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At least 451 records · Page 25Linked to original sources

PubMed2005

Ensemble coding of vocal control in birdsong.

Zebra finch song is represented in the high-level motor control nucleus high vocal center (HVC) (Reiner et al., 2004) as a sparse sequence of spike bursts. In contrast, the vocal organ is driven continuously by smoothly varying muscle control signals. To investigate how the sparse HVC code is transformed into continuous vocal patterns, we recorded in the singing zebra finch from populations of neurons in the robust nucleus of arcopallium (RA), a premotor area intermediate between HVC and the motor neurons. We found that highly similar song elements are typically produced by different RA ensembles. Furthermore, although the song is modulated on a wide range of time scales (10-100 ms), patterns of neural activity in RA change only on a short time scale (5-10 ms). We suggest that song is driven by a dynamic circuit that operates on a single underlying clock, and that the large convergence of RA neurons to vocal control muscles results in a many-to-one mapping of RA activity to song structure. This permits rapidly changing RA ensembles to drive both fast and slow acoustic modulations, thereby transforming the sparse HVC code into a continuous vocal pattern.

Action Potentials↗

PubMed2004

Reduction of single-neuron firing uncertainty by cortical ensembles during motor skill learning.

Motor skill learning is usually characterized by shortening of response time and performance of faster, more stereotypical movements. However, little is known about the changes in neural activity that underlie these behavioral changes. Here we used chronically implanted electrode arrays to record neuronal activity in the rat primary motor cortex (MI) as animals learned to execute movements in two directions. Strong modulation of MI single-neuron activity was observed while movement duration of the animal decreased. Despite many learning-induced changes, the precision with which single neurons fire did not improve with learning. Hence, prediction of movement direction from single neurons was bounded. In contrast, prediction of movement direction using neuronal ensembles improved significantly with learning, suggesting that, with practice, neuronal ensembles learn to overcome the uncertainty introduced by single-neuron stochastic activity.

Acoustic Stimulation↗

PubMed2006

Sequence-specific solvent accessibilities of protein residues in unfolded protein ensembles.

Protein stability cannot be understood without the correct description of the unfolded state. We present here an efficient method for accurate calculation of atomic solvent exposures for denatured protein ensembles. The method used to generate the ensembles has been shown to reproduce diverse biophysical experimental data corresponding to natively and chemically unfolded proteins. Using a data set of 19 nonhomologous proteins containing from 98 to 579 residues, we report average accessibilities for all residue types. These averaged accessibilities are considerably lower than those previously reported for tripeptides and close to the lower limit reported by Creamer and co-workers. Of importance, we observe remarkable sequence dependence for the exposure to solvent of all residue types, which indicates that average residue solvent exposures can be inappropriate to interpret mutational studies. In addition, we observe smaller influences of both protein size and protein amino acid composition in the averaged residue solvent exposures for individual proteins. Calculating residue-specific solvent accessibilities within the context of real sequences is thus necessary and feasible. The approach presented here may allow a more precise parameterization of protein energetics as a function of polar- and apolar-area burial and opens new ways to investigate the energetics of the unfolded state of proteins.

Computer Simulation↗

PubMed2006

On the characterization of protein native state ensembles.

Describing and understanding the biological function of a protein requires a detailed structural and thermodynamic description of the protein's native state ensemble. Obtaining such a description often involves characterizing equilibrium fluctuations that occur beyond the nanosecond timescale. Capturing such fluctuations remains nontrivial even for very long molecular dynamics and Monte Carlo simulations. We propose a novel multiscale computational method to exhaustively characterize, in atomistic detail, the protein conformations constituting the native state with no inherent timescale limitations. Applications of this method to proteins of various folds and sizes show that thermodynamic observables measured as averages over the native state ensembles obtained by the method agree remarkably well with nuclear magnetic resonance data that span multiple timescales. By characterizing equilibrium fluctuations at atomistic detail over a broad range of timescales, from picoseconds to milliseconds, our method offers to complement current simulation techniques and wet-lab experiments and can impact our understanding and description of the relationship between protein flexibility and function.

Amino Acids↗

PubMed1999

Conformational ensembles: the role of neuropeptide structures in receptor binding.

