Community structure and modularity in networks of correlated brain activity

Functional connectivity patterns derived from neuroimaging data may be represented as graphs or networks, with individual image voxels or anatomically-defined structures representing the nodes, and a measure of correlation between the responses in each pair of nodes determining the edges. This explicit network representation allows network-analysis approaches to be applied to the characterization of functional connections within the brain. Much recent research in complex networks has focused on methods to identify community structure, i.e. cohesive clusters of strongly interconnected nodes. One class of such algorithms determines a partition of a network into 'sub-networks' based on the optimization of a modularity parameter, thus also providing a measure of the degree of segregation versus integration in the full network. Here, we demonstrate that a community structure algorithm based on the maximization of modularity, applied to a functional connectivity network calculated from the responses to acute fluoxetine challenge in the rat, can identify communities whose distributions correspond to anatomically meaningful structures and include compelling functional subdivisions in the brain. We also discuss the biological interpretation of the modularity parameter in terms of segregation and integration of brain function.     

Measurement of the B(+) production cross section in pp collisions at sqrt[s]=7 TeV

Measurements of the total and differential cross sections dσ/dp(T)(B) and dσ/dy(B) for B(+) mesons produced in pp collisions at sqrt[s]=7 TeV are presented. The data correspond to an integrated luminosity of 5.8 pb(-1) collected by the CMS experiment operating at the LHC. The exclusive decay B(+)→J/ψK(+), with J/ψ→μ(+)μ(-), is used to detect B(+) mesons and to measure the production cross section as a function of p(T)(B) and y(B). The total cross section for p(T)(B)>5 GeV and |y(B)|<2.4 is measured to be 28.1±2.4±2.0±3.1 μb, where the first uncertainty is statistical, the second is systematic, and the last is from the luminosity measurement.     

A study of reaction rates of (n, f ) , (n, \gamma) and (n, 2n) reactions in natU and 232Th by the neutron fluence produced in the graphite set-up (GAMMA-3) irradiated by 2.33 GeV deuteron beam

Spallation neutrons produced in the collision of a 2.33GeV deuteron beam with a large lead target are moderated by a thick graphite block surrounding the target and used to activate the radioactive samples of ^natU and Th put at three different positions, identified as holes “a”, “b” and “c” in the graphite block. Rates of the (n, f), (n, $ \gamma$ and (n, 2n) reactions in the two samples are determined using the gamma spectrometry. The ratios of the experimental reaction rates, R (n, 2n)/R (n, f), for ²³²Th and ^natU are estimated in order to understand the role of the (n, x n) kind of reactions in Accelerator-Driven Sub-critical Systems. For the Th-sample, the ratio is ～ 54 (10)% in the case of hole “a” and ～ 95 (57)% in the case of hole “b” compared to 1.73(20)% for hole “a” and 0.710(9)% for hole “b” in the case of the ^natU sample. Also the ratio of fission rates in uranium to thorium, ^natU (n, f)/ ²³²Th (n, f), is ～ 11.2 (17) in the case of hole “a” and 26.8(85) in hole “b”. Similarly, the ratio ²³⁸U (n, 2n)/ ²³²Th (n, 2n) is 0.36(4) for hole “a” and 0.20(10) for hole “b” showing that ²³²Th is more prone to the (n, x n) reaction than ²³⁸U . All the experimental reaction rates are compared with the simulated ones by generating neutron fluxes at the three holes from MCNPX 2.6c and making use of the LA150 library of cross-sections. The experimental and calculated reaction rates of all the three reactions are in reasonably good agreement. The transmutation power, P _norm as well as P _norm/P _beam of the set-up is estimated using the reaction rates of the (n, $ \gamma$ and (n, 2n) reactions for both the samples in the three holes and compared with some of the results of the “Energy plus Transmutation” set-up and TARC experiment.     

Pharmacological modulation of functional connectivity: the correlation structure underlying the phMRI response to d-amphetamine modified by selective dopamine D3 receptor antagonist SB277011A

Pharmacological MRI (phMRI) experiments utilise fMRI time series methods to map the central effect of pharmaceutical compounds. The typical univariate maps may, however, integrate the effects of several different neurotransmitter systems or underlying mechanisms. The results may thus be spatially and/or mechanistically nonspecific. Intersubject correlation analysis based on the phMRI response amplitude can more directly identify patterns of functional connectivity underlying the central effects of an acutely administered compound. In this article, we extend this approach to experiments where the effects of one compound in modulating the response to another are of interest. Specifically, we show a modulation of the correlation structure of a probe compound (d-amphetamine) by pretreatment with the selective dopamine D3 receptor antagonist SB277011A in the rat. The strongest modifications in the correlation patterns occurred in connection with the ventral tegmental area, the source of mesolimbic dopamine projections and a key substrate in the reward system.     

Application of Mie theory to determine the structure of spheroidal scatterers in biological materials

We present here the results of a numerical study on light scattering from nonspherical particles with relevance to detecting precancerous states in epithelial tissues. In previous studies of epithelial cell nuclei, the experimental light scattering data have been analyzed by comparison with Mie theory. However, given the spheroidal shape of many cell nuclei, the validity of this assumption demands a thorough investigation. We investigate this assumption by using the T-matrix method to model light scattered from spheroids with parameters relevant to epithelial cell nuclei. In our previous studies, we have developed a data analysis procedure that extracts the oscillatory component of the angular-scattering distribution for an ensemble of epithelial cell nuclei for comparison with Mie theory. We demonstrate that application of our analysis procedure to the predictions of the T-matrix method for spheroids, oriented such that their axis of symmetry is aligned with the incident light propagation direction, generally yields the spheroid dimension that is transverse to the incident light propagation direction with subwavelength accuracy.     

