Abstract: Functional magnetic resonance imaging signals, in addition to reflecting neuronal response, also contain physiological variances. These factors may introduce variability into blood oxygen level-dependent (BOLD) activation results, particularly in different population groups. In this study, we hypothesized that the amplitude as well as the spatial extent of BOLD activation could be improved after minimizing the variance caused by the neurovascular and anatomical factors. Subjects were scanned while they performed finger tapping and digit-symbol substitution tasks (DSSTs). Partial volume and neurovascular effects were estimated on a voxelwise basis using subjects' own gray matter volume (GMV), breath holding (BH), and amplitude of low-frequency fluctuation (ALFF). The results showed that all individual's GMV, BH, and ALFF could significantly predict motor and DSST activations in a voxelwise manner. Whole-brain analyses were conducted to regress out the anatomical and neurovascular information. Differential maps (obtained using t-test) indicated that the adjustment tended to suppress activation in regions that were near vessels such as midline cingulate gyrus, bilateral anterior insula, and posterior cerebellum. These results suggest that voxelwise adjustment using GMV and neurovascular parameters can minimize structural and physiological variances among individuals and be used for quantitative comparisons.
Abstract: The present study reviewed voxel-based morphometry (VBM) studies on high-risk individuals with schizophrenia, patients experiencing their first-episode schizophrenia (FES), and those with chronic schizophrenia. We predicted that gray matter abnormalities would show progressive changes, with most extensive abnormalities in the chronic group relative to FES and least in the high-risk group.
Abstract: The importance of the cerebellum in coordinates of movement has been established by lesion studies. However, there is no clear understanding of whether there is consistent activation in cerebellum across various motor task complexities or how different parts of the cerebellum contribute to finger coordinates in dexterous manipulation. This article reviews imaging studies with data from healthy subjects. A mini meta-analysis using label-based and activation likelihood estimation (ALE) methods reveals that ipsilateral anterior and vermis regions of the cerebellum were consistently activated across various dexterous movement complexities and were associated with finger and hand movement.
Abstract: Schizophrenia is thought to be a mental disorder caused by the disconnection of brain regions. Cumulative evidence of white matter deficit in patients with schizophrenia has been reported using voxel-based morphometry (VBM), but these studies have not been quantitatively reviewed. In the study reported herein, we used activation likelihood estimation (ALE) analysis to quantitatively estimate focal white matter abnormalities in patients with schizophrenia. Seventeen studies that compared the white matter deficit of patients with schizophrenia and healthy controls were ascertained. The frontal white matter regions and internal capsule revealed consistent white matter reduction in patient groups relative to healthy controls, suggesting a clear focal white matter deficit in patients with schizophrenia. These results support the macro-circuit theory of white matter change in schizophrenia.
Abstract: The Fist-Edge-Palm (FEP) task is a motor sequencing task that is widely used in neurological examination. Deficits in this task are believed to reflect impairment in the frontal lobe regions. However, two recent functional brain imaging studies of the FEP task using conventional subtraction analysis failed to demonstrate FEP-induced activation in the prefrontal cortex (PFC), which contradicts existing neuropsychological literature. In this study, psychophysiological interaction (PPI) analysis was used to reanalyze our previous neuroimaging dataset from 10 healthy subjects in order to evaluate the changes of functional connectivity between the sensorimotor cortex and the prefrontal regions during the performances of the FEP task relative to simple motor control tasks. The PPI analysis revealed significantly increased functional connectivity between bilateral sensorimotor cortex and the right inferior and middle frontal cortex during the performance of the FEP task compared with the control tasks. However, regional signal changes showed no significant activation differences in these prefrontal regions. These results provide evidence supporting the involvement of the frontal lobe in the performance of the FEP task, and suggest a role of regulation, rather than direct participation, of the prefrontal cortex in the execution of complex motor sequence tasks such as the FEP task.
Abstract: Conventional neuroimaging methods primarily focus on functional localization, through which specific cognitive functions are localized to specific brain regions. However, fully understanding the human brain function requires characterization of functional integration within and among the functionally specialized regions in addition to functional localization. Functional connectivity and effective connectivity analyses have been developed to investigate functional integration in human brain. Several approaches for modeling functional connectivity and effective connectivity, including the time-series correlation, psychophysiological interaction (PPI), structural equation modeling (SEM), dynamic casual modeling (DCM), and diffusion tensor imaging (DTI) are reviewed. The applications of functional connectivity analysis to the studies of object representation, motor coordinate, language, and autism are demonstrated. Functional connectivity study will highly enrich our knowledge about the dynamic integration in the human brain.