Conformational properties of several similar FMRFamide-like neuropeptides from mollusks were investigated by nuclear magnetic resonance (NMR) spectroscopy. It was found that amino acid substitutions in the N-terminal variable regions of the peptides had dramatic effects on the populations of reverse turns in solution. The populations of turns, as measured by two independent NMR parameters, were found to be highly correlated (r(2) = 0.93 and 0. 82) with IC(50) values using receptor membrane preparations from Helix aspersa (Payza, 1987; Payza et al., 1989). These results suggest that the amount of turn in the free peptide can influence the receptor binding affinities of that peptide. On the basis of these observations, a model was developed in which only a single species from a conformational ensemble of an unbound peptide will bind to a particular receptor. Thus, the conformational ensemble reduces the effective concentration of a particular peptide with respect to a particular receptor.

Amino Acid Sequence↗

PubMed1999

Reconstruction of natural scenes from ensemble responses in the lateral geniculate nucleus.

A major challenge in studying sensory processing is to understand the meaning of the neural messages encoded in the spiking activity of neurons. From the recorded responses in a sensory circuit, what information can we extract about the outside world? Here we used a linear decoding technique to reconstruct spatiotemporal visual inputs from ensemble responses in the lateral geniculate nucleus (LGN) of the cat. From the activity of 177 cells, we have reconstructed natural scenes with recognizable moving objects. The quality of reconstruction depends on the number of cells. For each point in space, the quality of reconstruction begins to saturate at six to eight pairs of on and off cells, approaching the estimated coverage factor in the LGN of the cat. Thus, complex visual inputs can be reconstructed with a simple decoding algorithm, and these analyses provide a basis for understanding ensemble coding in the early visual pathway.

Algorithms↗

PubMed2000

Dynamics of hippocampal ensemble activity realignment: time versus space.

Whether hippocampal map realignment is coupled more strongly to position or time was studied in rats trained to shuttle on a linear track. The rats were required to run from a start box and to pause at a goal location at a fixed location relative to stable distal cues (room-aligned coordinate frame). The origin of each lap was varied by shifting the start box and track as a unit (box-aligned coordinate frame) along the direction of travel. As observed by Gothard et al. (1996a), on each lap the hippocampal activity realigned from a representation that was box-aligned to one that was room-aligned. We studied the dynamics of this transition using a measure of how well the moment-by-moment ensemble activity matched the expected activity given the location of the animal in each coordinate frame. The coherency ratio, defined as the ratio of the matches for the two coordinate systems, provides a quantitative measure of the ensemble activity alignment and was used to compare four possible descriptions of the realignment process. The elapsed time since leaving the box provided a better predictor of the occurrence of the transition than any of the three spatial parameters investigated, suggesting that the shift between coordinate systems is at least partially governed by a stochastic, time-dependent process.

Action Potentials↗

PubMed2003

Temporal resolution of ensemble visual motion signals in primate retina.

Recent studies have examined the temporal precision of spiking in visual system neurons, but less is known about the time scale that is relevant for behaviorally important visual computations. We examined how spatiotemporal patterns of spikes in ensembles of primate retinal ganglion cells convey information about visual motion to the brain. The direction of motion of a bar was estimated by comparing the timing of responses in ensembles of parasol (magnocellular-projecting) retinal ganglion cells recorded simultaneously, using a cross-correlation approach similar to standard models of motion sensing. To identify the temporal resolution of motion signals, spike trains were low-pass filtered before estimating the direction of motion. The filter time constant that resulted in most accurate motion sensing was in the range of 10-50 msec for a range of stimulus speeds and contrasts and approached a lower limit of approximately 10 msec at high speeds and contrasts. This time constant was, on average, comparable to the length of interspike intervals. These findings suggest that cortical neurons could filter their inputs on a time scale of tens of milliseconds, rather than relying on the precise times of individual input spikes, to sense motion most reliably.

Action Potentials↗

PubMed1992

A new ensemble averaging technique in impedance cardiography for estimation of stroke volume during treadmill exercise.

In this study, a new ensemble average technique is developed to measure cardiac output during treadmill exercise. Each dz/dt peak is used as a starting point for ensemble averaging, instead of the conventionally used R point of the ECG, in order to prevent the peak dz/dt waveform (C point) from smoothing, which results in increased dz/dtmax. The R-Z interval from the R point of the ECG to the peak dz/dt varies for each heart beat especially during strenuous exercise. Signal-to-noise ratios of five subjects obtained with the new technique are 0-32.6% higher than those obtained with the conventional technique at rest and during four levels of treadmill exercise. Power spectral densities of the averaged dz/dt waveforms by the peak dz/dt and R point references are also analyzed. Stroke volumes of the five subjects averaged by the peak dz/dt are 0-23.5% higher than those obtained by the R point at rest and during four levels of exercise.

