Authors :
Presenting Author: Sakar Rijal, M.S – Children's Health Care System
Kathryn F King, PhD – Children's Health Care System
Mally Townsend, BS – Cook Children's Health Care System
M. Scott Perry, MD – Cook Children’s Physician Network
Crystal Cooper, PhD – UT Arlington
Christos Papadelis, PhD – Cook Children's Health Care System
Rationale:
Epileptic seizures arise from an imbalance between excitatory and inhibitory (E/I) neural processes, particularly reduced cortical inhibition. Gamma-band oscillations ( >30 Hz) measured noninvasively via magnetoencephalography (MEG) are linked to GABAergic activity and proposed as markers of cortical excitability. In healthy brains, gamma power correlates with GABA levels suggesting disrupted gamma dynamics may reflect E/I imbalance. We investigate motor-induced gamma responses using MEG in children with epilepsy and neurotypical controls. We hypothesize that epilepsy will show altered gamma activity, indicating impaired inhibitory control in motor networks. Quantifying these neural signatures may establish motor gamma activity as a noninvasive biomarker of E/I imbalance in pediatric epilepsy, advancing understanding of disease mechanisms and guiding personalized treatment.
Methods:
We recruited 29 children with epilepsy (EP group; mean age: 15.48 ± 2.21 years) and 30 neurotypical controls (13.82 ± 2.42 years), with no significant age differences. Whole-head MEG and simultaneous electromyography were recorded from left and right index fingers during motor tasks with cartoon stimuli on a flashing checkerboard. Participants completed 340 finger-tap trials in separate runs (Fig. 1A). Data were filtered to remove DC offsets, notch filtered at 60 Hz, band-pass filtered (1–100 Hz) using a Butterworth filter, and artifacts rejection. Response-locked epochs (–1.5 to 1 s) were averaged across trials. (Fig. 1B). Cortical activity in primary motor cortex (M1) was localized using dynamic statistical parametric mapping, and virtual sensors reconstructed in left and right M1 (Fig. 1C). Morlet wavelet time-frequency (TF) maps were computed per trial and averaged by responses (left/right; Fig. 1D). Group TF differences were assessed using cluster-based permutation testing (CBPT) and correlated with antiseizure medication (ASMs) count.
Results:
Grand-averaged motor evoked fields (MEFs) at sensor and source levels for right and left index finger responses are shown in Fig. 2A–B. CBPT revealed suppressed contralateral gamma responses (~35–100 Hz) for right finger in the EP group from 55 ms before to 80 ms after movement onset (p=0.01; Fig. 2C–D). In this window, controls had higher gamma power (3.8% ± 15) than epilepsy (-2.8% ± 8; p=0.001; Fig. 2E). Left finger responses also showed suppressed contralateral gamma (~45–65 Hz) post-movement (~25–60 ms) with higher power in controls (5.9% ± 15) than EP (0.4% ± 10; p=0.01; Fig. 2F–H). Post-movement beta desynchronization power was lower in the EP group. For right taps, controls showed higher power (7% ± 26) than EP (-5% ± 17); for left taps, 12% ± 35 vs. -8% ± 19 (p< 0.05; Fig. 2I). In EP, beta power during left responses positively correlated with ASM count (Spearman’s r = 0.42; p=0.02; Fig. 2J).
Conclusions:
Our study shows altered oscillatory dynamics in epilepsy, with reduced beta and gamma power during motor responses. These findings suggest a potential biomarker of E/I imbalance, which may ultimately aid for diagnosis and monitoring ASMs efficacy.
Funding:
R01NS104116 and R01NS134944 by NINDS