Coordinated sleep oscillations between human hippocampal subfields

Poster No:

1079 

Submission Type:

Abstract Submission 

Authors:

Zhipeng Li1, Xia Liang1

Institutions:

1Harbin Institute of Technology, Harbin, Heilongjiang

First Author:

Zhipeng Li  
Harbin Institute of Technology
Harbin, Heilongjiang

Co-Author:

Xia Liang  
Harbin Institute of Technology
Harbin, Heilongjiang

Introduction:

The hippocampus is a heterogeneous brain structure, comprising histologically distinguishable subfields including the dentate gyrus (DG), CA3, CA1, subiculum (SUB). Interactions between these hippocampal subfields play a critical role in memory consolidation[1, 2]. During non-rapid eye movement (NREM) sleep, multiple brain oscillations (e.g., slow wave, spindle and ripple) have been shown to be involved in the computation and distribution of hippocampal information[3, 4]. However, it remains elusive how these oscillations interact to regulate information routing within the local hippocampal circuit. Here, using human intracranial recordings (iEEG), we found that DG/CA3 displays strong cross-frequency coupling (CFC) with CA1 and SUB, but CA1 and SUB show a more precise event-based coupling. We also showed that hippocampal synaptic plasticity, as indexed by delta slope, is modulated by spindle and ripple.

Methods:

We obtained iEEG data from 25 epilepsy patients writing the informed consent, and used pre-MRI and post-CT to locate electrode contacts[5]. NREM was identified by low delta (<2 Hz), spindle (12-16Hz) and high frequency band (70-200Hz) power[6]. Power spectral density (PSD) was calculated by 4 s window Welch method[7], and was normalized. Phase-amplitude coupling (PAC) calculated by mean vector length method was z-standardized to a shuffled distribution[4]. We extracted spindle and ripple events, and used preferred PAC phases to measure the event-based coupling[3]. Then, ripple power was grouped according to the SO-spindle coupling phase to measure the triple coupling of delta-spindle-ripple[8]. Correlation between spindle/ripple and delta slope was calculated by spearman correlations.

Results:

The PSD results revealed high delta and spindle power in all hippocampal subfields (Fig.1A). PAC analysis revealed that DG/CA3 not only exhibited robust within-region delta-ripple and delta-theta coupling (Fig.1B), but also showed strong delta-ripple coupling with the CA1 and SUB (Fig.1C). During PAC analysis, we did not identify any significant delta-spindle or spindle-ripple coupling in any of the four hippocampal subfields[3, 9]. We thus proceeded to examine event-based coupling between the subfields. Interestingly, we found that both delta-spindle and spindle-ripple coupling were evident in CA1 and SUB regions (Fig. 1D and E). Furthermore, our assessment of the relationship between delta-spindle coupling phase and ripple power indicated that the ripple power was significantly modulated by the coupling phase between delta and spindle in the CA1 (Fig. 1F), suggesting triple coordination among the delta, spindle and ripple oscillations in this subfield.
Prior studies have demonstrated that synaptic plasticity could be reflected in the alteration of slow wave slope[10]. We therefore measured the delta slope in each hippocampal subfield (Fig1G) and evaluated its changes as a function of the spindle or ripple power. The results demonstrated a significant correlation between delta slope and spindle power across all hippocampal subfields (Fig1.H). In contrast, ripple affects the delta slope only at the maximum power (Fig1.I, top), which is where the ripple event occurs (Fig1.I, bottom).
Supporting Image: Coordinatedsleeposcillationsbetweenhumanhippocampalsubfields.png
 

Conclusions:

Our findings suggest that the different hippocampal subfields may play different but complementing role in regulating information during NREM sleep. Specifically, DG/CA3 region communicated globally with CA1 and SUB through delta-ripple coupling, while CA1 and SUB exhibited local event-based coupling, presumably to enable further processing and transmission of critical information. Furthermore, the spindle and ripple functioned at different temporal scales to regulate the delta slope, which could reflect important synaptic changes within hippocampus. Overall, these findings provide valuable insights into the circuitry of the hippocampus during NREM sleep and enhance our understanding of how it facilitates memory consolidation.

Learning and Memory:

Long-Term Memory (Episodic and Semantic) 1

Modeling and Analysis Methods:

Other Methods 2

Neuroanatomy, Physiology, Metabolism and Neurotransmission:

Subcortical Structures

Keywords:

Memory
Other - Electrophysiology; Hippocampal subregions; Cross-frequency coupling; Synaptic regulation; Non-rapid eye movement sleep

1|2Indicates the priority used for review

Provide references using author date format

1. Mizuseki, K. and T. Kitanishi (2022), 'Oscillation-coordinated, noise-resistant information distribution via the subiculum', Curr Opin Neurobiol, vol. 75, no. pp. 102556.
2. Hainmueller, T. and M. Bartos (2020), 'Dentate gyrus circuits for encoding, retrieval and discrimination of episodic memories', Nature reviews. Neuroscience, vol. 21, no. 3, pp. 153-168.
3. Staresina, B. P., et al. (2015), 'Hierarchical nesting of slow oscillations, spindles and ripples in the human hippocampus during sleep', Nat Neurosci, vol. 18, no. 11, pp. 1679-1686.
4. Cox, R., et al. (2019), 'Heterogeneous profiles of coupled sleep oscillations in human hippocampus', Neuroimage, vol. 202, no. pp. 116178.
5. Stolk, A., et al. (2018), 'Integrated analysis of anatomical and electrophysiological human intracranial data', Nat Protoc, vol. 13, no. 7, pp. 1699-1723.
6. Jiang, X., et al. (2017), 'Replay of large-scale spatio-temporal patterns from waking during subsequent NREM sleep in human cortex', Sci Rep, vol. 7, no. 1, pp. 17380.
7. Vijayan, S., et al. (2017), 'Frontal beta-theta network during REM sleep', Elife, vol. 6, no. pp.
8. Helfrich, R. F., et al. (2019), 'Bidirectional prefrontal-hippocampal dynamics organize information transfer during sleep in humans', Nat Commun, vol. 10, no. 1, pp. 3572.
9. Girardeau, G. and V. Lopes-Dos-Santos (2021), 'Brain neural patterns and the memory function of sleep', Science, vol. 374, no. 6567, pp. 560-564.
10. Kurth, S., et al. (2010), 'Characteristics of sleep slow waves in children and adolescents', Sleep, vol. 33, no. 4, pp. 475-480.