Brain operates on a network level. Magnetic resonance imaging (MRI) provides structural and functional images noninvasively with large field of view and at high spatial resolution and thus assumes an extremely valuable role in studying brain networks. The objectives of this doctoral work were to develop and apply novel MRI methods on human and rodent brains, for in vivo and global assessments of functional brain networks at resting and task-evoked states. Firstly, the feasibility of passband balanced steady-state free precession (bSSFP) imaging for distortion-free and high-resolution resting-state fMRI (rsfMRI) was investigated. Resting-state networks (RSNs) derived from bSSFP images were shown spatially and spectrally comparable to those derived from conventional gradient-echo echo-planar imaging (GE-EPI) with considerable intra- and inter-subject reproducibility. High-resolution bSSFP corresponded well to the anatomical images, with RSNs exquisitely co-localized to gray matter. Furthermore, RSNs at areas of severe susceptibility were proved accessible including human anterior prefrontal cortex and rat piriform cortex. These findings demonstrated for the first time that passband bSSFP approach can be a promising alternative to GE-EPI for rsfMRI. It offers distortion-free and high-resolution RSNs and is potentially suited for high field studies. Secondly, to examine the macrovascular contributions to the spatial and spectral prosperities of resting-state networks, spin-echo echo-planar imaging (SE-EPI) with moderate diffusion weighting (DW) was proposed for rsfMRI. SE and DW suppressed the extravascular and intravascular contributions from macrovessels respectively. Significantly lower functional connectivity strength was observed in the posterior cingulate cortex of the default mode network derived from DW SE-EPI data comparing to that derived from SE-EPI, suggesting a confounding role played by the intravascular component from large veins, whereas no significant spectral difference was detected. Therefore, the DW SEEPI approach for rsfMRI may assist in better identifying and interpreting largescale brain networks with future improvement in temporal resolution by acceleration techniques and in sensitivity at higher field. Thirdly, rsfMRI was performed to evaluate the intrinsic functional networks in the corresponding anatomical visual brain connections traced by Mn-enhanced MRI (MEMRI). Strengths of resting-state functional connectivity appeared to couple with structural connectivity in MEMRI, demonstrating the sensitivity of these structural and functional connectivity MRI techniques for assessing the neuroarchitecture, neurophysiology and structural-functional relationships in the visual brain in vivo. Fourthly, the hypothesis that a regional activation identified via general linear model analysis of fMRI data reflects the summation of multiple distinct networks that carry different functional purposes was tested. Overlapping frontoparietal networks engaged in a simple single-digit multiplication task were found and their functional roles were evaluated through independent components analysis and contributive source analysis. Future studies incorporating different arithmetic tasks and resting state will shed more light upon how brain accomplishes arithmetic and more complex tasks in general. Lastly, benefiting from higher SNR, better spatial and temporal resolution at higher field, exploratory fMRI studies were conducted on rats at 7 T for in vivo assessments of 1) the effect of dark-rearing on postnatal visual development, 2) sound amplitude modulations and 3) sound frequency modulation sweep direction selectivity in auditory system. ( / published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

Thesis (M.S.)--University of Hawaii at Manoa, 2007. / Includes bibliographical references (leaves 50-51). / viii, 51 leaves, bound ill. (some col.) 29 cm

Thesis (Ph. D.)--Virginia Commonwealth University, 2007. / Prepared for: Dept. of Human Genetics. Bibliography: leaves 279 - 311. Also available online via the Internet.

published_or_final_version / Psychiatry / Master / Master of Philosophy

Brain maturation is an important factor in cognitive, emotional, behavioural and motor development during childhood and adolescence. This study uses multi-modal magnetic resonance imaging (MRI) techniques to assess neural representations of devel opment in both healthy and abnormally developing populations. A novel face emotion stimulus set, designed to assess distinct dimensions of facial emotion, particularly to assess the e ect of averted faces, is introduced in a pilot functional MRI study of an adult cohort. Results from this pilot study show that interactions between face direction and emotion can infuence which brain areas are recruited for emo- tion processing, suggesting that the neural correlates of judging facial emotion content are modulated by face direction. Facial emotion perception was assessed as a neural task to investigate dimensions of emotion processing, and emotion processing development, in a group of children and adolescents. A number of correlations were found between dimensions of the task and developmental measures such as age, pubertal development and intelligence. In particular, intelligence was shown to be positively associated with the increasing utilization of regions associated with cognitive control, such as the prefrontal cortex. A voxel-based morphometry (VBM) study explored potential structural correlates of adolescent development. Age was found to correlate with changes in local brain regions, however pubertal development was shown to be a more accurate measure of those changes. A diusion tensor imaging assessment of white matter using fractional anisotropy has demonstrated important developmental di erences in white matter be- tween males and females over childhood and adolescence. Findings also suggest diff erent relationships between intelligence and white matter for males and females. Developmental Coordination Disorder, a common childhood disorder characterised by deficits in learning and automating motor skills, was assessed as an example of ab normal brain development. VBM was used to show that kinematic metrics of a simple visuomotor task correlated with regional grey matter volumes.

Thesis (M. Eng.). / Written for the Dept. of Electrical and Computer Engineering. Title from title page of PDF (viewed 2008/01/14). Includes bibliographical references.

Thesis (doctoral)--Lund University, 1997. / Added t.p. with thesis statement inserted.

Thesis (doctoral)--Lund University, 1997. / Added t.p. with thesis statement inserted.

