Small Number Of Modules Research Articles

Coarse graining and criticality in the human connectome.

In the face of the stupefying complexity of the human brain, network analysis is a most useful tool that allows one to greatly simplify the problem, typically by approximating the billions of neurons making up the brain by means of a coarse-grained picture with a practicable number of nodes. But even such relatively small and coarse networks, such as the human connectome with its 100-1000 nodes, may present challenges for some computationally demanding analyses that are incapable of handling networks with more than a handful of nodes. With such applications in mind, we set out to study the extent to which dynamical behavior and critical phenomena in the brain may be preserved following a severe coarse-graining procedure. Thus we proceeded to further coarse grain the human connectome by taking a modularity-based approach, the goal being to produce a network of a relatively small number of modules. After finding that the qualitative dynamical behavior of the coarse-grained networks reflected that of the original networks, albeit to a less pronounced extent, we then formulated a hypothesis based on the coarse-grained networks in the context of criticality in the Wilson-Cowan and Ising models, and we verified the hypothesis, which connected a transition value of the former with the critical temperature of the latter, using the original networks. This preservation of dynamical and critical behavior following a severe coarse-graining procedure, in principle, allows for the drawing of similar qualitative conclusions by analyzing much smaller networks, which opens the door for studying the human connectome in contexts typically regarded as computationally intractable, such as Integrated Information Theory and quantum models of the human brain.

Protein Signatures of Centenarians and Their Offspring Suggest Centenarians Age Slower than Other Humans

We used a high-throughput Somascan platform to quantify 4116 proteins in the serum of 224centenarians, offspring, and controls (mean ages: 105, 80, 79 years) from the New England Centenarian Study, and to characterize the serum proteome of aging and longevity. We identified 1312 proteins that significantly differ between centenarians and their offspring and controls (FDR<1%), and replicated the association of 484 of these using 2 independent proteomic studies of aging. By comparing the patterns of proteins associated with aging to protein profiles of centenarians, we also identified serum-protein signatures of extreme old age and of immune senescence. We then searched for protein signatures that distinguish between short and long survival within various age groups and we identified two differentprotein signatures that predict longer survival in older people and in centenarians. The data suggest that centenarians acquire similar aging patterns as seen in younger cohorts that have short survival periods, suggesting that centenarians do not escape normal aging markers, but rather acquire them much later than usual. For example, centenarian signatures are significantly enriched for senescence-associated secretory phenotypes, consistent with those seen with younger aged individuals, and from this findingwe provide a new list of serum proteins that can be used to measure cellular senescence. Consistently with this findings, protein co-expression network analysis showed that the serum proteome of offspring and controls clusters in a small number of modules of correlated proteins, some of which are conserved in centenarians’ serum while others break down in smaller modules thus suggesting that a small number of biological drivers may regulate aging and that changes in gene regulation may be important to reach extreme old age. This centenarian study thus provides additional signatures that can be used to measure aging, and provides specific biomarkers of healthy aging and longevity, suggesting potential mechanisms that could help prolong health and support longevity.

Modular Organization of Exploratory Force Development Under Isometric Conditions in the Human Arm

ABSTRACTMuscle coordination of isometric force production can be explained by a smaller number of modules. Variability in force output, however, is higher during exploratory/transient force development phases than force maintenance phase, and it is not clear whether the same modular structure underlies both phases. In this study, eight neurologically-intact adults isometrically performed target force matches in 54 directions at hands, and electromyographic (EMG) data from eight muscles were parsed into four sequential phases. Despite the varying degree of motor complexity across phases (significant between-phase differences in EMG-force correlation, angular errors, and between-force correlations), the number/composition of motor modules were found equivalent across phases, suggesting that the CNS systematically modulated activation of the same set of motor modules throughout sequential force development.

Using gene expression data to identify causal pathways between genotype and phenotype in a complex disease: application to Genetic Analysis Workshop 19.

We explore causal relationships between genotype, gene expression and phenotype in the Genetic Analysis Workshop 19 data. We compare the use of structural equation modeling and a Bayesian unified framework approach to infer the most likely causal models that gave rise to the data. Testing an exhaustive set of causal relationships between each single-nucleotide polymorphism, gene expression probe, and phenotype would be computationally infeasible, thus a filtering step is required. In addition to filtering based on pairwise associations, we consider weighted gene correlation network analysis as a method of clustering genes with similar function into a small number of modules. These modules capture the key functional mechanisms of genes while greatly reducing the number of relationships to test for in causal modeling.

