The Neural Underpinnings of Functional MRI Networks

National Institute Of Mental Health

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Abstract

The technological advance that has likely had the greatest impact on our understanding of the operation of the human brain is functional magnetic resonance imaging (fMRI). Its remarkable capacity to look inside the head and view not only the structure of the brain, but its function, serves both basic and clinical research programs. 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, 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 focus on the study of neurovascular coupling per se, we do undertake experiments that bring new insights into the interpretation of the hemodynamic fMRI signal. For example, 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 the past year, we have made headway on understanding the link between a single neurons firing pattern and the blood-based activity measured throughout the brain. In one recently published study (Zaldivar et al, 2022, PNAS) we investigated the relationship of spontaneous single-unit activity to concurrently measured fMRI signals. In effect, we were able to use brain-wide fMRI to characterize the spontaneous firing of neurons within a local population. This required the simultaneous collection of single-unit and fMRI responses inside the MR scanner. As the technical hurdles associated with this type of work are immense, we needed to develop and acquire MR-compatible electrodes, microdrive, suitable RF coils, preamplifiers, cables, and filters to achieve such simultaneous recording. In the past year, we have discovered that, in contrast to the naturalistic visual responses described in the first study, the fMRI mapping of spontaneous activity is more homogeneous and more restricted across cortical and subcortical areas. In a related study more directly related to natural vision, we have also combined single unit and whole-brain fMRI to study the functional composition of local neural populations, in this case during the viewing of natural movies (Park et al, 2022, Sci Adv). In that study, we came to the surprising conclusion that functionally distinct regions of the visual cortex, which are generally believed to divide their labor in the analysis of a visual scene, have similar mixtures of neurons whose functional specialization varies greatly. Our study came to this conclusion after departing from the standard mode of showing isolated images onto a blank screen. Instead, we tested subjects during the free viewing of naturalistic movies. We found that neighboring neurons, all nominally selective for faces, respond to very different types of features under these conditions. Furthermore, by comparing their response profiles to that of voxels throughout the brain, we found neurons within a local population showed a diverse range of correpondences with networks across the brain. The implications of these findings is that, under natural modes of vision, the visual cortex is not composed of discrete, functionally homogeneous areas that process stimuli in a stepwise fashion. Instead, more broadly specialized regions are pervaded by parallel functional subnetworks, which contribute to the functioning of multiple brain areas. This finding contradicts the commonly held view that the fundamental organization of the visual brain is marked by strict segregation of function, which is a critical assumption for many experiments. Together, these two studies provide new insights into the nature of fMRI responses, including the local neurovascular relationship, as well as the network layout principles of high-level vision.