Spiral waves of sleep spindles predict overnight memory consolidation and age-related memory decline
Poster No:
843
Submission Type:
Abstract Submission
Authors:
Yiben Xu1, Alexander McInnes1, Chien-Hui Kao2, Angela D'Rozario2, JianFeng Feng3, Pulin Gong1
Institutions:
1School of Physics, University of Sydney, Sydney, New South Wales, 2Centre for Sleep and Chronobiology, Woolcock Institute of Medical Research, Macquarie University, Sydney, New South Wales, 3Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
First Author:
Co-Author(s):
Chien-Hui Kao
Centre for Sleep and Chronobiology, Woolcock Institute of Medical Research, Macquarie University
Sydney, New South Wales
Centre for Sleep and Chronobiology, Woolcock Institute of Medical Research, Macquarie University
Sydney, New South Wales
Angela D'Rozario
Centre for Sleep and Chronobiology, Woolcock Institute of Medical Research, Macquarie University
Sydney, New South Wales
Centre for Sleep and Chronobiology, Woolcock Institute of Medical Research, Macquarie University
Sydney, New South Wales
JianFeng Feng
Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University
Shanghai, China
Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University
Shanghai, China
Introduction:
Recent studies have revealed that spindle oscillations, a neural hallmark of stage 2 non-rapid-eye-movement (NREM, N2) sleep, are spatiotemporally organized as propagating waves (Muller et al., 2016; Townsend and Gong, 2018). However, the organizational principles governing the spatiotemporal dynamics of sleep spindle wave patterns and their functional role remain unclear.
In this study, we analyse 256-channel electroencephalogram (EEG) recordings from patients with obstructive sleep apnea (OSA) during stage 2 NREM (N2) sleep to investigate the organizational role of N2 spiral wave patterns in spindle dynamics and their functional relevance to sleep-dependent memory consolidation and aging-related decline of memory function.
In this study, we analyse 256-channel electroencephalogram (EEG) recordings from patients with obstructive sleep apnea (OSA) during stage 2 NREM (N2) sleep to investigate the organizational role of N2 spiral wave patterns in spindle dynamics and their functional relevance to sleep-dependent memory consolidation and aging-related decline of memory function.
Methods:
Experimental design and data pre-processing
We investigate the overnight EEG recordings of nine male participants (age: 50.4 ± 6.5 years, apnea-hypopnea index/AHI: 51.7 ± 23.5/h, mean ± s.d., n = 9) with moderate-severe obstructive sleep apnea (OSA, AHI > 15). As detailed in a recent study (D'Rozario et al., 2023), the participants underwent two sessions of overnight polysomnography with 256-channel EEG before and after 3 months of Continuous positive airway pressure (CPAP) therapy. A 32-word pair association test was conducted before and after sleep in both sessions.
We focus exclusively on the NREM stage 2 (N2) given the prominence of sleep spindles (11-15 Hz). Spindle epochs are detected via an automatic detection algorithm based on temporally filtered EEG signals at 11-15Hz.
Detection of spiral wave patterns
As detailed in our recent study (Xu et al., 2023), we detect spiral wave patterns based on the curl of phase velocity fields (Fig. 1).
We investigate the overnight EEG recordings of nine male participants (age: 50.4 ± 6.5 years, apnea-hypopnea index/AHI: 51.7 ± 23.5/h, mean ± s.d., n = 9) with moderate-severe obstructive sleep apnea (OSA, AHI > 15). As detailed in a recent study (D'Rozario et al., 2023), the participants underwent two sessions of overnight polysomnography with 256-channel EEG before and after 3 months of Continuous positive airway pressure (CPAP) therapy. A 32-word pair association test was conducted before and after sleep in both sessions.
We focus exclusively on the NREM stage 2 (N2) given the prominence of sleep spindles (11-15 Hz). Spindle epochs are detected via an automatic detection algorithm based on temporally filtered EEG signals at 11-15Hz.
Detection of spiral wave patterns
As detailed in our recent study (Xu et al., 2023), we detect spiral wave patterns based on the curl of phase velocity fields (Fig. 1).
·Fig. 1. Detection of spiral wave patterns based on moment-by-moment high-density EEG signals. (A) Three-dimensional representation of 256 electrodes (left) and their two-dimensional projections (right
Results:
Consistency in spiral trajectories predicts memory retention performance
As illustrated in Fig. 2A, long-term consistency of spiral distribution is significantly and positively correlated with memory retention performance averaged across baseline and treatment conditions, as measured by the changes in recall performance after sleep.