Cardiography, Impedance↗

PubMedDate not supplied

[Lagrange formulation of the self-organization problem of a neuronal ensemble during computation of nonlinear dissipation of energy].

The Lagrange formulation for the problem of excitation of the Bresslow neural network is given to construct an arbitrary law for energy dissipation of the ensemble. The Amari assumption about neuron conductivity as a function of membrane potential allows one to admit the logistic dissipation law. It was shown that, from the viewpoint of statistics, this law is valid at coherent excitation conditions. The property of factorizing for the functioning of this ensemble was obtained.

Energy Metabolism↗

PubMed2003

Ensemble machine learning on gene expression data for cancer classification.

Whole genome RNA expression studies permit systematic approaches to understanding the correlation between gene expression profiles to disease states or different developmental stages of a cell. Microarray analysis provides quantitative information about the complete transcription profile of cells that facilitate drug and therapeutics development, disease diagnosis, and understanding in the basic cell biology. One of the challenges in microarray analysis, especially in cancerous gene expression profiles, is to identify genes or groups of genes that are highly expressed in tumour cells but not in normal cells and vice versa. Previously, we have shown that ensemble machine learning consistently performs well in classifying biological data. In this paper, we focus on three different supervised machine learning techniques in cancer classification, namely C4.5 decision tree, and bagged and boosted decision trees. We have performed classification tasks on seven publicly available cancerous microarray data and compared the classification/prediction performance of these methods. We have observed that ensemble learning (bagged and boosted decision trees) often performs better than single decision trees in this classification task.

Algorithms↗

PubMed1992

Limb blood flow while wearing aircrew chemical defense ensembles in the heat with and without auxiliary cooling.

The effect of auxiliary air cooling on endurance time and limb blood flow in the heat (37 degrees C, 50% r.h., target time = 150 min) while wearing aircrew chemical defense (CD) ensembles was examined. Eight males were dressed in aircrew CD ensembles with or without an air-cooled vest. After an initial 10 min treadmill walk and 20 min of seated rest, the subjects alternately rested and exercised on a cycle ergometer (10 min rest, 10 min exercise) resulting in an overall metabolic rate of 240 W. Arm and leg blood flow (ABF, LBF), determined by venous occlusion plethysmography, were significantly lower with air cooling (AC) than with no cooling (NC) during the same time period (p less than 0.05). Endurance time was much greater with AC than with NC (150 min AC vs. 92 +/- 0.08 min NC, p less than 0.01). Arm and calf skin temperatures, rectal temperature and heart rate were all significantly lower with AC than with NC (p less than 0.05) after the onset of the cycle exercise. The results show that the use of the air-cooled vest under these conditions was able to increase heat tolerance and reduce blood flow to the periphery.

Adult↗

PubMedDate not supplied

[Propagation of spikes in statistical neuron ensembles. I. Concept of phase transitions].

A system of two coupled integro-differential equations for the propagation of sipkes is presented. A qualitative consideration of the system shows possibility of concentrational phase transition in the neuron ensemble from the state of spontaneous firing to the strong periodic oscilltation activity. Naer the point of the phase transition the neuron ensemble becomes labile, which maintains appropriate conditons for the existence of mosaic structures in the neuron network.

Models, Neurological↗

PubMedDate not supplied

[The ensemble organization of the sensorimotor cortex in ontogeny].

Examination of sensomotor zone of the human brain cortex in human subjects (from newborns up to 20 year-olds) with yearly intervals revealed the presence of all neuroglia-vascular ensembles components without any relationship in composition by the moment of birth. Significant increase of the cortical layers and sublayers thickness, connected with growth of the volume of all type neurons and development of dendritic-axonic networks, vessels and glia were noted. Stair-like groups of neurons are present by the moment of birth, and so called racemose groups, the composition of which is diverse in different fields form by the age of three when vertical and horizontal contacts system grows more complicate and the astrocyte glia differentiates. The size of pyramidal neurons (Betz cells included), fusiform and stellate neurons increases by the age of six. By 10-12 years intraensemble, interensemble and transcortical contacts attain the high level of development. By 16-18 years ensemble organization of the cortex reaches the level, characteristic to adults in main parameters of its architectonics.

