John C. Mosher, Ph.D - US grants

[unreadable] DESCRIPTION (provided by applicant): [unreadable] We propose to demonstrate the feasibility of using nuclear magnetic resonance (NMR) techniques at ultra- low fields (ULF) to directly image neuronal currents in the human brain. We hypothesize that neuronal currents (both intra- and extra-cellular) will interact with the proton spins in tissue resulting in a measurable change in the NMR signal that can be imaged with existing magnetic resonance imaging (MRI) techniques at ULF. This proposal is in response to RFA-EB-05-001: "New Ways to Image Neural Activity." MRI spatially encodes the NMR signature of nuclei, typically protons, in a volume of interest. Today's high-field (HF) MRI machines employ static magnetic fields in the 1.5 T to above 9 T range to yield exquisite anatomical features. The last decade has also witnessed an explosion in functional MRI (fMRI) research that measures hemody- namic responses; however, as this RFA notes, such responses are relatively sluggish and only indirectly related to electrophysiological processes. Magnetoencephalography (MEG) and electroencephalography (EEG) are direct measures of the external magnetic and electric fields generated by neuronal currents. While these modalities yield detailed temporal information, the spatial localization must be inferred from highly-spe-cific spatial modeling priors. The electrophysiological "imaging" in MEG and EEG is therefore only "indirect" at best. Recently, several researchers proposed that electrophysiological.activity may interact with the nuclear spins in a measurable manner, such as causing phase and amplitude variations or changing the rate of decay in the NMR signal. Interactions between neuronal currents and spin populations in tissue may enable direct neuronal imaging (DNI) by MRI. Most studies to date have focussed on the feasibility of DNI at HF. Recently, our group (and a few others) has experimentally demonstrated ultra-low field (ULF) MRI, using fields 100,000- 1,000,000 times weaker than HF-MRI. While the NMR signals, known as the free induction decay (FID), at ULF are dramatically weaker than HF, we acquired high signal-to-noise measurements of FIDs at ULF using super- conducting .quantum interference device (SQUID) technology. We also recently presented the world's first simultaneous FID and MEG measurement of the human brain, using SQUID sensors. Our research will pursue demonstrating the feasibility of measuring a neuronal current effect on the NMR signature at ULF using two distinct approaches: 1) we will study interactions between neuronal currents and the proton spin population in tissue that induce dephasing of the spin population; and 2) we will study a novel mechanism based on the interaction of neuronal currents and the spin population that will cause a distinctly different relaxation of the spin population. The first approach is a direct extension of ideas presented for DNI at high fields, but can be greatly enhanced at ULF. Our second approach pursues an exciting possibility unique to ULF. [unreadable] [unreadable] [unreadable]

? DESCRIPTION (provided by applicant): Treatment of intractable focal epilepsy by resection of the seizure onset zone (SOZ) is often effective provided the SOZ can be reliably identified. Focal epilepsy, however, is fundamentally a network-based disease. The seizure onset zone is connected to a network whose other nodes may also exhibit abnormal neural activity either concurrently or subsequently. In patients without MRI detectable lesions, differentiation of the onset zone from these other nodes in the network can be difficult, even with the use of invasive recordings. The goal of this project is to improve SOZ identification, ultimately reducing the need for presurgical invasive recordings where possible, and guiding placement of electrodes in those patients who do need invasive monitoring. To achieve this goal, in Aim 1 we will build a functional connectivity atlas from a database of invasive Cortico-Cortical Evoked Potential (CCEP) recordings to identify common interaction networks in patients with partial epilepsy and to investigate the degree to which these are dependent on the location of the SOZ. To construct the atlas, patient data will be coregistered to a labelled anatomical atlas using a cortically constrained warping of each subject's structural MRI. In Aim 2, CCEPs data will be supplemented in the atlas with other data that provide additional insight into the brain regions involved in the seizure: regions of hypometabolism in interictal FDG PET, hypermetabolism in ictal SPECT, interictal spike localization from EEG and MEG and invasive recordings, functional areas associated with seizure semiology, MR-identified lesions, area of resection, post-surgical Engel classification. Using machine-learning methods, we will perform a sequence of tests to examine the degree to which the atlas can be used to identify the SOZ in individual subjects. Finally, in Aim 3, we will investigate the potential for using regional connectivity established frm noninvasive MEG data and resting state MRI in combination with the CCEPs atlas to identify these networks, with the ultimate goal of reducing the need for invasive monitoring. Retrospective analysis using a leave-one- out approach and comparison with outcomes will be used to quantify improvement in identification of the onset zone from both invasive and noninvasive recordings.