Model-free functional MRI analysis based on unsupervised clustering

AbstractConventional model-based or statistical analysis methods for functional MRI (fMRI) are easy to implement, and are effective in analyzing data with simple paradigms. However, they are not applicable in situations in which patterns of neural response are complicated and when fMRI response is unknown. In this paper the “neural gas” network is adapted and rigourosly studied for analyzing fMRI data. The algorithm supports spatial connectivity aiding in the identification of activation sites in functional brain imaging. A comparison of this new method with Kohonen’s self-organizing map and with a fuzzy clustering scheme based on deterministic annealing is done in a systematic fMRI study showing comparative quantitative evaluations. The most important findings in this paper are: (1) both “neural gas” and the fuzzy clustering technique outperform Kohonen’s map in terms of identifying signal components with high correlation to the fMRI stimulus, (2) the “neural gas” outperforms the two other methods with respect to the quantization error, and (3) Kohonen’s map outperforms the two other methods in terms of computational expense. The applicability of the new algorithm is demonstrated on experimental data

Multiscale investigations in a mesoscale catchment ? hydrological modelling in the Gera catchment

International audienceThe application of the hydrological process-oriented model J2000 (J2K) is part of a cooperation project between the Thuringian Environmental Agency (Thüringer Landesanstalt für Umwelt und Geologie ? TLUG) and the Department of Geoinformatics of the Friedrich-Schiller-University Jena focussing on the implementation of the EU water framework directive (WFD). In the first project phase J2K was parametrised and calibrated for a mesoscale catchment to quantify if it can be used as hydrological part of a multi-objective tool-box needed for the implementation of the WFD. The main objectives for that pilot study were: The development and application of a suitable distribution concept which provide the spatial data basis for various tasks and which reflects the specific physiogeographical variability and heterogeneity of river basins adequately. This distribution concept should consider the following constraints: The absolute number of spatial entities, which forms the basis for any distributive modelling should be as small as possible, but the spatial distributed factors, which controls quantitative and qualitative hydrological processes should not be generalised to much. The distribution concept of hydrological response units HRUs (Flügel, 1995) was selected and enhanced by a topological routing scheme (Staudenrausch, 2001) for the simulation of lateral flow processes. J2K should be calibrated for one subbasin of the pilot watershed only. Then the parameter set should be used on the other subbasins (referred as transfer basins) to investigate and quantify the transferability of a calibrated model and potential spatial dependencies of its parameter set. In addition, potential structural problems in the process description should be identified by the transfer to basins which show a different process dominance as the one which was used for calibration does. Model calibration and selection of efficiency criteria for the quantification of the model quality should be based on a comprehensive sensitivity and uncertainty analysis (Bäse, 2005) and multi-response validations with independent data sets (Krause and Flügel, 2005) carried out in advance in the headwater part of the calibration basin. To obtain good results in the transfer basins the calibrated parameter set could be adjusted slightly. This step was considered as necessary because of specific constraints which were not of significant importance in the calibration basin. This readjustment should be carried out on parameters which show a sensitive reaction on the identified differences in the environmental setup. Potential scaling problems of the process description, distribution concept or model structure should be identified by the comparison of the modelling results obtained in a small headwater region of the calibration basin with observed streamflow to find out if the selected efficiency measures show a significant change

Determining and interpreting correlations in lipidomic networks found in glioblastoma cells

Background: Intelligent and multitiered quantitative analysis of biological systems rapidly evolves to a key technique in studying biomolecular cancer aspects. Newly emerging advances in both measurement as well as bio-inspired computational techniques have facilitated the development of lipidomics technologies and offer an excellent opportunity to understand regulation at the molecular level in many diseases. Results: We present computational approaches to study the response of glioblastoma U87 cells to gene- and chemo-therapy. To identify distinct biomarkers and differences in therapeutic outcomes, we develop a novel technique based on graph-clustering. This technique facilitates the exploration and visualization of co-regulations in glioblastoma lipid profiling data. We investigate the changes in the correlation networks for different therapies and study the success of novel gene therapies targeting aggressive glioblastoma. Conclusions: The novel computational paradigm provides unique “fingerprints” by revealing the intricate interactions at the lipidome level in glioblastoma U87 cells with induced apoptosis (programmed cell death) and thus opens a new window to biomedical frontiers. Background Glioblastoma are highly invasive brain tumors. Th

