Clinical Applications of High-Frequency Oscillations

NCT ID: NCT00600717

Last Updated: 2026-02-04

Basic Information

• Recruitment Status: WITHDRAWN
• Study Classification: OBSERVATIONAL
• Study Start Date: 2000-11-01
• Study Completion Date: 2027-08-01

Brief Summary

The objective of this study is to utilize high-frequency brain signals (HFBS) to localize functional brain areas and characterize HFBS in epilepsy, migraine, and other brain disorders. Our goal is to create the world's first high-frequency MEG/EEG/ECoG/SEEG database for the developing brain. HFBS include high-gamma activation/oscillations, high-frequency oscillations (HFOs), ripples, fast ripples, spikelets, fast spikelets, and very high-frequency oscillations (VHFOs). While terminologies and frequency bands may vary among reports, both HFOs and high-gamma waves are crucial for understanding brain function and developing potential treatments for neurological disorders.

We have been developing an intelligent software platform to analyze signals from low to very high-frequency ranges across multiple frequency bands. To achieve these goals, we have developed several innovative techniques and software packages:

• Accumulated spectrogram
• Accumulated source imaging
• Frequency-encoded source imaging
• Multi-frequency analysis at source levels
• Artificial intelligence detection of HFOs
• Neural network analysis (Graph Theory)
• Other techniques (e.g., Independent Component Analysis, virtual sensors) These methods enable researchers to better understand the characteristics and significance of HFOs and high-gamma brain waves, contributing to advancements in the diagnosis and treatment of neurological disorders.

Detailed Description

The purpose of this study is to go beyond conventional analyses of brain signals in narrow frequency bands (typically 1-30 Hz) by measuring brain signals from infraslow to very fast frequencies (0.01 - 2800 Hz). Specifically, we propose to study physiological high-frequency oscillations (HFOs) in sensorimotor, auditory, visual, and language-evoked magnetic fields, and to investigate pathological HFOs in epilepsy, migraines, and other disorders. This is clinically important for several reasons.

For instance, there are 400,000 to 600,000 patients with refractory epilepsy in the United States. As these patients' seizures cannot be controlled by medication, epilepsy surgery is a potential cure. Accurate identification of ictogenic zones (the brain areas that cause seizures) is essential for favorable surgical outcomes. Unfortunately, the existing method, electrocorticography (ECoG), requires placing electrodes on the brain surface to capture spikes (typically, 14-70 Hz), which is both risky and costly. Our study aims to use magnetoencephalography (MEG) and electroencephalography (EEG) to identify ictogenic zones non-invasively. To achieve this goal, we propose detecting high-frequency (70-2500 Hz) and low-frequency (< 14 Hz) brain signals using advanced signal processing methods. Our central hypothesis is that high-frequency brain signals will lead to significantly improved rates of seizure freedom compared to spikes. This hypothesis is based on recent reports that high-frequency brain signals are localized to ictogenic zones.

Leveraging our unique resources and expertise, we plan to address four specific aims:

1. Quantify the Spatial Concordance: We will quantify the spatial concordance between MEG and ECoG signals in both low and high-frequency ranges. We hypothesize that ictogenic zones determined by invasive ECoG can be non-invasively detected and localized by high-frequency MEG signals.

2. Quantify the Occurrence Concordance: We will quantify the occurrence concordance between EEG and ECoG signals in both low and high-frequency ranges. We hypothesize that epileptic high-frequency signals from the ictogenic zones determined by invasive ECoG can also be non-invasively detected by EEG, although the localization of EEG may be significantly inferior to that of MEG.

3. Improve Epilepsy Surgery Outcomes: We will determine whether epilepsy surgery based on multi-frequency signals (low-frequency brain signals, spikes, and high-frequency brain signals), instead of spikes alone, leads to better seizure outcomes. We hypothesize that epilepsy surgery guided by high-frequency brain signals detected with MEG/EEG will significantly improve surgical outcomes.

4. Enhance Pre-surgical Planning: We will determine whether multi-frequency analyses provide more information than single-frequency analysis for estimating epileptogenic zones for pre-surgical ECoG electrode implantation. We hypothesize that covering all brain areas generating low to high-frequency epileptic activity is a prerequisite to localize multiple ictogenic zones for favorable post-surgical outcomes.

To yield definitive results, we propose a multi-center study to determine if high-frequency brain signals are new biomarkers for significantly improving epilepsy surgery outcomes. According to our pilot data, localization of epileptogenic zones with MEG high-frequency signals can increase post-operative seizure freedom by approximately 30-40%. The proposed study should result in millions of intractable epilepsy patients being seizure-free. Additionally, this study lays the foundation for using low and high-frequency brain signals as new biomarkers for the diagnosis and treatment of various other disorders (e.g., migraine, autism).

Furthermore, we will incorporate Optically Pumped Magnetometers MEG (OPM-MEG) to enhance the detection of high-frequency brain signals. OPM-MEG offers higher sensitivity and spatial resolution compared to conventional MEG, making it an invaluable tool for our research objectives.

