Medical College of Wisconsin Epilepsy Research

The Language Imaging Laboratory, led by Jeffrey Binder, MD, pioneered fMRI as a less invasive alternative for determining language dominance prior to epilepsy surgery.

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Partial epilepsy is increasingly viewed as a network-level phenomenon involving progressive changes in brain morphology and inter-regional connectivity. Preliminary evidence suggests that these changes may be related to the duration and severity of epilepsy, severity of cognitive and psychiatric co-morbidities, and variation in medication responsiveness. The Epilepsy Connectome Project (ECP), funded by the National Institute of Neurological Disorders and Stroke (NINDS), aims to test these hypotheses by acquiring detailed neuroimaging and clinical data in a large (n = 150), prospective sample of patients with temporal lobe epilepsy who vary in epilepsy duration, seizure burden, and neurobehavioral status. The project is a collaboration between teams at MCW (J. Binder, PI) and UW-Madison (M.E. Meyerand, PI). MRI acquisitions closely follow Human Connectome Project guidelines and include high-resolution structural imaging, 40 minutes of “resting state” fMRI, 4 cognitive task activation protocols (emphasizing language, semantic memory, emotional face processing, and social cognition), and high-resolution diffusion tensor imaging. Magnetoencephalography (MEG) acquisitions include resting state and 3 task activation protocols. Neurobehavioral assessments cover a wide range of domains using instruments from the NIH Toolbox, standard clinical measures, and experimental measures.

Recruitment ran from January 2016 through March 2020, at which point enrollment was ended due to the Covid-19 pandemic. We enrolled 149 temporal lobe epilepsy patients. Of these, 131 completed the full MRI and behavioral baseline protocol, and 82 completed MEG. Healthy control data include 60 participants in the MRI protocol, 84 in the behavioral protocol, and 44 in the MEG protocol. Data analyses continue on this large and multi-faceted dataset. All data will be made publicly available in late 2021 for use by the scientific community.

Novel findings published to date include:

• Identification of connectivity differences between patients and controls using machine learning methods applied to resting-state fMRI data (Hwang et al., 2019b)
• Relationships between verbal memory function and effective connectivity between nodes of the ‘default mode’ network (Cook et al., 2019)
• Structural and functional connectivity correlates of cognitive slowing in TLE patients (Hwang et al., 2019a)
• Neuroanatomical changes underlying personality trait differences between patients and controls (Rivera-Bonet et al., 2019)
• Neurobiological and sociodemographic features of cognitive phenotypes in TLE (Hermann et al., 2020)

Electroencephalography (EEG), electrocorticography (ECoG), and Magnetoencephalography (MEG) represent important diagnostic tools in the evaluation of patients with epilepsy. Research efforts broadly focus on developing and validating novel methods for using brain signals to localize brain-regions that give rise to seizures and to map important functional areas that need to be preserved when surgical treatments are considered.

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Studies on the neuropsychology of epilepsy have advanced our knowledge of brain behavior relationships through examination of the effects of seizures, AEDs, and surgical intervention on higher cognitive functioning.

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Near infrared spectroscopy (NIRS) is a well-established, noninvasive tool to continuously assess regional tissue oxygenation in the brain. It was first described by Jöbsis 40 years ago and has been used in various clinical settings, especially in the field of neuroscience. The brain has high energy demands, and activation of brain tissue is accompanied by an increase in cerebral blood flow and volume in activated regions. This “neurovascular coupling” is the basis for many functional neuroimaging techniques, including NIRS, fMRI, positron emission tomography (PET) and single-photon emission computerized tomography (SPECT). By measuring the relative changes of different hemoglobin species, changes in cerebral blood flow can be calculated with NIRS. The coupling of NIRS with noninvasive neuroimaging techniques has potential for widespread clinical applications in neuroscience, including language mapping and epileptogenic zone localization, and detection of postsurgical cerebral reorganization as well as in neurocritical care. Several traits of NIRS make it a unique tool in both clinical care and neuroscience research, including its ease of use, low cost, and portability. Although spatial resolution is much lower than with fMRI, the temporal resolution of NIRS is considerably higher. Because no large device is required, brain activity can be monitored with NIRS even as a participant moves about in the environment, making it a uniquely powerful tool for studying brain activity in awake infants, children, and even underwater divers.

Previous research in human participants suggests that increases in prefrontal cerebral flow during cognitive tasks can be detected by NIRS. Reliable lateralization of this activation signal during a word-generation task was demonstrated in one preliminary study, which also suggested agreement between NIRS and Wada language lateralization in a small patient sample (n = 6). A second small study using a verbal fluency task also suggested good correlation between NIRS, fMRI, and Wada testing in both adult and pediatric patients with epilepsy.

Researchers in the Whelan Lab, headed by Harry Whelan, MD, are using a functional NIRS (fNIRS) imaging system to map cortical functions in healthy volunteers. The fNIRS system uses an array of 102 sensors in a cap, which is fitted on the head in a manner similar to an electroencephalography (EEG) cap. The large number of sensors enables investigation of a very large extent of the cortical surface, which is necessary to accurately localize signals and detect interactions between various brain functional regions. We are currently testing volunteers with motor tasks, vision tasks, and a language task protocol previously validated extensively with fMRI. We are presently engaged in benchmarking the performance of fNIRS against fMRI. We hope that the fNIRS system will allow us to conduct, outside of an MRI magnet, the same sort of cortical function testing that has become well accepted with fMRI (Chen et al., 2020). It is also our belief that with an appropriately water-tight and pressure resistant fNIRS system, we will be able to measure activity in cognitive brain networks at a variety of depths and oxygen conditions. This will allow not only pre-dive and post-dive measurements of cognitive function, but measurement during a dive.

National Institute of Neurological Disorders and Stroke (NINDS)
U01 NS093650: “The Epilepsy Connectome Project”
J. Binder, M.E. Meyerand, Co-Principal Investigators

National Institute of Neurological Disorders and Stroke (NINDS)
R01 NS035929: “Presurgical Applications of Functional MRI in Epilepsy”
J. Binder, Principal Investigator

National Institute of Neurological Disorders and Stroke (NINDS)
U01 NS108916: “Dynamics and Causal Functions of Large-Scale Cortical and Subcortical Networks”
J. Wolpaw (National Center for Adaptive Technologies, Albany), Principal Investigator

Office of Naval Research
ONR: N00014-19-1-2560: “Neurobiological and physiological measurements from free swimming marine mammals”
H.T. Whelan, Principal Investigator

Bleser Family Foundation
“Neurology Research Program in Brain Blood Flow”
H.T. Whelan, Principal Investigator

NIH Clinical Translational Science Institute of Southeast Wisconsin
KL2 Mentored Career Development Scholar Award: “Defining the Neural Dynamics of Concept Retrieval Using Electrocorticography”
W. Gross, Principal Investigator; J. Binder and W. Mueller, Mentors

Advancing a Healthier Wisconsin Endowment
Project #5520462: “Cognitive Neuroscience Research Program”
B.-F. Fitzsimmons, Principal Investigator

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