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High-order events in cortical networks: a lower bound.

It is commonly believed that information processing in cortical networks involves the collective spiking activity of neuronal assemblies. Nevertheless, due to current technical limitations in multielectrodes recording methods, it is not possible to tackle this issue with direct experimental measurements. In this study we simulate spiking activity of large ensembles of cells focusing on the temporal correlation properties of the neuronal dynamics, and demonstrate that transient, fast synchronization of large groups of cells is a natural phenomenon of the cortical activity. To prove this result we use a statistical approach (based on combinatorics), and knowledge derived from a previous research work [A. Benucci et al., Phys. Rev. E 68, 041905 (2003)]. We quantify the degree of synchronous activity by computing a lower bound for the fraction of cells participating in fast (few milliseconds) synchronous events. Finally we discuss the implications of the results found in terms of cortical coding mechanisms.

Action Potentials↗

Using neural networks and genetic algorithms to enhance performance in an electronic nose.

Sensitivity, repeatability, and discernment are three major issues in any classification problem. In this study, an electronic nose with an array of 32 sensors was used to classify a range of odorous substances. The collective time response of the sensor array was first partitioned into four time segments, using four smooth time-windowing functions. The dimension of the data associated with each time segment was then reduced by applying the Karhunen-Loéve (truncated) expansion (KLE). An ensemble of the reduced data patterns was then used to train a neural network (NN) using the Levenberg-Marquardt (LM) learning method. A genetic algorithm (GA)-based evolutionary computation method was used to devise the appropriate NN training parameters, as well as the effective database partitions/features. Finally, it was shown that a GA-supervised NN system (GANN) outperforms the NN-only classifier, for the classes of the odorants investigated in this study (fragrances, hog farm air, and soft beverages).

Algorithms↗

Characterizing glottal jet turbulence.

Air pressure associated with airflow from the lungs drives the vocal folds into oscillation and allows the air to exit the glottis as a turbulent jet, even though laminar flow may enter the glottis from the trachea. The separation of the turbulence from the deterministic portion of the glottal jet was investigated in the excised canine larynx model. The present study is methodological in that the main goal was to examine three methods of obtaining reasonable representations of both the deterministic signal and the residual turbulence portion: (a) smoothing, (b) wavelet denoising, and (c) ensemble averaging. Ensemble averaging resulted in a deterministic signal that disregarded gross cyclic alterations while exaggerating the turbulence intensity. Wavelet denoising can perform an excellent analysis and synthesis of the glottal velocity, but was problematic in determining which levels of analysis to choose to represent both the deterministic and turbulence appropriately. Smoothing appeared to be the most appropriate for phonation velocities because it preserved gross cyclic variations important to perturbations and modulations, while extracting turbulence at what appears to be reasonable levels.

Animals↗

Toxicological considerations in the application and interpretation of susceptibility biomarkers in epidemiological studies.

With major advances in genotyping technology, it has become practical and affordable to screen biological samples for multiple polymorphisms for which there is more or less knowledge about their functional relevance in relation to toxicological agents or disease. This situation creates some unique epidemiological challenges in which careful consideration of the mechanisms underlying genotype-disease and genotype-exposure-disease relationships, or the lack of knowledge thereof, may help to prevent false-positive results or misinterpretation of data that could mislead future research. Coordination and linkage of data resources on toxicological exposures, genes and disease would be useful as an integrated source of information to devise study design, analysis and interpretation. Such a database could be useful in collating information from which to determine relevant exposures for the disease and to guide the selection of susceptibility markers for study. Further information on toxicological mechanisms and functional relevance of gene variants in relation to disease could be accounted for in statistical analyses and interpretation. Statistical methods that can incorporate this prior information on mechanism, such as hierarchical regression modelling, may help to mitigate some of the problems inherent to these studies by adjusting estimates and confidence limits according to this prior information. Even in the situation where little information on etiological mechanisms is available, application of a less informed prior can be beneficial in improving the accuracy and precision for an ensemble of estimates. The changing paradigm of epidemiological research with regard to increasing detail of underlying mechanisms and the sheer amount of data being evaluated necessitates access to sources of information and analytic methods that can integrate this complexity.