Conditions

Migraine; Headache; Pain; Autism; Cerebral Palsy; Brain Development; Traumatic Brain Injury; ADHD - Attention Deficit Disorder With Hyperactivity; Mental Health; Epilepsy

Study Design

• Observational Model Type: OTHER
• Study Time Perspective: PROSPECTIVE

Study Groups

Pediatric Patients and Healthy Children

Healthy children without dental works. Pediatric patients with epilepsy and migraine (headache).

No interventions assigned to this group

Eligibility Criteria

Inclusion Criteria

• Healthy and cooperative.
• Ages: from 1 day to 69 years (male or female).
• Normal hearing and vision.
• Normal hand movement.
• No history of neurological or psychiatric diseases.
• No family history of genetic neurological or psychiatric diseases.
• No metal implants such as pacemakers, neuro-stimulators, cochlear implants, etc.

Exclusion Criteria

• Taking any medications for depression, neurologic, or psychiatric conditions.
• Not feeling well, having epilepsy, or other brain disorders.
• Recent concussion or head injury.
• Presence of metal in the body, such as dental braces, which could cause "magnetic noise". A simple, quick "magnetic noise screening" can be conducted at the MEG Center to determine eligibility.
• Presence of electrical or metal implants such as pacemakers, neuro-stimulators, or orthopedic pins or plates. The research nurse will discuss all exclusions in further detail before the magnetic resonance imaging (MRI) scan.
• Inability to pass the pre-experimental screening.

• Minimum Eligible Age: 1 Day
• Maximum Eligible Age: 69 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

University of Cincinnati

OTHER

Sponsor Role: collaborator

Children's Hospital Medical Center, Cincinnati

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

Jing Xiang, Ph.D M.D.

Role: STUDY_DIRECTOR

Children's Hospital Medical Center, Cincinnati

Locations

MEG

Cincinnati, Ohio, United States

Countries

United States

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Ren J, Xiang J, Chen Y, Li F, Wu T, Shi J. Abnormal functional connectivity under somatosensory stimulation in migraine: a multi-frequency magnetoencephalography study. J Headache Pain. 2019 Jan 9;20(1):3. doi: 10.1186/s10194-019-0958-3.

Reference Type: BACKGROUND

PMID: 30626318 (View on PubMed)

Yang K, Chen J, Xiang J, Liu H, Zou Y, Kan W, Liu Y, Li L. Histopathologic and Clinical Correlation of Aberrant Neuromagnetic Activities with Low to High Frequency of Gliomas. World Neurosurg. 2019 Mar;123:e609-e620. doi: 10.1016/j.wneu.2018.11.235. Epub 2018 Dec 8.

Reference Type: BACKGROUND

PMID: 30529596 (View on PubMed)

Shi Q, Zhang T, Miao A, Sun J, Sun Y, Chen Q, Hu Z, Xiang J, Wang X. Differences Between Interictal and Ictal Generalized Spike-Wave Discharges in Childhood Absence Epilepsy: A MEG Study. Front Neurol. 2020 Jan 24;10:1359. doi: 10.3389/fneur.2019.01359. eCollection 2019.

Reference Type: BACKGROUND

PMID: 32038453 (View on PubMed)

Yin C, Zhang X, Xiang J, Chen Z, Li X, Wu S, Lv P, Wang Y. Altered effective connectivity network in patients with insular epilepsy: A high-frequency oscillations magnetoencephalography study. Clin Neurophysiol. 2020 Feb;131(2):377-384. doi: 10.1016/j.clinph.2019.11.021. Epub 2019 Dec 6.

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PMID: 31865139 (View on PubMed)

Jiang W, Wu C, Xiang J, Miao A, Qiu W, Tang L, Huang S, Chen Q, Hu Z, Wang X. Dynamic Neuromagnetic Network Changes of Seizure Termination in Absence Epilepsy: A Magnetoencephalography Study. Front Neurol. 2019 Jul 2;10:703. doi: 10.3389/fneur.2019.00703. eCollection 2019.

Reference Type: BACKGROUND

PMID: 31338058 (View on PubMed)

Liang C, Wenstrup LH, Samy RN, Xiang J, Zhang F. The Effect of Side of Implantation on the Cortical Processing of Frequency Changes in Adult Cochlear Implant Users. Front Neurosci. 2020 Apr 29;14:368. doi: 10.3389/fnins.2020.00368. eCollection 2020.

Reference Type: BACKGROUND

PMID: 32410947 (View on PubMed)

Firestone GM, McGuire K, Liang C, Zhang N, Blankenship CM, Xiang J, Zhang F. A Preliminary Study of the Effects of Attentive Music Listening on Cochlear Implant Users' Speech Perception, Quality of Life, and Behavioral and Objective Measures of Frequency Change Detection. Front Hum Neurosci. 2020 Mar 31;14:110. doi: 10.3389/fnhum.2020.00110. eCollection 2020.

Reference Type: BACKGROUND

PMID: 32296318 (View on PubMed)

Xiang J, Maue E, Fan Y, Qi L, Mangano FT, Greiner H, Tenney J. Kurtosis and skewness of high-frequency brain signals are altered in paediatric epilepsy. Brain Commun. 2020 Mar 31;2(1):fcaa036. doi: 10.1093/braincomms/fcaa036. eCollection 2020.

