Emerging Clinical Applications
Beyond its established use in epilepsy and brain tumor, researchers are exploring the potential use of MEG in the management of a variety of neurological conditions, such as traumatic brain injury, stroke, and neurodegenerative conditions like Alzheimer and Parkinson disease. By tracking brain activity at high resolution and in real time, MEG can be used to identify early biomarkers of these conditions, leading to earlier intervention and more effective treatments. MEG is also being investigated for its use in psychiatric disorders such as schizophrenia and depression, where understanding the underlying neural mechanisms could lead to innovative therapies.
Research in translational and basic human neuroscience
Translational MEG research bridges the gap between basic science and clinical practice, ensuring that discoveries made in the lab can be effectively applied to patient care. For instance, MEG can be used to validate findings from animal models in humans, helping to translate experimental therapies and diagnostic tools into clinical settings. Basic MEG research focuses on understanding the fundamental principles of brain function and neural dynamics. As an example, MEG can be used to study how different regions of the brain communicate, process information, and generate behaviors. Below are examples of ongoing research being performed by scientists associated with the UF Health MEG lab.
Multimodal Presurgical Language Mapping
Our research integrates MEG with other neuroimaging and electrophysiological modalities such as functional MRI (fMRI) and high gamma modulation in intracranial EEG (HGM-iEEG) recordings. The primary aim of this research is to enhance presurgical language mapping methods to optimize surgical outcomes for patients undergoing epilepsy and brain tumor surgeries. For more information and sample articles from our group,
Brain Connectonics
We are utilizing brain connectivity analysis and graph theory to investigate epilepsy, Alzheimer’s disease, and other neurological conditions. Our research focuses on understanding the intricate network of connections in the brain and how these networks are altered in various neurological disorders. By applying advanced analytical techniques, we aim to identify biomarkers that can aid in early diagnosis and monitor disease progression.
Developing Biomarkers for Patients with Dementia
Our research focuses on identifying biomarkers, brain regions, and networks associated with cognitive decline in Alzheimer’s disease and other types of dementia, such as Lewy body dementia. By leveraging various neuroimaging modalities and advanced analysis techniques, we aim to uncover the intricate mechanisms underlying these diseases and their progression.
MEG in Movement Disorders
We are investigating the neural mechanisms underlying movement disorders like Parkinson’s disease and dystonia. By combining MEG and local field potential recordings, we study how deep brain stimulation impacts brain networks. Our research aims to uncover the changes in brain connectivity and oscillatory patterns induced by DBS, ultimately leading to improved therapeutic strategies and better patient outcomes.
MEG in Neuromuscular Disorders
We are using MEG to investigate speech decoding in normal healthy controls as well as patients with amyotrophic lateral sclerosis (ALS). By decoding neural signals associated with speech, we aim to develop assistive communication technologies that can significantly enhance the quality of life for ALS patients who have lost their ability to speak.