Biomarkers↗

Simulation of the gyroid phase in off-lattice models of pure diblock copolymer melts.

Particle-based molecular simulations of pure diblock copolymer (DBC) systems were performed in continuum space via dissipative particle dynamics and Monte Carlo methods for a bead-spring chain model. This model consisted of chains of soft repulsive particles often used with dissipative particle dynamics. The gyroid phase was successfully simulated in DBC melts at selected conditions provided that the simulation box size was commensurate with the gyroid lattice spacing. Simulations were concentrated at conditions where the gyroid phase is expected to be stable which allowed us to outline approximate phase boundaries. When more than one phase was observed by varying simulation box size, thermodynamic stability was discerned by comparing the Helmholtz free energy of the competing phases. For this purpose, chemical potentials were efficiently simulated via an expanded ensemble that gradually inserts/deletes a target chain to/from the system. These simulations employed a novel combination of Bennett's [J. Comput. Phys. 22, 245 (1976)] acceptance-ratio method to estimate free-energy differences and a recently proposed method to get biasing weights that maximize the number of times that the target chain is regrown. The analysis of the gyroid nodes revealed clear evidence of packing frustration in the form of an (entropically) unfavorably overstretching of chains, a phenomenon that has been suggested to provide the structural basis for the limited region of stability of the gyroid phase in the DBC phase diagram. Finally, the G phase and nodal chain stretching were also found in simulations with a completely different DBC particle-based model.

Journal Article↗

Ensemble of single quadrupolar nuclei in rotating solids: sidebands in NMR spectrum.

A novel way is proposed to describe the evolution of nuclear magnetic polarization and the induced NMR spectrum. In this method, the effect of a high-intensity external static magnetic field and the effects of proper Hamiltonian left over interaction components, which commute with the first, are taken into account simultaneously and equivalently. The method suits any concrete NMR problem. This brings forth the really existing details in the registered spectra, evoked by Hamiltonian secular terms, which may be otherwise smoothed due to approximate treatment of the effects of the secular terms. Complete analytical expressions are obtained describing the NMR spectra including the rotational sideband sets of single quadrupolar nuclei in rotating solids.

Journal Article↗

Classification methods for the development of genomic signatures from high-dimensional data.

Personalized medicine is defined by the use of genomic signatures of patients to assign effective therapies. We present Classification by Ensembles from Random Partitions (CERP) for class prediction and apply CERP to genomic data on leukemia patients and to genomic data with several clinical variables on breast cancer patients. CERP performs consistently well compared to the other classification algorithms. The predictive accuracy can be improved by adding some relevant clinical/histopathological measurements to the genomic data.

Algorithms↗

An ant colony optimisation algorithm for the 2D and 3D hydrophobic polar protein folding problem.

BACKGROUND: The protein folding problem is a fundamental problems in computational molecular biology and biochemical physics. Various optimisation methods have been applied to formulations of the ab-initio folding problem that are based on reduced models of protein structure, including Monte Carlo methods, Evolutionary Algorithms, Tabu Search and hybrid approaches. In our work, we have introduced an ant colony optimisation (ACO) algorithm to address the non-deterministic polynomial-time hard (NP-hard) combinatorial problem of predicting a protein's conformation from its amino acid sequence under a widely studied, conceptually simple model - the 2-dimensional (2D) and 3-dimensional (3D) hydrophobic-polar (HP) model. RESULTS: We present an improvement of our previous ACO algorithm for the 2D HP model and its extension to the 3D HP model. We show that this new algorithm, dubbed ACO-HPPFP-3, performs better than previous state-of-the-art algorithms on sequences whose native conformations do not contain structural nuclei (parts of the native fold that predominantly consist of local interactions) at the ends, but rather in the middle of the sequence, and that it generally finds a more diverse set of native conformations. CONCLUSIONS: The application of ACO to this bioinformatics problem compares favourably with specialised, state-of-the-art methods for the 2D and 3D HP protein folding problem; our empirical results indicate that our rather simple ACO algorithm scales worse with sequence length but usually finds a more diverse ensemble of native states. Therefore the development of ACO algorithms for more complex and realistic models of protein structure holds significant promise.

