Functional magnetic resonance imaging (fMRI) is undeniably the workhorse for neuroscientists who want localized measurements of neural correlates of human behavior. However, recent studies have presented fMRI results that conflict with traditional invasive (direct) electrophysiological measurements of neural population responses: attention strongly modulates the fMRI response in primary visual cortex (V1) but only weakly modulates neural firing rates; fMRI responses in V1 predict perceptual states while only subtle aspects of direct recordings of V1 neural responses correlate with perception. An important step toward reconciling the differences between fMRI data and invasive electrophysiology is to obtain fMRI data that can map out the details of the local neural population code on a scale that is closer to that sampled by electrodes. The proposed experiments will use 7 Tesla fMRI with sub-millimeter resolution ? a spatial scale comparable to that of the local field potential in electrophysiology ? to determine how the spatial details of the neural population response in V1 depend on visual stimulus properties as well as perceptual state. Because input, output and local connections are segregated according to depth, the primary focus of this research is to dissociate signals at different cortical depths. Several recent literature reports show that the fMRI response amplitude is different at different cortical depths. However, it is not yet established whether depth-dependent fMRI actually reflects local neural network changes at different cortical depths. The following aims seek to verify that fMRI has differential laminar sensitivity that corresponds meaningfully to neural activity.
The first aim i s to validate layer-specific fMRI against known properties of the intrinsic neural network. While fMRI and electrophysiological measurements of V1 response modulation due to behavioral or perceptual processes (putative feedback processes) disagree, there has been ample demonstration of the agreement between fMRI and electrophysiological measurements of intrinsic neural responses such as contrast sensitivity or orientation selectivity. Two sets of experiments will therefore quantify the depth-dependent fMRI response to simple visual stimuli, validating the fMRI laminar profile against laminar profiles predicted by electrophysiology.
The second aim i s to study modulation of neural responses in V1 by visual information that is extracted over a larger spatial scale. Enhancement of V1 neural responses by global scene structure (figure/ground segmentation) and suppression of V1 neural responses by uniform texture (orientation-dependent surround suppression) differ importantly in the role of awareness in regulating the modulation in V1. We will quantify fMRI laminar profiles under these two different kinds of contextual modulation. Because both visual feature grouping and iso-orientation suppression are affected by neurological disorders such as autism and schizophrenia, validating a technique for monitoring these mechanisms of visual contextual modulation has utility in the clinical setting.
) Modern neuroscience has revealed that diseases and learning disabilities such as autism, schizophrenia, and dyslexia have their foundation in abnormal brain function, and that these abnormalities are as much about interconnectivity between brain regions as they are about the dysfunction of local neural networks. In order to develop and validate treatments for these diseases, we need a method of quantifying the separate contributions of local computations and long-range connections to a given brain region. Fortunately, these different types of computations are segregated according to cortical depth and therefore may be accessible to modern neuroimaging techniques. The proposed research will validate the use of functional magnetic resonance imaging to characterize local network states by separately visualizing the signal changes associated with neural computations at different cortical depths.
| Olman, Cheryl A; Bao, Pinglei; Engel, Stephen A et al. (2018) Hemifield columns co-opt ocular dominance column structure in human achiasma. Neuroimage 164:59-66 |