The Hutlets - a biorthogonal wavelet family and their high speed implementation with RNS, multiplier-free, perfect reconstruction QMF

The relationship between wavelets, Laplace pyramids and QMF are now well established. 1--3 In recent years biorthorgonal wavelets have become of increased interest because, compared with orthogonal wavelets, they are symmetric and linear phase. In this paper the Hut y function 4 is used as a scaling function (father wavelet) to construct a biorthogonal wavelet family, we call Hutlets. A realization with perfect reconstruction, multiplier- free quadrature mirror filters using RNS technic is proposed. The approximation-filter is a CIC lowpass, the detail-filter is a CHPC highpass, and the reconstruction filters are IIRs. Exact pole-zero annihilation is guaranteed by implementing polynomial filters, over an integer ring, in the residue arithmetic system (RNS). Since CIC and CHPC designs rely on the exact annihilation of selected poles-zeros, a new facilitating technology is required which is fast, compact, and numerically exact. How this can be achieved is the thrust of this paper. ..

Comparison of different efficiency criteria for hydrological model assessment

The evaluation of hydrologic model behaviour and performance is commonly made and reported through comparisons of simulated and observed variables. Frequently, comparisons are made between simulated and measured streamflow at the catchment outlet. In distributed hydrological modelling approaches, additional comparisons of simulated and observed measurements for multi-response validation may be integrated into the evaluation procedure to assess overall modelling performance. In both approaches, single and multi-response, efficiency criteria are commonly used by hydrologists to provide an objective assessment of the "closeness" of the simulated behaviour to the observed measurements. While there are a few efficiency criteria such as the Nash-Sutcliffe efficiency, coefficient of determination, and index of agreement that are frequently used in hydrologic modeling studies and reported in the literature, there are a large number of other efficiency criteria to choose from. The selection and use of specific efficiency criteria and the interpretation of the results can be a challenge for even the most experienced hydrologist since each criterion may place different emphasis on different types of simulated and observed behaviours. In this paper, the utility of several efficiency criteria is investigated in three examples using a simple observed streamflow hydrograph

Pipelined Hogenauer Cic Filters Using Field-Programmable Logic And Residue Number System

Field-Programmable Logic (FPL) is on the verge of revolutionizing digital signal processing (DSP) in the manner that programmable DSP microprocessors did nearly two decades ago. While FPL densities and performance have steadily improved to the point where some DSP solutions can be integrated into a single FPL chip, they still have limited use in high-precision high-bandwidth applications. In this paper it is shown that in such cases, the residue number system (RNS) can be an enabling technology. The design of a high-decimation rate digital filter is presented which demonstrates the RNS-FPL synergy

Frequency Sampling Filters With Algebraic Integers

Algebraic integers have been proven beneficial to DFT and non-recursive FIR filter designs [2, 4] since algebraic integers can be dense in C, resulting in short word width, high speed designs. This paper uses another property of algebraic integers: algebraic integers can produce exact pole zero cancellation pairs that are used in recursive FIR, frequency sampling filter designs

Tree�dependent and topographic independent component analysis for fMRI analysis

Recently, a new paradigm in ICA emerged, that of finding ldquoclustersrdquo of dependent components. This striking philosophy found its implementation in two new ICA algorithms: tree–dependent and topographic ICA. Applied to fMRI, this leads to the unifying paradigm of combining two powerful exploratory data analysis methods, ICA and unsupervised clustering techniques. For the fMRI data, a comparative quantitative evaluation between the two methods, tree–dependent and topographic ICA was performed. The comparative results were evaluated based on (1) correlation and associated time–courses and (2) ROC study. It can be seen that topographic ICA outperforms all other ICA methods including tree–dependent ICA for 8 and 9 ICs. However, for 16 ICs topographic ICA is outperformed by both FastICA and tree–dependent ICA (KGV) using as an approximation of the mutual information the kernel generalized variance