No participants were enrolled to collected prospective data.

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.

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.

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.

The study will obtain MEG/EEG data from healthy subjects, recruiting only individuals without underlying health conditions. Additionally, this study will utilize clinical MEG/EEG data from patients, which are acquired as part of standard clinical care for clinical purposes. Since women, girls, and minorities are included in the population to whom recruiting materials are directed, we anticipate that subject selection will be equitable.