Establishing sleep stages using Delta, Theta and Gamma oscillations from long term Local Field Potential (LFP) recordings in mice

Molńar, László; Domokos, József; Ferando, Isabella; Módy, István

doi:10.1109/cinti.2018.8928237

Cited by 3 publications

(3 citation statements)

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“…Four to 5 days after the animals had fully recovered from the surgery, chronic simultaneous video and local field potential recordings were carried out continuously (24 h a day) for 1–8 weeks as previously described ( Molnár et al, 2018 ; Vrontou et al, 2022 ). LFPs were recorded with a custom-made miniature dual headstage amplifier connected to the electrode sockets mounted on the animal’s head and then wired to an electrical commutator (Dragonfly Inc.).…”

Section: Methodsmentioning

confidence: 99%

“…We used the Metric3S values to define epochs to be considered seizures (and post-ictal lulls) in the record. Previously we described an original approach to establish objective thresholds using only the intrinsic properties of the extracted signals ( Molnár et al, 2018 ). We enhanced the autocorrelation method using this thresholding technique.…”

Section: Methodsmentioning

confidence: 99%

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Capturing the power of seizures: an empirical mode decomposition analysis of epileptic activity in the mouse hippocampus

Molńar

Ferando

Liu

et al. 2023

Front. Mol. Neurosci.

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IntroductionVarious methods have been used to determine the frequency components of seizures in scalp electroencephalography (EEG) and in intracortical recordings. Most of these methods rely on subjective or trial-and-error criteria for choosing the appropriate bandwidth for filtering the EEG or local field potential (LFP) signals to establish the frequency components that contribute most to the initiation and maintenance of seizure activity. The empirical mode decomposition (EMD) with the Hilbert-Huang transform is an unbiased method to decompose a time and frequency variant signal into its component non-stationary frequencies. The resulting components, i.e., the intrinsic mode functions (IMFs) objectively reflect the various non-stationary frequencies making up the original signal.Materials and methodsWe employed the EMD method to analyze the frequency components and relative power of spontaneous electrographic seizures recorded in the dentate gyri of mice during the epileptogenic period. Epilepsy was induced in mice following status epilepticus induced by suprahippocampal injection of kainic acid. The seizures were recorded as local field potentials (LFP) with electrodes implanted in the dentate gyrus. We analyzed recording segments that included a seizure (mean duration 28 s) and an equivalent time period both before and after the seizure. Each segment was divided into non-overlapping 1 s long epochs which were then analyzed to obtain their IMFs (usually 8–10), the center frequencies of the respective IMF and their spectral root-mean-squared (RMS) power.ResultsOur analysis yielded unbiased identification of the spectral components of seizures, and the relative power of these components during this pathological brain activity. During seizures, the power of the mid frequency components increased while the center frequency of the first IMF (with the highest frequency) dramatically decreased, providing mechanistic insights into how local seizures are generated.DiscussionWe expect this type of analysis to provide further insights into the mechanisms of seizure generation and potentially better seizure detection.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Capturing the power of seizures: an empirical mode decomposition analysis of epileptic activity in the mouse hippocampus

Molńar

Ferando

Liu

et al. 2023

Front. Mol. Neurosci.

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“…The RMS values for the γ and δ bandpass filtered recordings were calculated in 8 s long epochs shifted by 0.5 or 1 s steps as previously described. 57 In brief, the RMS(γ)/RMS(δ) ratios were calculated on a point-by-point basis and plotted for 12 h recording periods corresponding to the L or the D cycles. A histogram of the RMS(γ)/RMS(δ) ratios was plotted for an entire 12 h (43 200 s) recording period.…”

Section: Methodsmentioning

confidence: 99%

Altered brain rhythms and behaviour in the accelerated ovarian failure mouse model of human menopause

Vrontou

Bédécarrats

Ayodeji

et al. 2022

Brain Communications

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To date, potential mechanisms of menopause-related memory and cognitive deficits have not been elucidated. Therefore, we studied brain oscillations, their phase-amplitude coupling, sleep and vigilance state patterns, running wheel use and other behavioral measures in a translationally valid mouse model of menopause, the 4-vinylcyclohexene-diepoxide induced accelerated ovarian failure. After accelerated ovarian failure, female mice show significant alterations in brain rhythms, including changes in the frequencies of θ (5-12 Hz) and γ (30-120 Hz) oscillations, a reversed phase-amplitude coupling, altered coupling of hippocampal sharp-wave ripples to medial prefrontal cortical sleep spindles, and reduced δ oscillation (0.5-4 Hz) synchrony between the two regions during non-REM sleep. In addition, we report on significant circadian variations in the frequencies of θ and γ oscillations, and massive synchronous δ oscillations during wheel running. Our results reveal novel and specific network alterations and feasible signs for diminished brain connectivity in the accelerated ovarian failure mouse model of menopause. Taken together, our results may have identified changes possibly responsible for some of the memory and cognitive deficits previously described in this model. Corresponding future studies in menopausal women could shed light on fundamental mechanisms underlying the neurological and psychiatric comorbidities present during this important transitional phase in women’s lives.

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Quantifying spectral peaks in theta and gamma brain oscillations detected from long term Local Field Potential (LFP) recordings in mice

Molńar

Módy

2019

2019 IEEE 19th International Symposium on Computational Intelligence and Informatics and 7th IEEE International Conference on R

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Establishing sleep stages using Delta, Theta and Gamma oscillations from long term Local Field Potential (LFP) recordings in mice

Cited by 3 publications

References 9 publications

Capturing the power of seizures: an empirical mode decomposition analysis of epileptic activity in the mouse hippocampus

Capturing the power of seizures: an empirical mode decomposition analysis of epileptic activity in the mouse hippocampus

Altered brain rhythms and behaviour in the accelerated ovarian failure mouse model of human menopause

Quantifying spectral peaks in theta and gamma brain oscillations detected from long term Local Field Potential (LFP) recordings in mice

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