77: Exploring the Significance of rsEEG Features in Pain Processing by Mapping them to Neurotransmitters

Topic: Basic Science
Subtopic: Non-specific to any diagnosis (including studies in healthy animals), Developing methodology/technology

Background and Aims: Chronic pain has been associated with altered cortical excitation/inhibition (E/I) balance[1]. However, scalable electrophysiological markers of these alterations, validated against independent neurobiological measures, are lacking. Aperiodic EEG features are frequently interpreted as reflecting E/I balance[2], yet evidence for this interpretation is sparse[3]. We leverage a large EEG dataset and PET-derived neurotransmitter receptor/transporter distributions(NT) from the neuromaps toolbox[4] to test whether spatial variation in EEG features, including aperiodic activity, aligns with neurochemical gradients. We quantify feature-wise EEG-NT associations and test joint glutamatergic and GABAergic contributions to aperiodic EEG variation, providing a foundation for non-invasive E/I assessment in chronic pain.

Methods: We analyze 1,037 eyes-closed resting-state EEG recordings (≥3 min) from healthy participants. Power spectra are computed and parameterized with specparam to separate aperiodic from oscillatory activity. We derive 18 EEG features and perform source reconstruction to the Schaefer-100 atlas; age and sex effects are regressed out. Neurochemical maps (n=19 receptor/transporter distributions) are obtained via the neuromaps toolbox. Spatial correspondence between each EEG feature map and each NT map is tested against spin or subject-generated null models. For E/I hypothesis testing, we combine single-subject and group-average approaches and fit Bayesian multiple linear models focused on NMDA, GABA, and mGluR5.

Results: Analyses will determine which EEG features (aperiodic 1/f metrics, band power, frequency-resolved network node strength, and PAF) show robust spatial correspondence with the 19 NT distributions under spin-test inference. We will evaluate specificity across NT systems and EEG features, and test whether a multivariate glutamatergic/ GABAergic model (NMDA, GABA, mGluR5) explains unique variance in EEG maps beyond single-NT associations. Bayesian statistics will be used for effect estimation and quantifying evidence when possible.

Conclusions: This exploratory, large-scale mapping study tests whether widely used resting-state EEG markers show neurochemically plausible spatial organisation. By combining 1,037 EEG recordings with neuromaps-derived receptor/transporter distributions (19 NT systems), we provide a broad screen of EEG–NT correspondences and a focused E/I test using multivariate glutamatergic (NMDA, mGluR5) and GABAergic predictors. Even in the absence of causal inference, identifying consistent and specific EEG–NT alignments could substantially strengthen the mechanistic interpretation of EEG biomarkers and inform target selection for translational pain research, patient stratification, and neuromodulation studies.

References: 1- Peirs, C., Williams, S. P. G., Zhao, X., Walsh, C. E., Gedeon, J. Y., Cagle, N. E., ... & Seal, R. P. (2015). Dorsal horn circuits for persistent mechanical pain. Neuron, 87(4), 797-812.
2- Gao, R., Peterson E.J., Voytek B., 2017. Inferring synaptic excitation/inhibition balance from field potentials. Neuroimage, 158, 70-8.
3- Ahmad, J., Ellis C., Leech R., Voytek B., Garces P., Jones E., Buitelaar J., Loth E., Dos Santos F.P., Amil A.F., Verschure P., Murphy D., McAlonan G., 2022. From mechanisms to markers: novel noninvasive EEG proxy markers of the neural excitation and inhibition system in humans. Transl Psychiatry, 12, 467.
4- Markello, R. D., Hansen, J. Y., Liu, Z. Q., Bazinet, V., Shafiei, G., Suárez, L. E., ... & Misic, B. (2022). Neuromaps: structural and functional interpretation of brain maps. Nature Methods, 19(11), 1472-1479.

Presenting Author: Nicolò Bruna
Submitting Author: Nicolò Bruna

Senior Author: Markus Ploner

IASP 2026 Global Year theme of Neuropathic Pain: No

• Nicolò Bruna: Msc - Technical University Munich
• Felix S. Bott: PhD - Techical University Munich
• Pau Theo Zebahuser: MD - Techical University Munich
• Elisabeth Susanne May: PhD - Techical University Munich
• Joachim Gross: Prof. - University of Münster, Institute for Biomagnetism and Biosignalanalysis
• Markus Ploner: Prof - Techical University Munich