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The Neural Basis of Functional MRI Responses

$929,620ZIAFY2019MHNIH

National Institute Of Mental Health

Investigators

Linked publications, trials & patents

Abstract

Functional magnetic resonance imaging (fMRI) has greatly advanced our understanding of the human brain, specifically how it processes sensory stimuli and even gives rise to particular percepts, actions, and thoughts. An unexpected twist has been the high value of studying the brains spontaneous activity in the absence of any task, which has given rise to the perspective of interplay among intrinsic brain networks. At its core, fMRI represents a readout of local changes in blood flow that is most often derived from local changes in neural activity. Since blood flow and neural activity operate by entirely different principles, pinpointing their specific connection has been elusive and seems to depend on a number of factors. This is not surprising surprising, for how can one make a one-to-one mapping between a specific pattern of activity among millions of neurons in a voxel to a slow change of single scalar values measured as the local the hemodynamic signal? Frustrating as the problem is, the topic is of great importance, since any clues about the link to local neural activity or ascending neuromodulation can have wide-reaching consequences for interpreting results in humans, including in psychiatric patients.. While our laboratory does not study neurovascular coupling per se, we do undertake experiments that bring new insights into the interpretation of the hemodynamic fMRI signal. We are studying the nature of local neural diversity of in the spiking responses to different types of signals, and how this bears on the hemodynamic responses from the same voxel or area. We are also investigating the relationship between activity in large-scale functional MRI networks across the brain to local neural activity measured at a single position. In a recently published study, we discovered that neurons from within a single voxel were highly varied in their responses to naturalistic movies, and that only 16% of the neurons measured therein were ostensibly linked with the fluctuations of the hemodynamic response. These special neurons matched not only the vascular response, but also the gamma-range local field potential (LFP) signal, suggesting that they may be involved in a particular local network mediating vascular control. We are currently pursuing this research direction through the use of simultaneous single-unit recordings inside the MR scanner. We have developed and acquired many of the necessary components (MR-compatible electrodes and microdrive, suitable RF coils, preamplifiers, cables, and filters) to achieve such simultaneous recording. A new postdoctoral fellow in the laboratory is currently working to understand the links between the activity fluctuations measured using fMRI and those observed in a host of neural measures, including the spiking of single cells. While the principal aim of this project is to understand the relationship of single cells with brain-wide fMRI networks, we anticipate that this analysis will give us perspectives on the nature of the local neurovascular relationship as well. The second area in which we have investigated the basis of the fMRI signal involves the manipulation of the basal forebrain, a small area that projects broadly to the cerebral cortex. We previously showed that reversibly inactivating the basal forebrain led to regional changes the global signal component of spontaneous fMRI activity (Turchi, Chang, et al.,2018). Our initial experiments inactivated portions of this structure in animals undergoing fMRI testing. They suggested that the basal forebrain is centrally involved in regulating spontaneous signals throughout the telencephalon, at least during rest. This effect is particularly pronounced during transitions of arousal, gauged by eye opening and closure. Through collaboration (Liu X et al. Nat Commun, 2018), we have also found that the spontaneous signals in the human cerebral cortex are likely also driven by basal forebrain input. We now plan to go further in this direction by combining fMRI with direct optogenetic stimulation of basal forebrain subregions. This manipulation will provide at least three different experimental opportunities. First, the local stimulation combined with fMRI mapping affords a new view of regional mapping view of basal forebrain projections. Second, control over basal forebrain connections may help understand mechanisms leading to fMRI functional connectivity and its relationship to arousal. Third, selective stimulation of the basal forebrain may help us to understand mechanisms of learning and plasticity.

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