Learning new gait patterns: Exploratory muscle activity during motor learning is not predicted by motor modules

The motor module hypothesis in motor control proposes that the nervous system can simplify the problem of controlling a large number of muscles in human movement by grouping muscles into a smaller number of modules. Here, we tested one prediction of the modular organization hypothesis by examining whether there is preferential exploration along these motor modules during the learning of a new gait pattern. Healthy college-aged participants learned a new gait pattern which required increased hip and knee flexion during the swing phase while walking in a lower-extremity robot (Lokomat). The new gait pattern was displayed as a foot trajectory in the sagittal plane and participants attempted to match their foot trajectory to this template. We recorded EMG from 8 lower-extremity muscles and we extracted motor modules during both baseline walking and target-tracking using non-negative matrix factorization (NMF). Results showed increased trajectory variability in the first block of learning, indicating that participants were engaged in exploratory behavior. Critically, when we examined the muscle activity during this exploratory phase, we found that the composition of motor modules changed significantly within the first few strides of attempting the new gait pattern. The lack of persistence of the motor modules under even short time scales suggests that motor modules extracted during locomotion may be more indicative of correlated muscle activity induced by the task constraints of walking, rather than reflecting a modular control strategy.

Modularity for Motor Control and Motor Learning.

How the central nervous system (CNS) overcomes the complexity of multi-joint and multi-muscle control and how it acquires or adapts motor skills are fundamental and open questions in neuroscience. A modular architecture may simplify control by embedding features of both the dynamic behavior of the musculoskeletal system and of the task into a small number of modules and by directly mapping task goals into module combination parameters. Several studies of the electromyographic (EMG) activity recorded from many muscles during the performance of different tasks have shown that motor commands are generated by the combination of a small number of muscle synergies, coordinated recruitment of groups of muscles with specific amplitude balances or activation waveforms, thus supporting a modular organization of motor control. Modularity may also help understanding motor learning. In a modular architecture, acquisition of a new motor skill or adaptation of an existing skill after a perturbation may occur at the level of modules or at the level of module combinations. As learning or adapting an existing skill through recombination of modules is likely faster than learning or adapting a skill by acquiring new modules, compatibility with the modules predicts learning difficulty. A recent study in which human subjects used myoelectric control to move a mass in a virtual environment has tested this prediction. By altering the mapping between recorded muscle activity and simulated force applied on the mass, as in a complex surgical rearrangement of the tendons, it has been possible to show that it is easier to adapt to a perturbation that is compatible with the muscle synergies used to generate hand force than to a similar but incompatible perturbation. This result provides direct support for a modular organization of motor control and motor learning.

3D VLSI Non-Slicing Floor Planning using Modified Corner List Representation

Background: Floor planning is important step in physical design automation of VLSI circuits, because it gives an early feedback on the architectural design. It is the process of finding the position of the module such that no two modules overlap with each other. Methods: In order to have an efficient floor plan, the total area occupied by the modules should be minimum. So, non-slicing floor plan is used to find an optimal floor plan layout. To represent non-slicing floor plan, a number of representations are proposed. Findings: To encompass billions of transistors in an Integrated Circuit (IC), 3Dimensional (3D) IC is preferred instead of 2D. In this paper, a novel 3Dimensional (3D) non-slicing floor planning representation called Modified Corner List (MCL) algorithm is proposed and properties of MCL algorithm is derived. The proposed algorithm is illustrated using Microelectronics Centre of North Carolina (MCNC) benchmark circuits and simulation results shows that it is very effective for 3D floor plan representation. Improvements: The proposed algorithm works well for small number of modules. As the number of module increases, computational time taken by the algorithm also increases. The above problem can be solved by applying heuristic algorithm in association with MCL strategy to find near optimal placement in reduced run time.

Description of modular devices for the measurement of external dosimetry in radiation protection.

In 2002 the Group of Radiation Dosimetry and Calibration of the Belgian Nuclear Research Centre (SCK•CEN) has developed an experimental device based on the optically stimulated luminescence (OSL) working with Al2O3:C detectors (TLD-500 and Luxel) stimulated with an argon laser. A set of devices made from different modules have been developed to permit external dosimetry measurements with thermoluminescence (TL) and OSL techniques under different conditions. This study describes these measurement devices that can be made with these modules and some of the characteristics of the different systems. These devices present several advantages in terms of measurement possibilities: a small number of modules allow the use of different detection materials (Al2O3:C, BeO, quartz electronic components and tiles) and different measurement methods (TL, CW-OSL and pulsed OSL). Some applications are commented.

Modular organization across changing task demands in healthy and poststroke gait.

