higher sleep efficiency was associated with increased PCC FC in the left insula, a key node of the salience network (SN), as well as increased LHPC FC in the right supramarginal and superior temporal region, which are components of the DMN. Conclusion Higher sleep efficiency was associated stronger FC between memory-related regions and major large-scale networks, including the DMN and SN. These findings suggest that reduced sleep efficiency may disrupt network-level connectivity patterns supporting memory and attention. Such disruptions may contribute to the neural mechanisms linking poor sleep to impaired memory consolidation and increased vulnerability to memory decline and dementia. Future work will integrate automating sleep-efficiency estimation into our modeling framework. Support (if any) Transdisciplinary Areas of Excellence seed grant at Binghamton University