Over the last year, much emphasis has been place on the analysis of electrophysiological data in order to better understand spontaneous fluctuations in the fMRI signal. Much of this work has been done on concurrently acquired EEG-fMRI data, and primate data obtained by the laboratories of David Leopold (NIMH/NIH) and Naotaka Fujii (BSI, RIKEN, Japan). In the EEG-fMRI data, it was found that the spatial correlation present in fMRI data, often thought to represent neuronal communication, was strongly dependent on EEG band limited power in specific frequency bands (alpha and theta). Similar to an earlier study in the lab, this was interpreted as the effect of alertness on spontaneous brain activity. Extending the earlier study, not only the level but also the spatial characteristics of the correlation changed with changes in alertness. To further investigate this, ECoG data collected over large swaths of primate brain was analyzed, with the goal of characterizing apparent networks of neuro-electrical communication. It was found that correlated variations in neuro-electrical signals occurred in clusters of electrodes whose spatial distribution was strikingly similar to the spatial correlation patterns found with fMRI. Furthermore, correlation patterns did not vary significantly across various states of alertness, including attentive and unattentive waking, as well as sleep. This suggests that the correlational patterns present in fMRI data in part result from neuro-electrical activity, but that this activity may not have direct relevance for waking behavior. Additionally, it was found that the spatial correlation of neuro-electrical activity is not specific to any oscillatory frequency band but rather has broadband characteristics. This is suggestive of brief electrophysiological events underlying MRI signal correlation. Based on this, further analysis focuses on analysis of concurrently acquired electrophysiology/MRI data. The use of magnetic susceptibility contrast to infer brain myelin content is ongoing. Currently, in collaboration with the laboratory of Danny Reich, systematic studies are underway to investigate the utility of susceptibility contrast, specifically the effect of myelin on the T2*-signal decay curve, in detecting abnormalities in multiple sclerosis. In addition, a myelin mapping approach based on a novel magnetization transfer technique is being evaluated on marmoset brain, with the goal of assessing specificity and sensitivity.
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| de Zwart, Jacco A; van Gelderen, Peter; Schindler, Matthew K et al. (2018) Impulse response timing differences in BOLD and CBV weighted fMRI. Neuroimage 181:292-300 |
| Turchi, Janita; Chang, Catie; Ye, Frank Q et al. (2018) The Basal Forebrain Regulates Global Resting-State fMRI Fluctuations. Neuron 97:940-952.e4 |
| Duyn, Jeff H (2018) Studying brain microstructure with magnetic susceptibility contrast at high-field. Neuroimage 168:152-161 |
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| Özbay, Pinar S; Chang, Catie; Picchioni, Dante et al. (2018) Contribution of systemic vascular effects to fMRI activity in white matter. Neuroimage 176:541-549 |
| Jiang, Xu; van Gelderen, Peter; Duyn, Jeff H (2017) Spectral characteristics of semisolid protons in human brain white matter at 7 T. Magn Reson Med 78:1950-1958 |
| Shmueli, K; Dodd, S J; van Gelderen, P et al. (2017) Investigating lipids as a source of chemical exchange-induced MRI frequency shifts. NMR Biomed 30: |
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| Duyn, Jeff H; Schenck, John (2017) Contributions to magnetic susceptibility of brain tissue. NMR Biomed 30: |
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