Our goal was to link impaired module patterns to mobility task performance in persons poststroke. Kinematic, kinetic, and electromyography (EMG) data were collected from 27 poststroke subjects and from 17 healthy control subjects. Each subject walked on a treadmill at their self‐selected walking speed in addition to a randomized block design of four steady‐state mobility capability tasks: walking at maximum speed, and walking at self‐selected speed with maximum cadence, maximum step length, and maximum step height. The number of modules required to account for >90% of the variability accounted for the EMG patterns of each muscle was found using nonnegative matrix factorization. Module compositions of each module during each task were compared to the average module in self‐selected walking using Pearson's correlations. Additionally, to compare module timing, the percentage of integrated module activation timing within six regions of the gait cycle was calculated. Statistical analyses were used to compare the correlations and integrated timing across tasks. Mobility performance measures of task capability were speed change, cadence change, step length change, and step height change. We found that although some poststroke subjects had a smaller number of modules than healthy subjects, the same underlying modules (number and composition) in each subject (both healthy and poststroke) that contribute to steady‐state walking also contribute to specific mobility capability tasks. In healthy subjects, we found that module timing, but not composition, changes when functional task demands are altered during walking. However, this adaptability in module timing, in addition to mobility capability, is limited in poststroke subjects.

A network that performs brute-force conversion of a temporal sequence to a spatial pattern: relevance to odor recognition.

A classic problem in neuroscience is how temporal sequences (TSs) can be recognized. This problem is exemplified in the olfactory system, where an odor is defined by the TS of olfactory bulb (OB) output that occurs during a sniff. This sequence is discrete because the output is subdivided by gamma frequency oscillations. Here we propose a new class of “brute-force” solutions to recognition of discrete sequences. We demonstrate a network architecture in which there are a small number of modules, each of which provides a persistent snapshot of what occurs in a different gamma cycle. The collection of these snapshots forms a spatial pattern (SP) that can be recognized by standard attractor-based network mechanisms. We will discuss the implications of this strategy for recognizing odor-specific sequences generated by the OB.

Simulation Modeling for Electrical Switching System of Hydropower Station

This paper proposes a simulation modeling method for the electrical switching system of hydropower station, which is a sub-topic for Hydropower Station Simulation Training System. The graphics model of commonly used electrical switch equipment is developed with a certain software. As vast and different types of Hydropower station circuit breakers and associated grounding switches, and each specific action of the switch process is not same, so the modular modeling method is described to solve the problem. According to the role and status in power plant, electrical switch system is divided into several sub modules, among which a number of small modules are sorted in. In each sub module, a common model is developed. Besides, the application method that the network topology analysis algorithm used in electrical switching system simulation logic judgment is introduced. With the ‘connecting line fusion’ technique, logic function expression member information table is automatically generated, thereby enhancing the suitability for the electrical switch simulation model. The methods mentioned above assure the real-time, typicality and flexibility in simulation, and have been successfully used in the development of a large hydropower station simulator. DOI: http://dx.doi.org/10.11591/telkomnika.v11i8.3135

Description of a portable devices developed at SCK•CEN for OSL and TL dosimetry

Abstract The Expert Group of Radiation Dosimetry and Calibration of the Belgian Nuclear Research Centre (SCK•CEN) uses thermoluminescence (TL) dosimetry for more than thirty years for routine measurements and for R&D purposes. In 2002, an experimental device based on the optically stimulated luminescence (OSL) was developed for research. It works with AL 2 O 3 :C detectors (TLD-500 & Luxel™) stimulated with a green line generated by a 150 mW Ar + laser. Since 2008, modular OSL devices have been developed using light emitting diodes (LED) and working with reflection or transmission mode. This paper describes these modules. The characteristics of the different systems are compared on experimental results: detections limits, linearity, sensitivity. The modular device presents advantages in terms of measurement possibilities with respect to the laser device: a small number of modules allows the use of different detection materials (AL 2 O 3 :C, BeO, quartz, electronic components) and different measurement methods (TL, CW-OSL and pulsed OSL). The modules are controlled by a personal computer and a microcontroller array. The whole set is able to measure a wide range of doses by changing the number of LEDs and is able to work in situ . The future trends are commented as well as some applications.

