The effects of physiologically plausible connectivity structure on local and global dynamics in large scale brain models.

Functionally relevant large scale brain dynamics operates within the framework imposed by anatomical connectivity and time delays due to finite transmission speeds. To gain insight on the reliability and comparability of large scale brain network simulations, we investigate the effects of variations in the anatomical connectivity. Two different sets of detailed global connectivity structures are explored, the first extracted from the CoCoMac database and rescaled to the spatial extent of the human brain, the second derived from white-matter tractography applied to diffusion spectrum imaging (DSI) for a human subject. We use the combination of graph theoretical measures of the connection matrices and numerical simulations to explicate the importance of both connectivity strength and delays in shaping dynamic behaviour. Our results demonstrate that the brain dynamics derived from the CoCoMac database are more complex and biologically more realistic than the one based on the DSI database. We propose that the reason for this difference is the absence of directed weights in the DSI connectivity matrix.

An Efficient Segmentation Method for Ultrasound Images based on a Semi-supervised Approach and Patch-based Features

Segmenting ultrasound images is a challenging problemwhere standard unsupervised segmentation methods such asthe well-known Chan-Vese method fail. We propose in thispaper an efficient segmentation method for this class ofimages. Our proposed algorithm is based on asemi-supervised approach (user labels) and the use ofimage patches as data features. We also consider thePearson distance between patches, which has been shown tobe robust w.r.t speckle noise present in ultrasoundimages. Our results on phantom and clinical data show avery high similarity agreement with the ground truthprovided by a medical expert.

The wound watch: an objective staging system for wounds in the diabetic (db/db) mouse model.

As in cancer biology, in wound healing there is a need for objective staging systems to decide for the best treatment and predictors of outcome. We developed in the diabetic (db/db) wound healing model, a staging system, the "wound watch," based on the quantification of angiogenesis and cell proliferation in open wounds. In chronic wounds, there is often a lack of cellular proliferation and angiogenesis that leads to impaired healing. The wound watch addresses this by quantifying the proliferative phase of wound healing in two dimensions (cellular division and angiogenesis). The results are plotted in a two-dimensional graph to monitor the course of healing and compare the response to different treatments.

Synchronizability of EEG-Based Functional Networks in Early Alzheimer's Disease.

Recently graph theory and complex networks have been widely used as a mean to model functionality of the brain. Among different neuroimaging techniques available for constructing the brain functional networks, electroencephalography (EEG) with its high temporal resolution is a useful instrument of the analysis of functional interdependencies between different brain regions. Alzheimer's disease (AD) is a neurodegenerative disease, which leads to substantial cognitive decline, and eventually, dementia in aged people. To achieve a deeper insight into the behavior of functional cerebral networks in AD, here we study their synchronizability in 17 newly diagnosed AD patients compared to 17 healthy control subjects at no-task, eyes-closed condition. The cross-correlation of artifact-free EEGs was used to construct brain functional networks. The extracted networks were then tested for their synchronization properties by calculating the eigenratio of the Laplacian matrix of the connection graph, i.e., the largest eigenvalue divided by the second smallest one. In AD patients, we found an increase in the eigenratio, i.e., a decrease in the synchronizability of brain networks across delta, alpha, beta, and gamma EEG frequencies within the wide range of network costs. The finding indicates the destruction of functional brain networks in early AD.

Model-Free Reconstruction of Excitatory Neuronal Connectivity from Calcium Imaging Signals

A systematic assessment of global neural network connectivity through direct electrophysiological assays has remained technically infeasible, even in simpler systems like dissociated neuronal cultures. We introduce an improved algorithmic approach based on Transfer Entropy to reconstruct structural connectivity from network activity monitored through calcium imaging. We focus in this study on the inference of excitatory synaptic links. Based on information theory, our method requires no prior assumptions on the statistics of neuronal firing and neuronal connections. The performance of our algorithm is benchmarked on surrogate time series of calcium fluorescence generated by the simulated dynamics of a network with known ground-truth topology. We find that the functional network topology revealed by Transfer Entropy depends qualitatively on the time-dependent dynamic state of the network (bursting or non-bursting). Thus by conditioning with respect to the global mean activity, we improve the performance of our method. This allows us to focus the analysis to specific dynamical regimes of the network in which the inferred functional connectivity is shaped by monosynaptic excitatory connections, rather than by collective synchrony. Our method can discriminate between actual causal influences between neurons and spurious non-causal correlations due to light scattering artifacts, which inherently affect the quality of fluorescence imaging. Compared to other reconstruction strategies such as cross-correlation or Granger Causality methods, our method based on improved Transfer Entropy is remarkably more accurate. In particular, it provides a good estimation of the excitatory network clustering coefficient, allowing for discrimination between weakly and strongly clustered topologies. Finally, we demonstrate the applicability of our method to analyses of real recordings of in vitro disinhibited cortical cultures where we suggest that excitatory connections are characterized by an elevated level of clustering compared to a random graph (although not extreme) and can be markedly non-local.

Computational problems in perfect phylogeny haplotyping: typing without calling the allele.

