bioRxivNeurosciencePreprint
Not Just Noise: Aperiodic Brain Activity Reflects Corticospinal Excitability
Juliana HouglandiD, Miriam KirchhoffiD, Timo van Hattem, J RoschiD, Jing CheniD, Maxim Schaier, Paolo BelardinelliiD, Ulf ZiemanniD
Abstract
BackgroundElectroencephalography (EEG) can be combined with transcranial magnetic stimulation (TMS) to perform brain-state-dependent stimulation. EEG-TMS studies have shown that corticospinal excitability, as measured via motor evoked potentials (MEPs), is modulated by pre-stimulus periodic EEG features, such as sensorimotor mu-rhythm phase and power. However, the influence of aperiodic brain activity on corticospinal excitability is largely unexplored. ObjectivesWe evaluated the relationship between aperiodic and periodic mu-power, aperiodic exponent, and mu-phase on MEP amplitudes using EEG-TMS. MethodsWe applied 800 single TMS pulses to the left primary motor cortex in 78 healthy adults. We calculated aperiodic/periodic mu-power, aperiodic exponent, and mu-phase for each trial from the pre-stimulus C3-Hjorth transformed EEG. MEP amplitudes were extracted from the right first dorsal interosseous muscle. A linear mixed-effects model assessed relationships between MEP amplitudes and EEG features, with interactions between mu-phase and all other EEG features. ResultsAperiodic and periodic mu-power, aperiodic exponent, and mu-phase significantly modulated MEP amplitudes. Higher aperiodic/periodic mu-power was associated with larger MEP amplitudes, while higher aperiodic exponent was associated with smaller MEP amplitudes. We found a significant interaction effect of aperiodic exponent and mu-phase on MEP amplitude. Aperiodic exponent was negatively associated with MEPs for trough, rising, falling phases, but positively associated with MEPs for peak phase. ConclusionsAperiodic and periodic features of brain activity are reflective of dissociable corticospinal excitability states. Future brain-state-dependent TMS interventions may include aperiodic EEG features, such as aperiodic mu-power and exponent, in addition to the well-established periodic features.
- organism: human
- assay: electronic health records
- research focus: cell type annotation
- approach: statistical model
- Citations
- 1
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