The brain activities are characterized by spontaneous and persistent irregular fluctuations in space and time. Criticality theory from statistical physics has been proposed as a principle to explain the variability in normal brain spontaneous activity and has suggested the functional benefits of variability, such as maximized dynamic range of response to stimuli and information capacity. In parallel, the brains show variability in other aspects, such as the structural heterogeneity across brain regions, the intra-individual variability across experimental trials, and the behavior difference across groups and individuals. The associations between the variability of spontaneous activities and these different types of structural, intra and inter-individual variabilities remain elusive. My doctoral study thus aimed to bridge the brain variability and the above-mentioned variations based on criticality theory and analysis of empirical data. As a preparatory analysis, we first collected evidence to prove criticality in human functional magnetic resonance imaging (fMRI) data. The advanced statistical criteria were used to exclude potential artefacts that can induce power-law scaling without the mechanism of criticality. In the first part of the study, we addressed methodological issue and tested whether several measures of either spatial or temporal complexity due to experimental limitations could be reliable proxy of spatiotemporal variability (related to criticality) in vivo. The high spatiotemporal resolutions of whole-cortex optical voltage imaging in mice brain during the waking up from anesthesia enabled simultaneous investigation of functional connectivity (FC), Multi-Scale Entropy (MSE, measure of temporal variability), Regional Entropy (RE, quantity of spatiotemporal variability) and the interdependency among them under different brain states. The results suggested that MSE and FC could be effective measures to capture spatiotemporal variability under limitation of imaging modalities applicable to human subjects. This study also lays methodological basis for the third study in this thesis. In the second study, we explored the interaction between spontaneous activity and evoked activity from mice brain imaging under whisker stimulus. The whisker stimulus will first evoke the local activation in sensory cortex and then trigger whole-cortex activity with variable patterns in different experimental trials. This trial-to-trial variability in the cortical evoked component was then attributed to the changes of ongoing activity state at stimulus onset. The study links ongoing activity variability and evoked activity variability, which further consolidates the association between ongoing activity and brain functions. In the third study, we measured the signal variability of the whole brain from resting state fMRI, and developed the multivariate pattern of cortical entropy, called entropy profile, as reliable and interpretable biomarker of individual difference in cognitive ability. We showed that the whole cortical entropy profile from resting- state fMRI is a robust personalized measure. We tested the predictive power for general and specific cognitive abilities based on cortical entropy profiles with out- of-sample prediction. Furthermore, we revealed the anatomical features underlying cross-region and cross-individual variations in cortical entropy profiles. This study provides new potential biomarker based on brain spontaneous variability which could benefit the applications in psychology and psychiatry studies. The whole study laid a foundation for brain criticality-/variability-based studies and applications and broadened our understanding of the associations between neural structures, functional dynamics and cognitive ability

The brain activities are characterized by spontaneous and persistent irregular fluctuations in space and time. Criticality theory from statistical physics has been proposed as a principle to explain the variability in normal brain spontaneous activity and has suggested the functional benefits of variability, such as maximized dynamic range of response to stimuli and information capacity. In parallel, the brains show variability in other aspects, such as the structural heterogeneity across brain regions, the intra-individual variability across experimental trials, and the behavior difference across groups and individuals. The associations between the variability of spontaneous activities and these different types of structural, intra and inter-individual variabilities remain elusive. My doctoral study thus aimed to bridge the brain variability and the above-mentioned variations based on criticality theory and analysis of empirical data. As a preparatory analysis, we first collected evidence to prove criticality in human functional magnetic resonance imaging (fMRI) data. The advanced statistical criteria were used to exclude potential artefacts that can induce power-law scaling without the mechanism of criticality. In the first part of the study, we addressed methodological issue and tested whether several measures of either spatial or temporal complexity due to experimental limitations could be reliable proxy of spatiotemporal variability (related to criticality) in vivo. The high spatiotemporal resolutions of whole-cortex optical voltage imaging in mice brain during the waking up from anesthesia enabled simultaneous investigation of functional connectivity (FC), Multi-Scale Entropy (MSE, measure of temporal variability), Regional Entropy (RE, quantity of spatiotemporal variability) and the interdependency among them under different brain states. The results suggested that MSE and FC could be effective measures to capture spatiotemporal variability under limitation of imaging modalities applicable to human subjects. This study also lays methodological basis for the third study in this thesis. In the second study, we explored the interaction between spontaneous activity and evoked activity from mice brain imaging under whisker stimulus. The whisker stimulus will first evoke the local activation in sensory cortex and then trigger whole-cortex activity with variable patterns in different experimental trials. This trial-to-trial variability in the cortical evoked component was then attributed to the changes of ongoing activity state at stimulus onset. The study links ongoing activity variability and evoked activity variability, which further consolidates the association between ongoing activity and brain functions. In the third study, we measured the signal variability of the whole brain from resting state fMRI, and developed the multivariate pattern of cortical entropy, called entropy profile, as reliable and interpretable biomarker of individual difference in cognitive ability. We showed that the whole cortical entropy profile from resting- state fMRI is a robust personalized measure. We tested the predictive power for general and specific cognitive abilities based on cortical entropy profiles with out- of-sample prediction. Furthermore, we revealed the anatomical features underlying cross-region and cross-individual variations in cortical entropy profiles. This study provides new potential biomarker based on brain spontaneous variability which could benefit the applications in psychology and psychiatry studies. The whole study laid a foundation for brain criticality-/variability-based studies and applications and broadened our understanding of the associations between neural structures, functional dynamics and cognitive ability