Reference Type: BACKGROUND

PMID: 32954294 (View on PubMed)

Xiang J, Maue E, Tong H, Mangano FT, Greiner H, Tenney J. Neuromagnetic high frequency spikes are a new and noninvasive biomarker for localization of epileptogenic zones. Seizure. 2021 Jul;89:30-37. doi: 10.1016/j.seizure.2021.04.024. Epub 2021 May 4.

Reference Type: BACKGROUND

PMID: 33975080 (View on PubMed)

Xiang J, Maue E, Fujiwara H, Mangano FT, Greiner H, Tenney J. Delineation of epileptogenic zones with high frequency magnetic source imaging based on kurtosis and skewness. Epilepsy Res. 2021 May;172:106602. doi: 10.1016/j.eplepsyres.2021.106602. Epub 2021 Mar 8.

Reference Type: BACKGROUND

PMID: 33713889 (View on PubMed)

Xiang J, Yu X, Bonnette S, Anand M, Riehm CD, Schlink B, Diekfuss JA, Myer GD, Jiang Y. Improved Biomagnetic Signal-To-Noise Ratio and Source Localization Using Optically Pumped Magnetometers with Synthetic Gradiometers. Brain Sci. 2023 Apr 15;13(4):663. doi: 10.3390/brainsci13040663.

Reference Type: BACKGROUND

PMID: 37190628 (View on PubMed)

Xiang J, Tong H, Jiang Y, Barnes-Davis ME. Spatial and Frequency Specific Artifact Reduction in Optically Pumped Magnetometer Recordings. J Integr Neurosci. 2022 Aug 16;21(5):145. doi: 10.31083/j.jin2105145.

Reference Type: BACKGROUND

PMID: 36137963 (View on PubMed)

Chen D, Liu K, Guo J, Bi L, Xiang J. Editorial: Brain-computer interface and its applications. Front Neurorobot. 2023 Feb 9;17:1140508. doi: 10.3389/fnbot.2023.1140508. eCollection 2023. No abstract available.

Reference Type: BACKGROUND

PMID: 36845071 (View on PubMed)

Zhang F, Han JH, Samy R, Xiang J. Editorial: Changes in the auditory brain following deafness, cochlear implantation, and auditory training, volume II. Front Hum Neurosci. 2023 Feb 6;17:1124304. doi: 10.3389/fnhum.2023.1124304. eCollection 2023. No abstract available.

Reference Type: BACKGROUND

PMID: 36814434 (View on PubMed)

Guo J, Xiao N, Li H, He L, Li Q, Wu T, He X, Chen P, Chen D, Xiang J, Peng X. Transformer-Based High-Frequency Oscillation Signal Detection on Magnetoencephalography From Epileptic Patients. Front Mol Biosci. 2022 Mar 4;9:822810. doi: 10.3389/fmolb.2022.822810. eCollection 2022.

Reference Type: BACKGROUND

PMID: 35309504 (View on PubMed)

Sun Y, Li Y, Sun J, Zhang K, Tang L, Wu C, Gao Y, Liu H, Huang S, Hu Z, Xiang J, Wang X. Functional reorganization of brain regions into a network in childhood absence epilepsy: A magnetoencephalography study. Epilepsy Behav. 2021 Sep;122:108117. doi: 10.1016/j.yebeh.2021.108117. Epub 2021 Jul 8.

Reference Type: BACKGROUND

PMID: 34246893 (View on PubMed)

Sun K, Yu T, Yang D, Ren Z, Qiao L, Ni D, Wang X, Zhao Y, Chen X, Xiang J, Chen N, Gao R, Yang K, Lin Y, Kober T, Zhang G. Fluid and White Matter Suppression Imaging and Voxel-Based Morphometric Analysis in Conventional Magnetic Resonance Imaging-Negative Epilepsy. Front Neurol. 2021 Apr 29;12:651592. doi: 10.3389/fneur.2021.651592. eCollection 2021.

Reference Type: BACKGROUND

PMID: 33995250 (View on PubMed)

Xiang J, Ishii R, Yang X. Editorial: High Frequency Brain Signals: From Basic Research to Clinical Application. Front Hum Neurosci. 2022 Mar 30;16:872478. doi: 10.3389/fnhum.2022.872478. eCollection 2022. No abstract available.

Reference Type: RESULT

PMID: 35431837 (View on PubMed)

Related Links

http://www.cincinnatichildrens.org/research/div/neurology/labs/xiang-lab/

Xiang Lab's website offers in-depth insights into both basic scientific research and its clinical applications.

https://github.com/brainx888

The GitHub website offers extensive resources on software, methodologies, manuals, guides, and other information for analyzing signals across various frequency bands, ranging from low to high.

Other Identifiers

2008-1439

Identifier Type: OTHER

Identifier Source: secondary_id

IRB 2012-0866; 2018-8108

Identifier Type: -

Identifier Source: org_study_id