A Functional MRI and Magneto/Electro Source Imaging Procedure for Cognitive and Pre-surgical Evaluation

AbstractAnalysis of normal/pathological brain activity using neuroimaging methods is necessary to avoid operation risks, and the outcome serves as prior information for surgical neuronavigation. We present an fMRI/MEG/EEG-based methodology for tasks demanding mainly sensorimotor and visual/cognitive responses. This consists of carefully selected/designed stimulation paradigms and statistical parametric mapping methods that demonstrate the practicability of these techniques for clinical applications. The results replicate known findings in the brain-imaging field, with the improvement that our analyses are restricted to grey matter tissue. The latter enhance computations, which is advantageous for the massive data analyses that are typical of clinical and radiological functional brain “checkup” services

Towards Symbolic Model-Based Mutation Testing: Combining Reachability and Refinement Checking

Model-based mutation testing uses altered test models to derive test cases that are able to reveal whether a modelled fault has been implemented. This requires conformance checking between the original and the mutated model. This paper presents an approach for symbolic conformance checking of action systems, which are well-suited to specify reactive systems. We also consider nondeterminism in our models. Hence, we do not check for equivalence, but for refinement. We encode the transition relation as well as the conformance relation as a constraint satisfaction problem and use a constraint solver in our reachability and refinement checking algorithms. Explicit conformance checking techniques often face state space explosion. First experimental evaluations show that our approach has potential to outperform explicit conformance checkers.Comment: In Proceedings MBT 2012, arXiv:1202.582

AMPK activation protects against diet induced obesity through Ucp1-independent thermogenesis in subcutaneous white adipose tissue

Obesity results from a chronic imbalance between energy intake and energy output but remains difficult to prevent or treat in humans. Adenosine monophosphate (AMP)-activated protein kinase (AMPK) is an important regulator of energy homeostasis1,2,3 and is a molecular target of drugs used for the treatment of metabolic diseases, including obesity4,5. Here we show that mice expressing a gain-of-function AMPK mutant6 display a change in morphology of subcutaneous white adipocytes that is reminiscent of browning. However, despite a dramatic increase in mitochondrial content, Ucp1 expression is undetectable in these adipocytes. In response to a high-fat diet (HFD), expression of skeletal muscle–associated genes is induced in subcutaneous white adipocytes from the gain-of-function AMPK mutant mice. Chronic genetic AMPK activation results in protection against diet-induced obesity due to an increase in whole-body energy expenditure, most probably because of a substantial increase in the oxygen consumption rate of white adipose tissue. These results suggest that AMPK activation enriches, or leads to the emergence of, a population of subcutaneous white adipocytes that produce heat via Ucp1-independent uncoupling of adenosine triphosphate (ATP) production on a HFD. Our findings indicate that AMPK activation specifically in adipose tissue may have therapeutic potential for the treatment of obesity

Finding electrophysiological sources of aging-related processes using penalized least squares with Modified Newton-Raphson algorithm

In this work, we evaluate the flexibility of a modified Newton-Raphson (MNR) algorithm for finding electrophysiological sources in both simulated and real data, and then apply it to different penalized models in order to compare the sources of the EEG theta rhythm in two groups of elderly subjects with different levels of declined physical performance. As a first goal, we propose the MNR algorithm for estimating general multiple penalized least squares (MPLS) models and show that it is capable to find solutions that are simultaneously sparse and smooth. This algorithm allowed to address known and novel models such as the Smooth Non-negative Garrote and the Non-negative Smooth LASSO. We test its ability to solve the EEG inverse problem with multiple penalties -using simulated data- in terms of localization error, blurring and visibility, as compared with traditional algorithms. As a second goal, we explore the electrophysiological sources of the theta activity extracted from resting-state EEG recorded in two groups of older adults, which belong to a longitudinal study to assess the relationship between measures of physical performance (gait speed) decline and normal cognition. The groups contained subjects with good and bad physical performance in the two evaluations (6 years apart). In accordance to clinical studies, we found differences in EEG theta sources for the two groups, specifically, subjects with declined physical performance presented decreased temporal sources while increased prefrontal sources that seem to reflect compensating mechanisms to ensure a stable walking