Algorithms↗

Ancestral sequence reconstruction in primate mitochondrial DNA: compositional bias and effect on functional inference.

Reconstruction of ancestral DNA and amino acid sequences is an important means of inferring information about past evolutionary events. Such reconstructions suggest changes in molecular function and evolutionary processes over the course of evolution and are used to infer adaptation and convergence. Maximum likelihood (ML) is generally thought to provide relatively accurate reconstructed sequences compared to parsimony, but both methods lead to the inference of multiple directional changes in nucleotide frequencies in primate mitochondrial DNA (mtDNA). To better understand this surprising result, as well as to better understand how parsimony and ML differ, we constructed a series of computationally simple "conditional pathway" methods that differed in the number of substitutions allowed per site along each branch, and we also evaluated the entire Bayesian posterior frequency distribution of reconstructed ancestral states. We analyzed primate mitochondrial cytochrome b (Cyt-b) and cytochrome oxidase subunit I (COI) genes and found that ML reconstructs ancestral frequencies that are often more different from tip sequences than are parsimony reconstructions. In contrast, frequency reconstructions based on the posterior ensemble more closely resemble extant nucleotide frequencies. Simulations indicate that these differences in ancestral sequence inference are probably due to deterministic bias caused by high uncertainty in the optimization-based ancestral reconstruction methods (parsimony, ML, Bayesian maximum a posteriori). In contrast, ancestral nucleotide frequencies based on an average of the Bayesian set of credible ancestral sequences are much less biased. The methods involving simpler conditional pathway calculations have slightly reduced likelihood values compared to full likelihood calculations, but they can provide fairly unbiased nucleotide reconstructions and may be useful in more complex phylogenetic analyses than considered here due to their speed and flexibility. To determine whether biased reconstructions using optimization methods might affect inferences of functional properties, ancestral primate mitochondrial tRNA sequences were inferred and helix-forming propensities for conserved pairs were evaluated in silico. For ambiguously reconstructed nucleotides at sites with high base composition variability, ancestral tRNA sequences from Bayesian analyses were more compatible with canonical base pairing than were those inferred by other methods. Thus, nucleotide bias in reconstructed sequences apparently can lead to serious bias and inaccuracies in functional predictions.

Animals↗

Techniques for long-term multisite neuronal ensemble recordings in behaving animals.

Advances in our understanding of neural systems will go hand in hand with improvements in the experimental techniques used to study these systems. This article describes a series of methodological developments aimed at enhancing the power of the methods needed to record simultaneously from populations of neurons over broad regions of the brain in awake, behaving animals. First, our laboratory has made many advances in electrode design, including movable bundle and array electrodes and smaller electrode assemblies. Second, to perform longer and more complex multielectrode implantation surgeries in primates, we have modified our surgical procedures by employing comprehensive physiological monitoring akin to human neuroanesthesia. We have also developed surgical implantation techniques aimed at minimizing brain tissue damage and facilitating penetration of the cortical surface. Third, we have integrated new technologies into our neural ensemble, stimulus and behavioral recording experiments to provide more detailed measurements of experimental variables. Finally, new data analytical techniques are being used in the laboratory to analyze increasingly large quantities of data.

Animals↗

An investigation of simulated umbilical artery Doppler waveforms. III. The effect of noise reduction algorithms on the maximum frequency envelope and on the pulsatility index.