CPAP therapy improves spiral short-term consistency
As shown in Fig. 2B, we find significant increases in the short-term consistency of spiral distributions following the CPAP therapy. On the other hand, we observe no significant change in memory retention following the CPAP treatment, suggesting further investigations are required to uncover the functional impact of increased spiral short-term consistency.
Aging-related decline of spiral long-term consistency
As demonstrated in Fig. 2C, we observe a significant negative correlation between age and spiral long-term consistency, indicating that older individuals are more likely to exhibit a decline in spiral long-term consistency.
Spindle consistency enhanced by N2 spirals predicts improved memory retention
As shown in Fig. 2D, we observe a significant increase in spindle event consistency in the presence of N2 spirals compared to their absence. Moreover, we observe a significant correlation between the consistency of spindle events and memory retention performance in the presence of N2 spirals (Fig. 2E). Additionally, we observe significant negative correlations between spindle consistency and subjects' age in the presence of N2 spirals (Fig. 2F).
As illustrated in Fig. 2A, long-term consistency of spiral distribution is significantly and positively correlated with memory retention performance averaged across baseline and treatment conditions, as measured by the changes in recall performance after sleep.
CPAP therapy improves spiral short-term consistency
As shown in Fig. 2B, we find significant increases in the short-term consistency of spiral distributions following the CPAP therapy. On the other hand, we observe no significant change in memory retention following the CPAP treatment, suggesting further investigations are required to uncover the functional impact of increased spiral short-term consistency.
Aging-related decline of spiral long-term consistency
As demonstrated in Fig. 2C, we observe a significant negative correlation between age and spiral long-term consistency, indicating that older individuals are more likely to exhibit a decline in spiral long-term consistency.
Spindle consistency enhanced by N2 spirals predicts improved memory retention
As shown in Fig. 2D, we observe a significant increase in spindle event consistency in the presence of N2 spirals compared to their absence. Moreover, we observe a significant correlation between the consistency of spindle events and memory retention performance in the presence of N2 spirals (Fig. 2E). Additionally, we observe significant negative correlations between spindle consistency and subjects' age in the presence of N2 spirals (Fig. 2F).
·Fig. 2. Consistency of spirals and spindles predict memory retention performance and are related to aging. (A) Linear regression showing subject-level spiral long-term consistency against baseline-tre
Conclusions:
In summary, we observe the abundant presence of spiral wave patterns whose locations remain surprisingly consistent across a three-month period. Crucially, such consistency accurately predicts the patients' memory retention performance and is significantly reduced in older patients. Additionally, we reveal the significant increase of spindle consistency in the presence of spiral waves, which also predicts better memory retention performance and declines with aging. These results thus provide a novel perspective on the neural mechanisms underlying sleep-dependent memory consolidation and the aging-related decline in memory function.
Learning and Memory:
Long-Term Memory (Episodic and Semantic) 1
Lifespan Development:
Aging
Modeling and Analysis Methods:
EEG/MEG Modeling and Analysis 2
Novel Imaging Acquisition Methods:
EEG
Keywords:
Aging
Data analysis
Electroencephaolography (EEG)
Memory
Plasticity
Sleep
Therapy
1|2Indicates the priority used for review
Abstract Information
By submitting your proposal, you grant permission for the Organization for Human Brain Mapping (OHBM) to distribute your work in any format, including video, audio print and electronic text through OHBM OnDemand, social media channels, the OHBM website, or other electronic publications and media.
The Open Science Special Interest Group (OSSIG) is introducing a reproducibility challenge for OHBM 2025. This new initiative aims to enhance the reproducibility of scientific results and foster collaborations between labs. Teams will consist of a “source” party and a “reproducing” party, and will be evaluated on the success of their replication, the openness of the source work, and additional deliverables. Click here for more information. Propose your OHBM abstract(s) as source work for future OHBM meetings by selecting one of the following options:
Please indicate below if your study was a "resting state" or "task-activation” study.
Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
Was this research conducted in the United States?
Were any human subjects research approved by the relevant Institutional Review Board or ethics panel? NOTE: Any human subjects studies without IRB approval will be automatically rejected.
Were any animal research approved by the relevant IACUC or other animal research panel? NOTE: Any animal studies without IACUC approval will be automatically rejected.
Please indicate which methods were used in your research:
Provide references using APA citation style.
Muller, L. (2016). Rotating waves during human sleep spindles organize global patterns of activity that repeat precisely through the night. eLife, 5, e17267.
Townsend, R.G. (2018). Detection and analysis of spatiotemporal patterns in brain activity. PLoS Comput. Biol. 14, e1006643.
Xu, Y. (2023). Interacting spiral wave patterns underlie complex brain dynamics and are related to cognitive processing. Nat. Hum. Behav. 7, 1196-1215.