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Brain Waves

Brain Waves

Brain waves are electrical signals generated by the neurons in the brain, which are regularly monitored to measure mental activities. Brain waves and their frequency ranges can be measured using an electroencephalogram or EEG. There are four main types of brain waves, each with distinct characteristics:

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Slow wave canonical activity deviation concept: Toward a slow wave-based EEG-fMRI reference map for health-associated

Merve Ilhan-Bayrakcı¹, Oliver Tüscher^1,2,3,4,5, Albrecht Stroh^1,6

¹Leibniz Institute for Resilience Research, Mainz, Germany.

|April 20, 2026

Summary

This study introduces a novel method using slow wave events (SWEs) from EEG-fMRI to map brain activity. This approach enhances the detection of early neural network dysfunction for identifying individuals at risk for neurological conditions.

Keywords:

behavioral neuroscience cognitive neuroscience neuroscience sensory neuroscience techniques in neuroscience

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Area of Science:

Neuroscience
Neuroimaging
Computational Neuroscience

Background:

Individual variations in brain functional networks challenge neuroimaging's sensitivity for detecting early maladaptations.
Slow wave events (SWEs) are neurophysiological markers influenced by neural excitability and network states, impacting their spatiotemporal dynamics.

Purpose of the Study:

To enhance neuroimaging sensitivity by integrating EEG-informed fMRI analyses using SWEs.
To develop reference maps of SWE-related brain activity and stratify these based on SWE synchronization efficiency.
To introduce the Slow Wave Canonical Activity Deviation (SloCAD) concept for quantifying individual deviations from typical SWE activation patterns.

Main Methods:

Simultaneous EEG-fMRI data from two healthy cohorts (N=24) were analyzed.
Individual SWE-related Blood-Oxygen-Level-Dependent (BOLD) maps were generated.
Cohort-level probabilistic maps and reference maps were created, with SWEs stratified by synchronization efficiency.

Main Results:

Consistently engaged regions, including the cingulate cortex, thalamus, hippocampus, and cerebellum, were identified in reference maps.
High synchronization SWEs engaged widespread cortical and subcortical networks.
Low-synchronization SWEs predominantly engaged posterior cortical regions, refining reference maps for distinct SWE subtypes.

Conclusions:

SWEs can serve as sensitive neurophysiological markers in EEG-fMRI for mapping brain activity.
Stratification of SWEs by synchronization efficiency reveals distinct BOLD patterns, enabling refined reference maps.
The proposed SloCAD concept offers a foundation for studying early network dysfunction in pathological conditions.