The effect of two noise reduction algorithms on the accuracy of estimation of the maximum frequency envelope and pulsatility index (PI) of simulated umbilical artery Doppler waveforms was investigated. The algorithms were: first, smoothing of the envelope from unfiltered Doppler spectra using a double window modified trimmed mean (DWMTM) filter and second, speckle and noise reduction of the Doppler spectrum using an image processing method. The test population consisted of waveforms were the degree of beam-vessel misalignment had been varied. The accuracy of estimation of the maximum frequency envelope and the PI was calculated by comparing each set of waveforms with the gold-standard maximum frequency envelope from the ensemble averaged waveform obtained with no misalignment. Speckle reduction gave rise to PI values that were low by approximately 0.1 (3%-4%). When there was no background noise present the improvements in envelope estimation were factors of 1.27 and 1.24, respectively, for the DWMTM method and the spectral filter, whereas the factors were 1.56 and 2.07 when background noise was present. For estimation of PI the DWMTM filter was superior. For no background noise the DWMTM filter gave a factor of 3.36 improvement whereas there was no improvement with the spectral filter. When background noise was present the factors for improvement in PI estimation were 2.39 and 4.16.

Algorithms↗

Static contributions to the persistence length of DNA and dynamic contributions to DNA curvature.

Long molecules of DNA have the statistical properties of a worm-like coil. Deviations from linearity occur both because of small dynamic bends induced by thermal motion and from a random distribution of static bends. The latter originate in the different conformations of each of the possible base pair sequences. In this paper a statistical theory of the persistence length of DNA is developed which includes both static and dynamic effects for each base pair sequence, as well as the sequence-dependent correlations of bending angles. The result applies to a generic DNA, i.e., the average over an ensemble of all possible sequences. The theory is also applied to the generation of the average properties of curved DNAs by an analytic method that includes dynamic averaging as well as correlated bends. These results provide information which supplements that obtained by others using Monte Carlo methods. The additivity relation 1/P = 1/P(S) + 1/P(d) proposed by Trifonov et al., where P is the persistence length and P(S) and P(d) are the persistence lengths arising from purely static and dynamic effects, respectively, has been verified to be accurate to better than 0.5%. This is true for both a simplified model and one that includes a complete set of static bends at all base pair sequences.

Base Composition↗

Structure-based predictions of 1H NMR chemical shifts using feed-forward neural networks.

Feed-forward neural networks were trained for the general prediction of 1H NMR chemical shifts of CH(n) protons in organic compounds in CDCl3. The training set consisted of 744 1H NMR chemical shifts from 120 molecular structures. The method was optimized in terms of selected proton descriptors (selection of variables), the number of hidden neurons, and integration of different networks in ensembles. Predictions were obtained for an independent test set of 952 cases with a mean average error of 0.29 ppm (0.20 ppm for 90% of the cases). The results were significantly better than those obtained with counterpropagation neural networks.

Hydrogen↗

Use of a simplified method of optical recording to identify foci of maximal neuron activity in the somatosensory cortex of white rats.

Eight mongrel white male rats were studied under urethane anesthesia, and neuron activity evoked by mechanical and/or electrical stimulation of the contralateral whiskers was recorded in the primary somatosensory cortex. Recordings were made using a digital USB chamber attached to the printer port of a Pentium 200MMX computer running standard programs. Optical images were obtained in the barrel-field zone using a differential signal, i.e., the difference signal for cortex images in control and experimental animals. The results obtained here showed that subtraction of averaged sequences of frames yielded images consisting of spots reflecting the probable position of activated groups of neurons. The most effective stimulation consisted of natural low-frequency stimulation of the whiskers. The method can be used for preliminary mapping of cortical zones, as it provides for rapid and reproducible testing of the activity of neuron ensembles over large areas of the cortex.

Animals↗

Assessment of neuronal maturation and acquisition of functional competence in the developing zebrafish olfactory system.