Assessing the functional coherence of modules found in multiple-evidence networks from Arabidopsis

BackgroundCombining multiple evidence-types from different information sources has the potential to reveal new relationships in biological systems. The integrated information can be represented as a relationship network, and clustering the network can suggest possible functional modules. The value of such modules for gaining insight into the underlying biological processes depends on their functional coherence. The challenges that we wish to address are to define and quantify the functional coherence of modules in relationship networks, so that they can be used to infer function of as yet unannotated proteins, to discover previously unknown roles of proteins in diseases as well as for better understanding of the regulation and interrelationship between different elements of complex biological systems.ResultsWe have defined the functional coherence of modules with respect to the Gene Ontology (GO) by considering two complementary aspects: (i) the fragmentation of the GO functional categories into the different modules and (ii) the most representative functions of the modules. We have proposed a set of metrics to evaluate these two aspects and demonstrated their utility in Arabidopsis thaliana. We selected 2355 proteins for which experimentally established protein-protein interaction (PPI) data were available. From these we have constructed five relationship networks, four based on single types of data: PPI, co-expression, co-occurrence of protein names in scientific literature abstracts and sequence similarity and a fifth one combining these four evidence types. The ability of these networks to suggest biologically meaningful grouping of proteins was explored by applying Markov clustering and then by measuring the functional coherence of the clusters.ConclusionsRelationship networks integrating multiple evidence-types are biologically informative and allow more proteins to be assigned to a putative functional module. Using additional evidence types concentrates the functional annotations in a smaller number of modules without unduly compromising their consistency. These results indicate that integration of more data sources improves the ability to uncover functional association between proteins, both by allowing more proteins to be linked and producing a network where modular structure more closely reflects the hierarchy in the gene ontology.

Generation of Variants of a Motor Act in a Modular and Hierarchical Motor Network

Most motor systems can generate a variety of behaviors, including categorically different behaviors and variants of a single motor act within the same behavioral category. Previous work indicated that many pattern-generating interneuronal networks may have a modular organization and that distinct categories of behaviors can be generated through flexible combinations of a small number of modules or building blocks. However, it is unclear whether and how a small number of modules could possibly generate a large number of variants of one behavior. We show that the modular feeding motor network of Aplysia mediates variations in protraction duration in biting-like programs. Two descending commands are active during biting behavior and trigger biting-like responses in a semiintact preparation. In the isolated CNS, when activated alone, the two commands produce biting-like programs of either long or short protraction duration by acting specifically on two modules that have opposite effects on protraction duration. More importantly, when coactivated at different frequencies, the two commands produce biting programs with an intermediate protraction duration. It was previously hypothesized that behavioral variants may be produced by combining different activity levels of multiple descending commands. Our data provide direct evidence for such a scheme and show how it is implemented in a modularly organized network. Thus, within a modular and hierarchical architecture, in addition to generating different categories of behavior, a small number of modules also efficiently implements variants of a single behavior.

An orthogonal simulated annealing algorithm for large floorplanning problems

The conventional simulated annealing with some random generation mechanism using the sequence-pair topological representation in block placement and floorplanning is effective for a very small number of modules (40-50). This paper proposes an orthogonal simulated annealing algorithm (OSA) with an efficient generation mechanism (EGM) for solving large floorplanning problems. EGM samples a small number of representative floorplans and then efficiently derives a high-performance floorplan by using a systematic reasoning method for the next move of OSA based on orthogonal experimental design. Furthermore, an improved swap operation is proposed which cooperates with EGM to make OSA efficient. Excellent experimental results using the Microelectronics Center of North Carolina and the Gigascale Systems Research Center benchmarks show that OSA performs better than existing methods for large floorplanning problems.

Flow Field and Performance Analysis of Aerospike Nozzles with Simplified Clustered Modules

The fundamental characteristics of simplified clustered aerospike nozzles are analyzed by the computational fluid dynamics approach. Several types of aerospike nozzles, having 6, 12 and 24 inner nozzle modules with the same area ratio and total flow rate, are examined. The interactions of the exhaust flows from the neighboring modules create shock waves, which produce high-pressure regions on the nozzle surface. The base regions of the cluster-type aerospike nozzles are not influenced by the clustering of the modules and show features similar to axisymmetric-type aerospike nozzles. The base pressure is nearly equal to the environmental pressure when the pressure ratio is low and suddenly attains a constant pressure when the pressure ratio is high. The computed results show that the number of modules influence the thrust performance, and the major reason for the decrease in thrust performance with a smaller number of modules is due to thrust loss in the ramp region.

