Trunk, B. H. | bioRxiv Science

bioRxiv2024

Brain signal complexity and aperiodicity predict human corticospinal excitability

BackgroundTranscranial magnetic stimulation (TMS) holds promise for brain modulation with relevant scientific and therapeutic applications, but it is limited by response variability. Targeting state-dependent EEG features such as phase and power shows potential, but uncertainty remains about the suitable brain states. ObjectiveThis study evaluated broadband EEG measures (BEMs), including the aperiodic exponent (AE) and entropy measures (CTW, LZ), as alternatives to band-limited features, such as power and phase, for predicting corticospinal excitability (CSE). MethodsTMS was delivered with randomly applied single pulses targeting the left primary motor cortex in 34 healthy participants while simultaneously recording EEG and EMG signals. Broadband and band-limited EEG features were evaluated for their ability to predict CSE using motor evoked potentials (MEPs) from the right extensor digitorum communis muscle as the outcome measure. ResultsBEMs (AE, CTW) significantly predicted CSE, comparable to beta-band power and phase, the most predictive and spatially specific band-limited markers of motor cortex CSE. Unlike these localized CSE markers at the site of stimulation, BEMs captured more global brain states and greater within-subject variability, indicating sensitivity to dynamic state changes. Notably, CTW was associated with high CSE, while AE was linked to low CSE. ConclusionThis study reveals BEMs as robust predictors of CSE that circumvent challenges of band-limited EEG features, such as narrowband filtering and phase estimation. They may reflect more general markers of brain excitability. With their slower timescale and broader sensitivity, BEMs are promising biomarkers for state-dependent TMS applications, particularly in therapeutic contexts.

neuroscience↗

bioRxiv2023

Phase-specific stimulation reveals consistent sinusoidal modulation of human corticospinal excitability along the oscillatory beta cycle

The responsiveness of neuronal populations to incoming information fluctuates. Retrospective analyses of randomly applied stimuli reveal a neural input-output relationship along the intrinsic oscillatory cycle. Prospectively harnessing this biological mechanism would necessitate frequency- and phase-specificity, intra- and inter-individual consistency, and instantaneous access to the oscillatory cycle. We used a novel real-time approach to electroencephalography-triggered transcranial magnetic stimulation to precisely target 8 equidistant phases of the oscillatory cycle in the human motor cortex of male and female healthy participants. The phase-dependency of corticospinal excitability was investigated in ten different intrinsic frequencies (4, 8, 12, 16, 20, 24, 28, 32, 36, and 40Hz) and indexed by motor-evoked potentials (MEP) in the corresponding forearm muscle. On both the individual and group level, we detected a consistent sinusoidal MEP modulation along the oscillatory cycle at 24Hz ({chi}22 =9.2, p=.01), but not at any other target frequency (all {chi}22 <5, all p>.08). Moreover, cross-validations showed also at 24Hz the highest consistency of the optimal phase between prospective (real-time) and retrospective (out-of-sample) testing (r=.605, p<.001), and across experimental sessions on three different days (r[≥].45). The optimal corticospinal signal transmission was at the transition from the trough to the rising flank of the oscillatory 24Hz cycle. Integrating real-time measurement and brain stimulation revealed that the sinusoidal input-output relationship of corticospinal signal transmission is frequency- and phase specific, and consistent within and across individuals and sessions. In future, this approach allows to selectively and repetitively target windows of increased responsiveness, and to thereby investigate potential cumulative effects on plasticity induction.

neuroscience↗