Implementation of integrated computer control for X-ray material characterization systems

An integrated computer control for an X-ray K-Edge measurement system and an X-ray scan system was implemented. Field tests and various laboratory applications showed that they greatly facilitated the operator's control of the systems. In order to develop these control programs, device drivers and control classes were developed in C++ for several PC boards, including a motion control indexer (PC23 and AT6000), multi-channel analyzer (MCA) and frame grabber (DT3155). Each class encapsulates the necessary functions to control the underlying hardware, thus provides a tool for other programmers to rapidly develop new custom data acquisition programs. Device driver techniques under MS DOS, Windows 3.x /Windows 9x, Windows NT4.0 and Windows 2000 were introduced, compared and commented. Device drivers were developed for a MCA both under Windows 3.x /Windows 9x and Windows NT/Windows 2000 operating systems. These drivers can be easily modified to apply to other memory mapping devices and port I/O devices. Graphical interfaces using these hardware drivers and control classes were shown from the K-edge measurement system and from the X-ray scan system. In addition to hardware control, the graphical interface needed to display X-ray spectrum, X-ray real time image, status indications of the data acquisition, etc

Performing group-level functional image analyses based on homologous functional regions mapped in individuals

Functional MRI (fMRI) studies have traditionally relied on intersubject normalization based on global brain morphology, which cannot establish proper functional correspondence between subjects due to substantial intersubject variability in functional organization. Here, we reliably identified a set of discrete, homologous functional regions in individuals to improve intersubject alignment of fMRI data. These functional regions demonstrated marked intersubject variability in size, position, and connectivity. We found that previously reported intersubject variability in functional connectivity maps could be partially explained by variability in size and position of the functional regions. Importantly, individual differences in network topography are associated with individual differences in task-evoked activations, suggesting that these individually specified regions may serve as the localizer to improve the alignment of task-fMRI data. We demonstrated that aligning task-fMRI data using the regions derived from resting state fMRI may lead to increased statistical power of task-fMRI analyses. In addition, resting state functional connectivity among these homologous regions is able to capture the idiosyncrasies of subjects and better predict fluid intelligence (gF) than connectivity measures derived from group-level brain atlases. Critically, we showed that not only the connectivity but also the size and position of functional regions are related to human behavior. Collectively, these findings suggest that identifying homologous functional regions across individuals can benefit a wide range of studies in the investigation of connectivity, task activation, and brain-behavior associations. Author summary No two individuals are alike. The size, shape, position, and connectivity patterns of brain functional regions can vary drastically between individuals. While interindividual differences in functional organization are well recognized, to date, standard procedures for functional neuroimaging research still rely on aligning different subjects' data to a nominal average brain based on global brain morphology. We developed an approach to reliably identify homologous functional regions in each individual and demonstrated that aligning data based on these homologous functional regions can significantly improve the study of resting state functional connectivity, task-fMRI activations, and brain-behavior associations. Moreover, we showed that individual differences in size, position, and connectivity of brain functional regions are dissociable, and each can provide nonredundant information in explaining human behavior

Topological Fractionation of Resting-State Networks

Exploring topological properties of human brain network has become an exciting topic in neuroscience research. Large-scale structural and functional brain networks both exhibit a small-world topology, which is evidence for global and local parallel information processing. Meanwhile, resting state networks (RSNs) underlying specific biological functions have provided insights into how intrinsic functional architecture influences cognitive and perceptual information processing. However, topological properties of single RSNs remain poorly understood. Here, we have two hypotheses: i) each RSN also has optimized small-world architecture; ii) topological properties of RSNs related to perceptual and higher cognitive processes are different. To test these hypotheses, we investigated the topological properties of the default-mode, dorsal attention, central-executive, somato-motor, visual and auditory networks derived from resting-state functional magnetic resonance imaging (fMRI). We found small-world topology in each RSN. Furthermore, small-world properties of cognitive networks were higher than those of perceptual networks. Our findings are the first to demonstrate a topological fractionation between perceptual and higher cognitive networks. Our approach may be useful for clinical research, especially for diseases that show selective abnormal connectivity in specific brain networks

Resting-State Brain Organization Revealed by Functional Covariance Networks

BACKGROUND: Brain network studies using techniques of intrinsic connectivity network based on fMRI time series (TS-ICN) and structural covariance network (SCN) have mapped out functional and structural organization of human brain at respective time scales. However, there lacks a meso-time-scale network to bridge the ICN and SCN and get insights of brain functional organization. METHODOLOGY AND PRINCIPAL FINDINGS: We proposed a functional covariance network (FCN) method by measuring the covariance of amplitude of low-frequency fluctuations (ALFF) in BOLD signals across subjects, and compared the patterns of ALFF-FCNs with the TS-ICNs and SCNs by mapping the brain networks of default network, task-positive network and sensory networks. We demonstrated large overlap among FCNs, ICNs and SCNs and modular nature in FCNs and ICNs by using conjunctional analysis. Most interestingly, FCN analysis showed a network dichotomy consisting of anti-correlated high-level cognitive system and low-level perceptive system, which is a novel finding different from the ICN dichotomy consisting of the default-mode network and the task-positive network. CONCLUSION: The current study proposed an ALFF-FCN approach to measure the interregional correlation of brain activity responding to short periods of state, and revealed novel organization patterns of resting-state brain activity from an intermediate time scale

Quaternary folding in the south piedmont of central segment of Tianshan Mountains

The Tianshan Mountains are an important active structural belt in the interior of Eurasia. By integrated methods of surface geology survey and interpretation of seismic profiles, we distinguish fold scarps located at the south limb of the Kuqatawu anticline and the north limb of the Dongqiulitag anticline in the Kuqa rejuvenation foreland thrust belt, south piedmont of central segment of the Tian- shan Mountains. Fold scarp is a newly found structural phenomenon. Because of the bend of thrust plane and the movement of hanging wall above the thrust plane, the origi- nal horizontal deposits of hanging wall and their surface become a monocline structure, resulting from the separating and migration of the active and fixed axial surfaces. Meas- uring the geometry of fold scarp and using the data of age of the deformed deposits, the crustal shortening rate resulting from the deeply seated subsurface thrust is calculated. The crustal shortening rate reflected by the fold scarp located at the north limb of the Dngqiulitag anticline is (1␣0.1) mm/a. The fold scarps of the Dongqiulitag anticline and the Ku- qatawu anticline identify that the deformation process of the crustal compressive structures in the Kuqa area extends into the Late Quaternary