Modeling change requests due to faults in a large-scale telecommunication system

It is widely known that a small number of modules in any system are likely to contain the majority of faults. Early identification and consequent attention to such modules may mitigate or prevent many defects. The objective of this study is to use product metrics to build a prediction model of the number of change requests (CRs) that are likely to occur in individual modules during testing. The study first empirically validates eight product metrics, while considering the confounding effects of code size (lines of code). Next, a prediction model of CR outcomes is developed with the validated metrics by utilizing a negative binomial regression that allows over-dispersion. In total, 816 modules written in the Chill programming language were analyzed in a large-scale telecommunication system. There is a positive association between the number of CRs and four product metrics (number of unique operators, unique operands, signals, and library calls) after considering the confounding effect of code size. A prediction model that includes only code size and the number of unique operands provides the best empirical fit.

Simplifying metabolic complexity

A complete description of the regulation of metabolism in even a single cell will be very hard to achieve, enormous and indigestible. However, there are two powerful ways to simplify the complexity. Firstly, related processes and intermediates can be grouped into a small number of modules, and the regulation of the simplified system can be studied. Secondly, control analysis can be used. With these simplifications to illuminate the important regulatory features, even a full description could be made intellectually and experimentally accessible without distorting the essential regulatory features. Modular control analysis is powerful because it can quantify the relative importance of different flows of regulatory information through any metabolic, physiological, signalling or transcriptional network. It can answer global questions about the importance of different pathways mediating any change to a system. It has been used to analyse how cadmium, a poison with multiple effects, changes oxidative phosphorylation in isolated mitochondria, and to quantify the regulation of energy metabolism in hepatocytes. It has been used to measure how energy metabolism is regulated during mitogen stimulation of thymocytes, quantifying the relative importance of different signalling pathways and how each pathway contributes to the activation of energy metabolism. Recently, we have applied modular control analysis to modern DNA micro-array expression profiling to measure the importance of different groups of mRNA transcripts in mediating physiological responses.

Multiple effects of 2,2',5,5'-tetrachlorobiphenyl on oxidative phosphorylation in rat liver mitochondria.

An experimental investigation of the response of the multicomponent oxidative phosphorylation system to the environmental pollutant 2,2',5,5'-tetrachlorobiphenyl (2,2',5,5'-TCB) was performed by modular kinetic analysis in rat liver mitochondria oxidizing succinate (+ rotenone) and glutamate + malate. This approach facilitates the analysis of a complex process by dividing it into a small number of modules, each comprising multiple enzymatic steps, and allows evaluation of changes in the kinetics of individual blocks of the complex system induced by multisite effectors. Kinetic dependencies of the respiratory subsystem, the phosphorylation subsystem, and the proton permeability of the inner membrane on the membrane potential Delta Psi were determined in the control and in the presence of 20 microM 2,2',5,5'-TCB. The toxin inhibited the rate of respiration with both substrates to a similar extent (by 23-26%). We showed that 2,2',5,5'-TCB affected the all three modules of the oxidative phosphorylation system: it inhibited both the respiratory and the phosphorylation subsystems, and increased the membrane leak. As a result, the value of Delta Psi in State 3 of mitochondria oxidizing glutamate + malate remained the same or slightly increased with succinate, indicating that in the former case the respiratory subsystem was more sensitive to 2,2',5,5'-TCB. We explain this by the 2,2',5,5'-TCB-induced inhibition of Complex I. Moreover, 2,2',5,5'-TCB decreased the number of oligomycin-binding sites by 20%, caused a significant drop in the membrane potential generated by ATP hydrolysis, and inhibited activity of ATP hydrolysis in uncoupled mitochondria. Thus, we obtained evidence that at least one of the targets of 2,2',5,5'-TCB action within the phosphorylation module was ATP synthase.

Simplifying metabolic complexity.

A complete description of the regulation of metabolism in even a single cell will be very hard to achieve, enormous and indigestible. However, there are two powerful ways to simplify the complexity. Firstly, related processes and intermediates can be grouped into a small number of modules, and the regulation of the simplified system can be studied. Secondly, control analysis can be used. With these simplifications to illuminate the important regulatory features, even a full description could be made intellectually and experimentally accessible without distorting the essential regulatory features. Modular control analysis is powerful because it can quantify the relative importance of different flows of regulatory information through any metabolic, physiological, signalling or transcriptional network. It can answer global questions about the importance of different pathways mediating any change to a system. It has been used to analyse how cadmium, a poison with multiple effects, changes oxidative phosphorylation in isolated mitochondria, and to quantify the regulation of energy metabolism in hepatocytes. It has been used to measure how energy metabolism is regulated during mitogen stimulation of thymocytes, quantifying the relative importance of different signalling pathways and how each pathway contributes to the activation of energy metabolism. Recently, we have applied modular control analysis to modern DNA microarray expression profiling to measure the importance of different groups of mRNA transcripts in mediating physiological responses.