A haplotype is an m-long binary vector. The XOR-genotype of two haplotypes is the m-vector of their coordinate-wise XOR. We study the following problem: Given a set of XOR-genotypes, reconstruct their haplotypes so that the set of resulting haplotypes can be mapped onto a perfect phylogeny (PP) tree. The question is motivated by studying population evolution in human genetics, and is a variant of the perfect phylogeny haplotyping problem that has received intensive attention recently. Unlike the latter problem, in which the input is "full" genotypes, here we assume less informative input, and so may be more economical to obtain experimentally. Building on ideas of Gusfield, we show how to solve the problem in polynomial time, by a reduction to the graph realization problem. The actual haplotypes are not uniquely determined by that tree they map onto, and the tree itself may or may not be unique. We show that tree uniqueness implies uniquely determined haplotypes, up to inherent degrees of freedom, and give a sufficient condition for the uniqueness. To actually determine the haplotypes given the tree, additional information is necessary. We show that two or three full genotypes suffice to reconstruct all the haplotypes, and present a linear algorithm for identifying those genotypes.

Sleep deprivation (SD) on focal brain ischemia in the rat : effects of different SD protocols

Sleep-wake disturbances are frequently observed in stroke patients and are associated with poorer functional outcome. Until now the effects of sleep on stroke evolution are unknown. The purpose of the present study was to evaluate the effects of three sleep deprivation (SD) protocols on brain damages after focal cerebral ischemia in a rat model. Permanent occlusion of distal branches of the middle cerebral artery was induced in adult rats. The animals were then subjected to 6h SD, 12h SD or sleep disturbances (SDis) in which 3 x 12h sleep deprivation were performed by gentle handling. Infarct size and brain swelling were assessed by Cresyl violet staining, and the number of damaged cells was measured by terminal deoxynucleotidyl transferase mediated dUTP nick end labeling (TUNEL) staining. Behavioral tests, namely tape removal and cylinder tests, were performed for assessing sensorimotor function. In the 6h SD protocol, no significant difference (P > 0.05) was found either in infarct size (42.5 ± 30.4 mm3 in sleep deprived animals vs. 44.5 ± 20.5 mm3 in controls, mean ± s.d.), in brain swelling (10.2 ± 3.8 % in sleep deprived animals vs. 11.3 ± 2.0 % in controls) or in number of TUNEL-positive cells (21.7 ± 2.0/mm2 in sleep deprived animals vs. 23.0 ± 1.1/mm2 in controls). In contrast, 12h sleep deprivation increased infarct size by 40 % (82.8 ± 10.9 mm3 in SD group vs. 59.2 ± 13.9 mm3 in control group, P = 0.008) and number of TUNEL-positive cells by 137 % (46.8 ± 15/mm in SD group vs. 19.7 ± 7.7/mm2 in control group, P = 0.003). There was no significant difference (P > 0.05) in brain swelling (12.9 ± 6.3 % in sleep deprived animals vs. 11.6 ± 6.0 % in controls). The SDis protocol also increased infarct size by 76 % (3 x 12h SD 58.8 ± 20.4 mm3 vs. no SD 33.8 ± 6.3 mm3, P = 0.017) and number of TUNEL-positive cells by 219 % (32.9 ± 13.2/mm2 vs. 10.3 ± 2.5/mm2, P = 0.008). Brain swelling did not show any difference between the two groups (24.5 ± 8.4 % in SD group vs. 16.7 ± 8.9 % in control group, p > 0.05). Both behavioral tests did not show any concluding results. In summary, we demonstrate that sleep deprivation aggravates brain damages in a rat model of stroke. Further experiments are needed to unveil the mechanisms underlying these effects.

Magnetic properties of Fe-Cu-Nb-Si-B nanocrystaliine magnetic alloys

Several ribbons of composition Fe73.5Cu1Nb 3Si16.5B6 and Fe73.5Cu1 Nb3Si13.5B9 were prepared by annealing the as-quenched samples between 525°C and 700°C; which induced nucleation of nanocrystallites of Fe bcc-type composition. Mean grain sizes were obtained from X-ray diffraction. Static magnetic properties were measured with both a Magnet Physik Hysteresis-Graph (up to 200 Oe) and a SHE SQUID magnetometer (up to 50 kOe). Soft magnetic parameters (coercive field and initial permeability) were very sensitive to grain size. The ZFC magnetization at low field showed a broad peak at a temperature TM, thus signalling a certain distribution of nanocrystalline sizes, and TM strongly decreased when the mean grain size decreased. Isothermal magnetization curves at low temperature showed the expected asymptotic behavior of a random magnet material at low and high fields.

Tracking Iowa Meth Lab Incidents, February 1, 2011

Graph produced by Office of Drug Control Policy showing the tracking of Meth Labs in Iowa from 2008-2010.

Synchronization reveals topological scales in complex networks

We study the relationship between topological scales and dynamic time scales in complex networks. The analysis is based on the full dynamics towards synchronization of a system of coupled oscillators. In the synchronization process, modular structures corresponding to well-defined communities of nodes emerge in different time scales, ordered in a hierarchical way. The analysis also provides a useful connection between synchronization dynamics, complex networks topology, and spectral graph analysis.