Layer-Specific Connectivity Analysis with High-Resolution Functional MRI in Human Brain
Type of DegreePhD Dissertation
DepartmentElectrical and Computer Engineering
Restriction TypeAuburn University Users
MetadataShow full item record
Functional magnetic resonance imaging (fMRI) has been increasingly used for understanding the human brain connectome. In this work, we utilized high-resolution fMRI to investigate the sensitivity of layer-specific connectivity methods, including functional connectivity (FC) and effective connectivity (EC), to connectional architecture at sub-millimeter spatial scale under different human brain states. The human neocortical gray matter contains cytoarchitectonically distinct layers, with notable differences in their structural connectivity with the rest of the brain. While this has traditionally been done using invasive techniques, recent improvements in the spatial resolution of anatomical and functional MRI may enable non-invasive investigation of the connectional architecture at the laminar level. Before the connectivity analysis, we applied a surface-based laminar analysis pipeline to process high-resolution, sub-millimeter MRI data obtained at 7T, and to delineate different layers of the human cortex. Because of the inter-subject and spatial variability of the hemodynamic response function (HRF), we performed blind deconvolution of vertex-based fMRI data to obtain underlying later neural signals from all layers. We demonstrated that the post-deconvolution connectivity analysis in the latent neural space aligned more closely with the underlying anatomical connections compared to connectivity obtained from original fMRI data. Using high-resolution resting state fMRI, we tested general hypotheses. First, given that functional connectivity is anchored and constrained by the structural connectome, we hypothesized that pathways between different layers, which have been shown to have a structural basis in invasive studies must have higher functional (synchronized and undirected) connectivity inferred from layer-resolved fMRI. Second, unidirectional anatomical projections at the layer level, which support feedback and feedforward interactions must be inferred using effective (directional, time-lagged) connectivity derived from layer resolved fMRI. We found these specific results in support of the first hypothesis: 1) FC between the entire thalamus and cortical layers I and VI was significantly stronger than between the thalamus and other layers. Further, FC between somatosensory thalamus (ventral posterolateral nucleus, VPL) and layers IV, VI of the primary somatosensory cortex were stronger than with other layers; 2) Inter-hemispheric cortico-cortical FC between homologous regions in superficial layers (layer I-III) was stronger compared to deep layers (layer V-VI). These findings are in agreement with structural connections inferred from previous invasive studies. These findings demonstrate for the first time that resting state fMRI is sensitive to structural connections between cortical layers, specifically in thalamocortical and cortico-cortical networks. In order to test the second hypothesis, we propose an experimental and analysis framework, which enables noninvasive functional characterization of layer-specific cortical microcircuits. Specifically, we illustrate this framework by characterizing layer-specific directional functional pathways in the corticogeniculate network of the human visual system by obtaining sub-millimeter fMRI at 7T using a task that engages the magnocellular pathway between LGN and the primary visual cortex. Our results showed that: (i) center-surround inhibition in magnocellular neurons within LGN (lateral geniculate nucleus) is detectable using localized fMRI responses within LGN; (ii) feedforward (LGN→ Layers VI/IV, Layer IV→ Layer VI) and feedback (Layer VI→ LGN) functional pathways, known to exist from invasive animal studies, can be inferred using dynamic directional connectivity models of fMRI and could potentially explain the mechanism underlying center-surround inhibition as well as gain control by Layer-VI in the human visual system. Our framework is domain-neutral, and could potentially be employed to investigate the layer-specific cortical microcircuits in other systems related to cognition, memory, and language. In summary, we demonstrate layer-specific connectivity analysis with high-resolution functional MRI obtained at 7T is a powerful non-invasive technique to unveil the connectional architecture at submillimeter spatial scale in the human brain.