Aperiodic EEG Slope Tracks Cortical Excitability More Closely Than Rhythmic Power
Aperiodic neural activity may be doing more than passively reflecting the brain’s electrical background. In a new preprint from bioRxiv, aperiodic exponent measured before stimulation showed a strong negative relationship with cortical excitability in two distinct cortical targets during TMS-EEG: the primary motor cortex and the dorsolateral prefrontal cortex.
The finding is clinically interesting because it points away from a narrow focus on oscillatory bands alone. For years, alpha and beta rhythms have dominated discussions of state-dependent brain stimulation, partly because they are easy to quantify and biologically intuitive. This study argues that the broader 1/f-like structure of spontaneous EEG may be a more faithful marker of how strongly a cortex will respond when probed with transcranial magnetic stimulation.
A steeper aperiodic slope was associated with smaller early TMS-evoked potentials. In bedside terms, the cortex looked less excitable when the background signal leaned more heavily toward higher-frequency attenuation in the 1/f profile.
What Was Tested Across Motor and Prefrontal Cortex
Investigators delivered single-pulse TMS to the left motor cortex in 29 healthy adults and to the left dorsolateral prefrontal cortex in 11 healthy adults. EEG was recorded simultaneously, allowing the pre-stimulus signal to be separated into aperiodic and periodic components. The analysis extracted the aperiodic exponent, alpha power in the 8–13 Hz range, and beta power in the 13–30 Hz range.
The readout of interest was the early local TMS-evoked potential, or EL-TEP, measured as a peak-to-peak amplitude from roughly 20 to 65 milliseconds after the pulse. That window is important because it captures the immediate local cortical response rather than later network-level reverberations. In practical neurophysiology, this is the moment when a stimulated cortex either answers back briskly or barely reacts at all.
The same basic pattern emerged in both cortical regions. Larger aperiodic exponent values tracked with smaller EL-TEP amplitudes. The relationship was described as strong and negative, and it appeared in both the motor and prefrontal experiments.
Why the 1/f Signal May Be a Better State Marker
The aperiodic exponent is often interpreted as a summary of excitation-inhibition balance, synaptic activity, and overall background network dynamics. A steeper slope has been linked conceptually to a cortex with less readily available excitability, though the exact biological meaning remains an inference rather than a direct measurement. Even so, the direction of the association makes physiological sense: if the baseline neural milieu is already tilted toward reduced responsiveness, an external perturbation should evoke a smaller local volley.
This is where the study becomes more than a technical exercise. TMS-EEG is increasingly used to probe brain state in a way that can be adapted for closed-loop protocols. If the aperiodic exponent consistently indexes cortical responsiveness, then stimulation could be timed to moments when the target cortex is most receptive, rather than firing pulses into a relatively quiescent state. That could matter for both experimental precision and future therapeutic stimulation strategies.
The result also fits with a broader shift in systems neuroscience. Instead of treating the EEG as a collection of independent rhythms, the field is beginning to examine the full spectral architecture of neural activity. The aperiodic component may capture a baseline property of the cortex that periodic alpha or beta power only partially reflects.
Alpha and Beta Power Were Less Consistent
Periodic activity did not behave with the same reliability. Relationships between alpha power or beta power and EL-TEP amplitude were inconsistent across the two regions. In one cortical target, rhythmic power may have related to excitability in one direction; in the other, the pattern did not hold with the same clarity.
That inconsistency matters because it limits the appeal of using a single oscillatory band as a universal proxy for brain state. Alpha and beta power remain important physiological signals, but this dataset suggests they are not the most stable predictors of how the cortex will respond to a single magnetic pulse across different brain regions.
The contrast is sharp. Aperiodic slope was the more dependable predictor; alpha and beta were not.
Implications for Closed-Loop Brain Stimulation
The authors argue that brain-state-dependent protocols may benefit from real-time extraction of the aperiodic exponent. That proposal is straightforward in concept but technically demanding in practice. Real-time EEG processing must estimate the 1/f component quickly and cleanly enough to guide stimulation timing without disrupting the workflow of the experiment or clinic.
If that hurdle can be cleared, the payoff could be meaningful. TMS protocols designed around ongoing cortical state may achieve more reproducible responses, especially when the objective is to drive plasticity or test causal brain function. In disorders where responsiveness to stimulation varies widely from one moment to the next, a better biomarker of excitability could help reduce trial-to-trial noise.
The study does not claim that aperiodic activity is the only determinant of excitability, and it does not resolve the underlying mechanism. Healthy adults were studied, and the sample in the prefrontal cortex arm was small. Still, the pattern was coherent enough to raise a serious mechanistic question: whether the 1/f slope is not just background noise, but a state variable that helps set the gain of cortical tissue before stimulation arrives.
A Preprint That Reorients the Excitability Question
Because this is a preprint, the findings remain preliminary and should be read with that caution in mind. Even so, the signal is notable: aperiodic neural activity predicted cortical excitability in two anatomically and functionally different regions, while standard oscillatory metrics were less reliable.
For TMS-EEG research, that shifts attention toward a richer spectral biomarker. The early cortical response may be governed less by whether alpha or beta happens to be high at a given moment and more by the broader spectral tilt of the resting cortex itself. Future work will need to test whether the same relationship holds across larger cohorts, across additional cortical sites, and in patient populations where excitability is altered by disease or medication. The current dataset stops short of those questions, but it establishes a concrete starting point: the aperiodic exponent deserves a place in the real-time physiology of brain stimulation.