Spatial and frequency domain effects of defects in 1D photonic crystal

The aim of this paper is to present the analysis of influence of defects in 1D photonic crystal (PC) on the density of states and simultaneously spontaneous emission, in both spatial and frequency domains. In our investigations we use an analytic model of 1D PC with defects. Our analysis reveals how presence of a defect causes a defect mode to appear. We show that a defect in 1D PC has local character, being negligible in regions of PC situated far from the defected elementary cell. We also analyze the effect of multiple defects, which lead to photonic band gap splitting.     

Improving motion estimation by accounting for local image distortion

Cardiac elastography is a useful diagnostic technique for detection of heart function abnormalities, based on analysis of echocardiograms. The analysis of the regional heart motion allows assessing the extent of myocardial ischemia and infarction. In this paper, a new two-stage algorithm for cardiac motion estimation is proposed, where the data is taken from a sequence of 2D echocardiograms. The method combines the advantages of block-matching and optical flow techniques. The first stage employs a standard block-matching algorithm (sum of absolute differences) to provide a displacement estimate with accuracy of up to one pixel. At the second stage, this estimate is corrected by estimating the parameters of a local image transform within a test window. The parameters of the image transform are estimated in the least-square sense. In order to account for typical heart motions, like contraction/expansion, translation and rotation, a local affine model is assumed within the test window. The accuracy of the new algorithm is evaluated using a sequence of 500 grayscale B-mode images, which are generated as distorted, but known copies of an original ROI, taken from a real echocardiogram. The accuracy of the motion estimation is expressed in terms of errors: maximum absolute error, root-mean-square error, average error and standard deviation. The errors of the proposed algorithm are compared with these of the known block-matching technique with cross-correlation and interpolation in the sub-pixel space. Statistical analysis of the errors shows that the proposed algorithm provides more accurate estimates of the heart motion than the cross-correlation technique with interpolation in the sub-pixel space.     

Time-resolved analysis of the X-ray emission of femtosecond-laser-produced plasmas in the 1.5-keV range

Recent experimental results on ion beams produced in high-intensity laser–solid interactions indicate the presence of very intense electric fields in the target. This suggests the possibility of efficiently heating a solid material by means of the fast electrons created during the laser–solid interactions and trapped in the target, rather than by the laser photons themselves. We tested this mechanism by irradiating very small cubic aluminum targets with the LULI 100-TW, 300-fs laser at 1.06-m wavelength. X-ray spectra were measured with an ultra-fast streak camera, coupled to a conical Bragg crystal, providing spectra in the 1.5-keV range with high temporal and spectral resolution. The results indicate the creation of a hot plasma, but a very low coupling between the rapid electrons and the solid. A tentative explanation, in agreement with other experimental results and with preliminary particle-in-cell (PIC) simulations, points out the fatal role of the laser prepulse. PACS 52.50.Jm; 52.38.Ph; 52.38.Kd     

Evidence for the decay D0-->K(-)pi(+)pi(-)e(+)nu(e)

Using a 281 pb{-1} data sample collected at the psi(3770) with the CLEO-c detector, we present the first absolute branching fraction measurement of the decay D0-->K(-)pi(+)pi(-)e(+)nu(e) at a statistical significance of about 4.0 standard deviations. We find 10 candidates consistent with the decay D0-->K(-)pi(+)pi(-)e(+)nu(e). The probability that a background fluctuation accounts for this signal is less than 4.1 x 10{-5}. We find B(D0-->K(-)pi(+)pi(-)e(+)nu(e)) = [2.8{-1.1}{+1.4}(stat)+/-0.3(syst)]x10{-4}. By restricting the invariant mass of the hadronic system to be consistent with K1(1270), we obtain the product of branching fractions B(D{0}-->K{1}{-}(1270)e{+}nu{e})xB(K1-(1270)-->K{-}pi{+}pi{-})=[2.5{-1.0}{+1.3}(stat)+/-0.2(syst)]x10{-4}. Using B(K1-(1270)-->K{-}pi{+}pi{-})=(33+/-3)%, we obtain B(D{0}-->K{1}{-}(1270)e{+}nu{e})=[7.6{-3.0}{+4.1}(stat)+/-0.6(syst)+/-0.7]x10{-4}. The last error accounts for the uncertainties in the measured K1-(1270)-->K{-}pi{+}pi{-} branching fractions.     

Evidence for two energy scales in the superconducting state of optimally doped (Bi,Pb)2(Sr,La)2CuO6+delta

We use angle-resolved photoemission spectroscopy to investigate the energy gap(s) in (Bi,Pb)2(Sr,La)2CuO6+delta. We find that the spectral gap has two components in the superconducting state: a superconducting gap and pseudogap. Differences in their momentum and temperature dependence suggest that they represent two separate energy scales. Spectra near the node reveal a sharp peak with a small gap below T(c) that closes at T(c). Near the antinode, spectra are broad with a large energy gap of approximately 40 meV above and below T(c). The latter spectral shape and gap magnitude are almost constant across T(c), indicating that the pseudogap state coexists with the superconducting state below T(c), and it dominates spectra around the antinode. We speculate that the pseudogap state competes with the superconductivity by diminishing spectral weight in antinodal regions, where the superconducting gap is largest.