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Alterations in rhythmic and non-rhythmic resting-state EEG activity and their link to cognition in older age

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Cesnaite,  Elena       
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Steinfath,  Tim Paul       
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Jamshidi Idaji,  Mina       
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Stephani,  Tilman       
International Max Planck Research School on Neuroscience of Communication: Function, Structure, and Plasticity, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Kumral,  Deniz       
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Schroeter,  Matthias L.
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Witte,  A. Veronica       
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Villringer,  Arno       
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Nikulin,  Vadim V.       
Department Neurology, MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Citation

Cesnaite, E., Steinfath, T. P., Jamshidi Idaji, M., Stephani, T., Kumral, D., Haufe, S., et al. (2021). Alterations in rhythmic and non-rhythmic resting-state EEG activity and their link to cognition in older age. bioRxiv. doi:10.1101/2021.08.26.457768.


Cite as: https://hdl.handle.net/21.11116/0000-000B-1B79-0
Abstract
While many structural and biochemical changes in the brain have been previously associated with aging, the findings concerning electrophysiological signatures, reflecting functional properties of neuronal networks, remain rather controversial. To try resolve this issue, we took advantage of a large population study (N=1703) and comprehensively investigated the association of multiple EEG biomarkers (power of alpha and theta oscillations, individual alpha peak frequency (IAF), the slope of 1/f power spectral decay), aging, and aging and cognitive performance. Cognitive performance was captured with three factors representing processing speed, episodic memory, and interference resolution. Our results show that not only did IAF decline with age but it was also associated with interference resolution over multiple cortical areas. To a weaker extent, 1/f slope of the PSD showed age-related reductions, mostly in frontal brain regions. Finally, alpha power was negatively associated with the speed of processing in the right frontal lobe, despite the absence of age-related alterations. Our results thus demonstrate that multiple electrophysiological features, as well as their interplay, should be considered when investigating the association between age, neuronal activity, and cognitive performance.