Measuring Granger Causality between Cortical Regions from Voxelwise fMRI BOLD Signals with LASSO

Functional brain network studies using the Blood Oxygen-Level Dependent (BOLD) signal from functional Magnetic Resonance Imaging (fMRI) are becoming increasingly prevalent in research on the neural basis of human cognition. An important problem in functional brain network analysis is to understand directed functional interactions between brain regions during cognitive performance. This problem has important implications for understanding top-down influences from frontal and parietal control regions to visual occipital cortex in visuospatial attention, the goal motivating the present study. A common approach to measuring directed functional interactions between two brain regions is to first create nodal signals by averaging the BOLD signals of all the voxels in each region, and to then measure directed functional interactions between the nodal signals. Another approach, that avoids averaging, is to measure directed functional interactions between all pairwise combinations of voxels in the two regions. Here we employ an alternative approach that avoids the drawbacks of both averaging and pairwise voxel measures. In this approach, we first use the Least Absolute Shrinkage Selection Operator (LASSO) to pre-select voxels for analysis, then compute a Multivariate Vector AutoRegressive (MVAR) model from the time series of the selected voxels, and finally compute summary Granger Causality (GC) statistics from the model to represent directed interregional interactions. We demonstrate the effectiveness of this approach on both simulated and empirical fMRI data. We also show that averaging regional BOLD activity to create a nodal signal may lead to biased GC estimation of directed interregional interactions. The approach presented here makes it feasible to compute GC between brain regions without the need for averaging. Our results suggest that in the analysis of functional brain networks, careful consideration must be given to the way that network nodes and edges are defined because those definitions may have important implications for the validity of the analysis

Assignment of PolyProline II Conformation and Analysis of Sequence – Structure Relationship

International audienceBACKGROUND: Secondary structures are elements of great importance in structural biology, biochemistry and bioinformatics. They are broadly composed of two repetitive structures namely α-helices and β-sheets, apart from turns, and the rest is associated to coil. These repetitive secondary structures have specific and conserved biophysical and geometric properties. PolyProline II (PPII) helix is yet another interesting repetitive structure which is less frequent and not usually associated with stabilizing interactions. Recent studies have shown that PPII frequency is higher than expected, and they could have an important role in protein - protein interactions. METHODOLOGY/PRINCIPAL FINDINGS: A major factor that limits the study of PPII is that its assignment cannot be carried out with the most commonly used secondary structure assignment methods (SSAMs). The purpose of this work is to propose a PPII assignment methodology that can be defined in the frame of DSSP secondary structure assignment. Considering the ambiguity in PPII assignments by different methods, a consensus assignment strategy was utilized. To define the most consensual rule of PPII assignment, three SSAMs that can assign PPII, were compared and analyzed. The assignment rule was defined to have a maximum coverage of all assignments made by these SSAMs. Not many constraints were added to the assignment and only PPII helices of at least 2 residues length are defined. CONCLUSIONS/SIGNIFICANCE: The simple rules designed in this study for characterizing PPII conformation, lead to the assignment of 5% of all amino as PPII. Sequence - structure relationships associated with PPII, defined by the different SSAMs, underline few striking differences. A specific study of amino acid preferences in their N and C-cap regions was carried out as their solvent accessibility and contact patterns. Thus the assignment of PPII can be coupled with DSSP and thus opens a simple way for further analysis in this field

On the Construction of Live Timed Systems

We present a method that allows to guarantee liveness by construction of a class of timed systems. The method is based on the use of a set of structural properties which can be checked locally at low cost. We provide sufficient conditions for liveness preservation by parallel composition nd priority choice operators. The latter allow to restrict a system's behavior according to a given priority order on its actions. We present several examples illustrating the use of the results, in particular for the construction of live controllers