A Whole-Brain Model of the Aging Brain During Slow Wave Sleep

Overview

Journal eNeuro

Specialty Neurology

Date 2024 Oct 15

PMID 39406483

Authors

Eleonora Lupi

Gabriele Di Antonio

Marianna Angiolelli

Maria Sacha

Mehmet Alihan Kayabas

Nicola Albore

Riccardo Leone

Karim El Kanbi

Alain Destexhe

Jan Fousek

Affiliations

Soon will be listed here.

Abstract

Age-related brain changes affect sleep and are reflected in properties of sleep slow-waves, however, the precise mechanisms behind these changes are still not completely understood. Here, we adapt a previously established whole-brain model relating structural connectivity changes to resting state dynamics, and extend it to a slow-wave sleep brain state. In particular, starting from a representative connectome at the beginning of the aging trajectory, we have gradually reduced the inter-hemispheric connections, and simulated sleep-like slow-wave activity. We show that the main empirically observed trends, namely a decrease in duration and increase in variability of the slow waves are captured by the model. Furthermore, comparing the simulated EEG activity to the source signals, we suggest that the empirically observed decrease in amplitude of the slow waves is caused by the decrease in synchrony between brain regions.

References

Ghosh A, Rho Y, McIntosh A, Kotter R, Jirsa V . Noise during rest enables the exploration of the brain's dynamic repertoire. PLoS Comput Biol. 2008; 4(10):e1000196. PMC: 2551736. DOI: 10.1371/journal.pcbi.1000196. View

Piantoni G, Poil S, Linkenkaer-Hansen K, Verweij I, Ramautar J, van Someren E . Individual differences in white matter diffusion affect sleep oscillations. J Neurosci. 2013; 33(1):227-33. PMC: 6618630. DOI: 10.1523/JNEUROSCI.2030-12.2013. View

Goldman J, Kusch L, Aquilue D, Yalcinkaya B, Depannemaecker D, Ancourt K . A comprehensive neural simulation of slow-wave sleep and highly responsive wakefulness dynamics. Front Comput Neurosci. 2023; 16:1058957. PMC: 9880280. DOI: 10.3389/fncom.2022.1058957. View

Giorgio A, Santelli L, Tomassini V, Bosnell R, Smith S, De Stefano N . Age-related changes in grey and white matter structure throughout adulthood. Neuroimage. 2010; 51(3):943-51. PMC: 2896477. DOI: 10.1016/j.neuroimage.2010.03.004. View

Caspers S, Moebus S, Lux S, Pundt N, Schutz H, Muhleisen T . Studying variability in human brain aging in a population-based German cohort-rationale and design of 1000BRAINS. Front Aging Neurosci. 2014; 6:149. PMC: 4094912. DOI: 10.3389/fnagi.2014.00149. View

Buchmann A, Kurth S, Ringli M, Geiger A, Jenni O, Huber R . Anatomical markers of sleep slow wave activity derived from structural magnetic resonance images. J Sleep Res. 2011; 20(4):506-13. DOI: 10.1111/j.1365-2869.2011.00916.x. View

Staresina B, Niediek J, Borger V, Surges R, Mormann F . How coupled slow oscillations, spindles and ripples coordinate neuronal processing and communication during human sleep. Nat Neurosci. 2023; 26(8):1429-1437. PMC: 10400429. DOI: 10.1038/s41593-023-01381-w. View

Romanella S, Roe D, Tatti E, Cappon D, Paciorek R, Testani E . The Sleep Side of Aging and Alzheimer's Disease. Sleep Med. 2020; 77:209-225. PMC: 8364256. DOI: 10.1016/j.sleep.2020.05.029. View

Deco G, Corbetta M . The dynamical balance of the brain at rest. Neuroscientist. 2011; 17(1):107-23. PMC: 4139497. DOI: 10.1177/1073858409354384. View

10.

Brette R, Gerstner W . Adaptive exponential integrate-and-fire model as an effective description of neuronal activity. J Neurophysiol. 2005; 94(5):3637-42. DOI: 10.1152/jn.00686.2005. View

11.

Mattia M, Del Giudice P . Population dynamics of interacting spiking neurons. Phys Rev E Stat Nonlin Soft Matter Phys. 2003; 66(5 Pt 1):051917. DOI: 10.1103/PhysRevE.66.051917. View

12.

Petkoski S, Ritter P, Jirsa V . White-matter degradation and dynamical compensation support age-related functional alterations in human brain. Cereb Cortex. 2023; 33(10):6241-6256. PMC: 10183745. DOI: 10.1093/cercor/bhac500. View

13.

Spiegler A, Karimi Abadchi J, Mohajerani M, Jirsa V . In silico exploration of mouse brain dynamics by focal stimulation reflects the organization of functional networks and sensory processing. Netw Neurosci. 2021; 4(3):807-851. PMC: 7888484. DOI: 10.1162/netn_a_00152. View

14.

Alexandersen C, de Haan W, Bick C, Goriely A . A multi-scale model explains oscillatory slowing and neuronal hyperactivity in Alzheimer's disease. J R Soc Interface. 2023; 20(198):20220607. PMC: 9810432. DOI: 10.1098/rsif.2022.0607. View

15.

Tatulian S . Challenges and hopes for Alzheimer's disease. Drug Discov Today. 2022; 27(4):1027-1043. DOI: 10.1016/j.drudis.2022.01.016. View

16.

Schilling K, Archer D, Yeh F, Rheault F, Cai L, Hansen C . Aging and white matter microstructure and macrostructure: a longitudinal multi-site diffusion MRI study of 1218 participants. Brain Struct Funct. 2022; 227(6):2111-2125. PMC: 9648053. DOI: 10.1007/s00429-022-02503-z. View

17.

Abbott , van Vreeswijk C . Asynchronous states in networks of pulse-coupled oscillators. Phys Rev E Stat Phys Plasmas Fluids Relat Interdiscip Topics. 1993; 48(2):1483-1490. DOI: 10.1103/physreve.48.1483. View

18.

Lavanga M, Stumme J, Yalcinkaya B, Fousek J, Jockwitz C, Sheheitli H . The virtual aging brain: Causal inference supports interhemispheric dedifferentiation in healthy aging. Neuroimage. 2023; 283:120403. DOI: 10.1016/j.neuroimage.2023.120403. View

19.

Sanz-Leon P, Knock S, Spiegler A, Jirsa V . Mathematical framework for large-scale brain network modeling in The Virtual Brain. Neuroimage. 2015; 111:385-430. DOI: 10.1016/j.neuroimage.2015.01.002. View

20.

Van Cauter E, Leproult R, Plat L . Age-related changes in slow wave sleep and REM sleep and relationship with growth hormone and cortisol levels in healthy men. JAMA. 2000; 284(7):861-8. DOI: 10.1001/jama.284.7.861. View