The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism.

Autism spectrum disorders (ASDs) represent a formidable challenge for psychiatry and neuroscience because of their high prevalence, lifelong nature, complexity and substantial heterogeneity. Facing these obstacles requires large-scale multidisciplinary efforts. Although the field of genetics has pioneered data sharing for these reasons, neuroimaging had not kept pace. In response, we introduce the Autism Brain Imaging Data Exchange (ABIDE)-a grassroots consortium aggregating and openly sharing 1112 existing resting-state functional magnetic resonance imaging (R-fMRI) data sets with corresponding structural MRI and phenotypic information from 539 individuals with ASDs and 573 age-matched typical controls (TCs; 7-64 years) (http://fcon_1000.projects.nitrc.org/indi/abide/). Here, we present this resource and demonstrate its suitability for advancing knowledge of ASD neurobiology based on analyses of 360 male subjects with ASDs and 403 male age-matched TCs. We focused on whole-brain intrinsic functional connectivity and also survey a range of voxel-wise measures of intrinsic functional brain architecture. Whole-brain analyses reconciled seemingly disparate themes of both hypo- and hyperconnectivity in the ASD literature; both were detected, although hypoconnectivity dominated, particularly for corticocortical and interhemispheric functional connectivity. Exploratory analyses using an array of regional metrics of intrinsic brain function converged on common loci of dysfunction in ASDs (mid- and posterior insula and posterior cingulate cortex), and highlighted less commonly explored regions such as the thalamus. The survey of the ABIDE R-fMRI data sets provides unprecedented demonstrations of both replication and novel discovery. By pooling multiple international data sets, ABIDE is expected to accelerate the pace of discovery setting the stage for the next generation of ASD studies.

RHIZOSCAN: A semiautomatic image processing system for characterization of the morphology and secondary metabolite concentration in hairy root cultures.

We describe the application of the newly developed RHIZOSCAN software for accurate morphological analysis and determination of overall and local secondary metabolite concentrations in two clones of Beta vulgaris throughout the growth period. Local secondary metabolite concentrations may be determined at any point in the root, and pigment gradients in each lateral root can be followed during culture and saved to the computer. Throughout the entire analysis process, an image appears in a graphical result window on the screen, which enables visual evaluation of the numerical output at each stage of the analysis. Biosynthetic data on concentrations obtained by image analysis were validated by spectrophotometric analysis. The importance of determining appropriate scanning and analysis conditions (scanning resolution, background color, threshold value, segmentation plane in the hue-saturation-intensity color system and pruning length) for obtaining accurate morphological measurements is examined and the means of fixing these parameters is described. Our results show that, using RHIZOSCAN, detailed and accurate information on root architecture and secondary metabolite concentrations can be obtained in a short time.

Human chromosome classification using multilayer perceptron neural network.

A multilayer perceptron (MLP) neural network (NN) has been studied for human chromosome classification. Only 10-20 examples were required for the MLP NN to reach its ultimate performance classifying chromosomes of 5 types. The empirical dependence of the entropic error on the number of examples was found to be highly comparable to the 1/t function. The principal component analysis (PCA) was used, both for network initialization and for feature reduction purposes. The PCA demonstrated the importance of retaining most of the image information whenever small training sets are used. The MLP NN classifier outperformed the Bayes piecewise classifier for all the cases tested. The MLP classifier was found to be almost unsusceptible to the ratio of the number of training vectors to the number of features, whereas the piecewise classifier was highly dependent on this ratio.

Performance consequences of two types of stereo picture compression.

Two algorithms for stereo picture compression were evaluated. According to one algorithm, consistent with the fusion theory of depth perception, the reduction of information in the two pictures was about equal. The other algorithm, consistent with the suppression theory of depth perception, was based on very deep compression of one picture and minimal reduction of information in the second picture. Subjects performed depth decisions and object decisions on the compressed picture. They were able to perform both tasks on the compressed pictures, though performance generally was worse than in the un-compressed control conditions. In both tasks performance was better for an uneven division of information between the two pictures. These results are consistent with the suppression theory of depth perception.

Prediction of effects of weather on image quality: preliminary results of model validation.

Using the atmospheric modulation transfer function area (MTFA) as a single-valued numerical criterion for image quality horizontally near the ground propagated through the atmosphere, a statistical study of atmospheric imaging data accumulated over a three-year period has led to the determination of regression coefficients with which to quantitatively predict image quality as a function of wavelength, over the 400-1000- nm wavelength region, according to weather forecast. Utilization of this procedure is simple: one plugs in expected values for wind speed, air temperature, and relative humidity in the regression coefficient expression for MTFA. The larger the expected MTFA, the better the expected image quality. Two sets of regression coefficient data have been obtained, one each for desert and nondesert climates, corresponding to summer and winter data here. Preliminary experimentation over a different line of sight indicates that the accuracy of the prediction is fairly reliable.

Projection-based geometrical feature extraction for computer vision: algorithms in pipeline architectures.

In this correspondence, some image transforms and features such as projections along linear patterns, convex hull approximations, Hough transform for line detection, diameter, moments, and principal components will be considered. Specifically, we present algorithms for computing these features which are suitable for implementation in image analysis pipeline architectures. In particular, random access memories and other dedicated hardware components which may be found in the implementation of classical techniques are not longer needed in our algorithms. The effectiveness of our approach is demonstrated by running some of the new algorithms in conventional short-pipelines for image analysis. In related papers, we have shown a pipeline architecture organization called PPPE (Parallel Pipeline Projection Engine), which unleashes the power of projection-based computer vision, image processing, and computer graphics. In the present correspondence, we deal with just a few of the many algorithms which can be supported in PPPE. These algorithms illustrate the use of the Radon transform as a tool for image analysis.

Handling memory overflow in connected component labeling applications.

The storage requirements for component labeling and feature extraction operations are unknown a priori. Whenever large images are processed, many labels, and thus a large amount of storage, may be required, making hardware implementation difficult. The proposed labeling procedure eliminates memory overflow by enabling the reuse of memory locations in which features of nonactive labels had been stored. The storage requirement for the worst case conditions is analyzed and is shown to be realizable. The basic procedure can be implemented in two modes, an interrupted mode or a parallel mode. A hardware design is presented.