Olfactory coding at the level of the olfactory bulb is thought to depend upon an ensemble response of mitral cells receiving input from chemotopically-organized projections of olfactory sensory neurons and regulated by lateral inhibitory circuits. Immunocytochemical methods are described to metabolically classify neurons in the developing zebrafish olfactory system based on the relative concentrations of taurine, glutamate, GABA (and potentially other small biogenic amines) and a small guanidium-based cation, agmatine, which labels NMDA-sensitive cells by permeating through active ionotropic glutamate receptor channels. Using metabolic profiling in conjunction with activity dependent labeling we demonstrate that neuronal differentiation in the developing olfactory bulb, as assessed by acquisition of a mature neurochemical profile, and sensitivity to an ionotropic glutamate receptor agonist, NMDA, occurs during the second day of development. This experimental approach is likely to be useful in studies concerned with the development of glutamatergic signaling pathways.

Agmatine↗

Dual spatial folds and different local structures of the HIV-1 immunogenic crown in various virus isolates.

Local and global structural properties of the HIV-1 principal neutralizing epitope were studied in terms of NMR spectroscopy data reported in literature for the HIV-Haiti and HIV-RF isolates. To this effect, the NMR-based method comprising a probabilistic model of protein conformation in conjunction with the molecular mechanics and quantum chemical computations was used for determining the ensembles of conformers matching the NMR requirements and energy criteria. As a matter of record, the high resolution 3D structure models were constructed for the HIV-Haiti and HIV-RF immunogenic crowns, and their geometric parameters were collated with the ones of conformers derived previously for describing the conformational features of immunogenic tip of gp120 from Thailand and MN HIV-1 strains. The HIV-1 neutralization site was demonstrated to constitute in water solution highly flexible system sensitive to its environment. This inference is completely valid for the geometric space of dihedral angles where statistically significant differences in local structures of simulated conformers have been found for all virus isolates of interest. In spite of this fact, the stretch analyzed was shown to manifest a certain conservatism in the space of atomic coordinates, building up in four HIV-1 isolates two spatial folds similar to those observed in crystal for the V3 loop peptides bound to different neutralizing Fabs. The results are discussed in the light of literature data on HIV-1 neutralizing epitope structure.

Amino Acid Sequence↗

Identification methods for nonlinear stochastic systems.

Model identifications based on orbit tracking methods are here extended to stochastic differential equations. In the present approach, deterministic and statistical features are introduced via the time evolution of ensemble averages and variances. The aforementioned quantities are shown to follow deterministic equations, which are explicitly written within a linear as well as a weakly nonlinear approximation. Based on such equations and the observed time series, a cost function is defined. Its minimization by simulated annealing or backpropagation algorithms then yields a set of best-fit parameters. This procedure is successfully applied for various sampling time intervals, on a stochastic Lorenz system.

Journal Article↗

NMR visualization of displacement correlations for flow in porous media.

The temporal correlations of velocities for both water and a water-glycerol mixture flowing through a random packings of monodisperse spherical particles have been investigated using two-dimensional nuclear magnetic resonance methods. By combining various flow rates, fluid viscosities, and bead sizes, a wide range of flow parameters has been covered, the dimensionless Peclet number ranging from 100 to 100 000. The velocity exchange spectroscopy (VEXSY) technique has been employed to measure the correlation between velocities during two intervals separated from each other by a mixing time tau(m). This time is made both large and small compared with the time constant tau(c), required for a fluid element possessing the average flow velocity to cover a distance equal to the characteristic size in the system, the bead diameter. The two-dimensional conditional probability of displacement resulting from the VEXSY method reveals the existence of different "subensembles" of molecules, including a slow moving pool whose displacement is dominated by Brownian motion, an intermediate ensemble whose velocities change little over the mixing time, and a fast flowing ensemble which loses correlation due to mechanical dispersion. We find that that the approach to asymptotic dispersion, as tau(c)/tau(m) increases, depends strongly on the Peclet number, the deviation of the velocity autocorrelation function from a monoexponential Ornstein-Uhlenbeck process becoming more pronounced with increasing Peclet number.

Journal Article↗