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Updated: Oct 9, 2026

Generation of Local CA1 γ Oscillations by Tetanic Stimulation
Published on: August 14, 2015
High-frequency oscillations arise through distinct mechanisms in models of α- synucleinopathy and
Abstract:
Background Pathological high-frequency oscillations (HFOs), widely researched in epilepsy, are increasingly being investigated as potential biomarkers of network hyperexcitability in neurodegenerative disorders. This interest is driven by growing evidence of comorbidity between epilepsy and neurodegenerative diseases, particularly Alzheimer's disease (AD) and dementia with Lewy bodies (DLB), suggesting that these HFOs could be useful biomarkers in these disorders. Patients with AD and mouse models of AD exhibit elevated HFOs during neurophysiology recordings, but whether HFOs occur in DLB remains unknown. Methods To address this question, we quantified cortical HFOs within the spectral range of 250-500 Hz and interictal spikes using surface electroencephalography recordings in a transgenic model of α-synucleinopathy that exhibits features of DLB (A53T mice) and a model of channelopathy-induced epilepsy ( Kcna1 -/- mice) . Results Both A53T and Kcna1 -/- mice exhibited significantly more HFOs than their respective control mice across all vigilance states. A53T mice exhibited more HFOs and interictal spikes than Kcna1 -/- mice, and the HFOs in A53T mice had higher frequencies and longer durations than those in Kcna1 -/- mice. Additionally, HFOs were most prevalent during non-REM sleep in A53T mice, coinciding with the vigilance state in which interictal spikes were most frequent in this model. However, they did not consistently co-occur with interictal spikes or seizures, and HFO counts did not correlate with interictal spike counts during 10-minute recording epochs. Conclusions Our findings indicate that HFOs likely arise from different neuronal populations and are generated through distinct mechanisms in these two models. Importantly, this work shows that HFOs are an electroencephalographic abnormality in a model of DLB and supports their potential as a new biomarker for neurodegenerative disorders.
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