TY  - JOUR
AB  - OBJECTIVES: The spontaneous neural activity of premature neonates has been characterized with electroencephalography (EEG). However, evaluation of normal and pathological fetal brain development is still largely unknown. Fetal magnetoencephalography (fMEG) is currently the only available technique to record fetal neural activity. Benefiting from progress in machine learning and artificial intelligence, we aimed to transfer premature EEG to fMEG, to characterize the manifestation of spontaneous activity using the knowledge obtained from premature EEG. METHODS: In this study, 30 high-resolution EEG recordings from premature newborns and 44 fMEG recordings were used to develop a transfer function to predict the spontaneous neural activity of the fetus. After preprocessing, bursts of spontaneous activity were detected using the non-linear energy operator. Next, we proposed a CycleGAN-based model to transform the premature EEG to fMEG and evaluated its performance with both time and frequency measurements. RESULTS: In the time domain, the values were similar for the mean square error (< 5 %) and correlation (0.91 ± 0.05 and 0.89 ± 0.08) for both transformations between the original data and that generated by CycleGAN. However, considering the frequency content, the CycleGAN-based model modulated the frequency content of EEG to MEG transformed signals relative to the original signals by increasing the power, on average, in all frequency bands, except for the slow delta frequency band. CONCLUSION: Our developed model showed promising potential to generate a priori signatures of fMEG manifestations related to spontaneous neural activity. Collectively, this study represents the first steps toward identifying neurobiomarkers of fetal brain development.
AU  - Gallard, A.*
AU  - Brebion, B.*
AU  - Sippel, K.*
AU  - Zaylaa, A.
AU  - Preissl, H.
AU  - Moghimi, S.*
AU  - Fregier, Y.*
AU  - Wallois, F.*
C1  - 74923
C2  - 57722
CY  - 65 Rue Camille Desmoulins, Cs50083, 92442 Issy-les-moulineaux, France
TI  - Transforming spontaneous premature neonatal EEG to spontaneous fetal MEG using a novel machine learning approach.
JO  - Neurophysiol. Clin.
VL  - 55
IS  - 5
PB  - Elsevier France-editions Scientifiques Medicales Elsevier
PY  - 2025
SN  - 0987-7053
ER  - 

TY  - JOUR
AB  - Introduction. -Pantothenate kinase-associated neurodegenerative disease (PKAN) is a secondary generalized dystonia associated with an accumulation of iron in the basal ganglia and increased motor cortex excitability. A pilot study in three patients with secondary generalized dystonia had reported a reduced frequency of painful axial spasms following inhibitory 1-Hz repetitive transcranial magnetic stimulation (rTMS) applied over the premotor cortex. Patient and methods. -We compared the effects of real versus sham rTMS on the frequency of the complex movement pattern and the need for additional benzodiazepine medication in a 6-year-old male patient with PKAN. A 20-minute session of left premotor 1-Hz rTMS was performed daily on 5 consecutive days. Results. -The occurrence of the complex movement pattern was gradually reduced from three to two attacks daily to one attack daily by real rTMS while sham rTMS had no effect. This reduction was obtained concomitantly with a similar reduction of additional benzodiazepines for both real and sham rTMS sessions. Conclusion. -Inhibitory rTMS of the premotor cortex may be used to temporarily control motor symptoms in PKAN.
AU  - Mylius, V.*
AU  - Gerstner, A.*
AU  - Peters, M.*
AU  - Prokisch, H.
AU  - Leonhardt, A.*
AU  - Hellwig, D.*
AU  - Rosenow, F.*
C1  - 1860
C2  - 26096
SP  - 27-30
TI  - Low-frequency rTMS of the premotor cortex reduces complex movement patterns in a patient with pantothenate kinase-associated neurodegenerative disease (PKAN).
JO  - Neurophysiol. Clin.
VL  - 39
IS  - 1
PB  - Elsevier France-Editions Scientifiques Medicales Elsevier
PY  - 2009
SN  - 0987-7053
ER  -