Adolescent↗

PubMed1997

Influence of a reduced G-suit pressure schedule on G-duration tolerance using enhanced G-protection ensembles.

BACKGROUND: Reducing pressure to enhanced G-protection ensembles may diminish potential undesirable physiologic effects, as well as improve wear comfort and garment durability. HYPOTHESIS: G-duration tolerance will not be affected by reducing pressure to the Swedish tactical flight combat suit (TFCS). A second objective tested the similarity in G-duration tolerance between the TFCS and Combined Advanced Technology Enhanced Design G-Ensemble (COMBAT EDGE) combined with a prototype enhanced coverage G-suit. METHODS: There were 12 Swedish pilots (mean = 30 yr) who experienced gradual onset (+0.1 G.s-1) runs (GOR) to +9 Gz, rapid (+6 G.s-1) onset runs (ROR) and simulated aerial combat maneuvers (SACM) with +5 to +9 Gz cycles. The GOR and ROR profiles had a sustained times of 60 s after reaching +9 Gz. RESULTS: GOR duration tolerance was statistically decreased (p < 0.01) by the lower pressure (1.1 psig.G-1) when compared to standard pressure (1.5 psig.G-1). No statistical difference between TFCS and COMBAT EDGE was observed during the GOR trials. For all conditions, during the RORs, 90% of the subjects completed at least 30 s at +9 Gz. Many technical or medical difficulties during SACM trials limited statistical treatment of these data. However, no obvious among-condition differences were observed. Noteworthy among SACM trials were those of 3 subjects enduring more than 9 min before stopping; one completing 12.5 min (35 cycles). Neither heart rate, blood pressure, nor perceived exertion data revealed a condition-effect difference. CONCLUSION: Moderately reduced pressure to the extended coverage anti-G suit, combined with positive pressure breathing, may yield decreased G-tolerance results during laboratory evaluation; however, observed differences are sufficiently small they are likely operationally insignificant.

Adult↗

PubMed2026

Ensemble DNA methylation clock demonstrates Immune-metabolic aging signatures associated with mortality.

Aging is a multifactorial process that is best described in terms of the progressive acquisition of multiple layers of phenotypic changes, such as epigenetic modifications, inflammation, and metabolic dysregulation. DNA methylation clocks have been extensively used to construct epigenetic clocks based on the DNAm profiles that can be used to estimate biological age and predict age-associated outcomes. Nevertheless, the vast majority of clocks constructed so far have been based on linear models, which are unlikely to fully account for the heterogeneity and non-linearity of survival-related DNAm signatures. In this work, we constructed a heterogeneous stacked ensemble survival model based on DNAm data obtained from the Framingham Heart Study. We first identified 190 CpG loci using elastic net Cox regression and subsequently constructed a survival prediction model based on the fusion of five complementary survival models by means of a neural network meta-learner. The prediction power of the survival model was evaluated in an external validation cohort, where we observed strong performance for predicting all-cause mortality that significantly exceeded PhenoAge and was statistically comparable to GrimAge. These performance estimates were derived in cohorts of European ancestry and externally validated in postmenopausal women aged 50-79 years, and should therefore be interpreted as applicable only to demographically similar populations.

Humans↗

PubMed2000

Computational analysis of two similar neuropeptides yields distinct conformational ensembles.

Conformational states and thermodynamic properties for two similar neuropeptides, GDPFLRF-NH(2) and GYPFLRF-NH(2), have been computed by Monte Carlo simulated annealing (MCSA) conformational searches and Metropolis Monte Carlo (MMC) calculations. These peptides were recently shown to have dramatically different conformations in solution by NMR [Edison et al., J Neuroscience 1999;19:6318-6326]. Final conformations of multiple independent MCSA runs were the starting points for MMC calculations, and conformations saved at intervals during MMC runs were characterized in terms of total energy, configuration entropy, side-chain fraction population, and ensemble average inter-nuclear distances. Without the use of any NMR data-generated pseudo-potentials, the present calculations were in excellent qualitative agreement with all previous NMR experimental data and provided a foundation by which to more quantitatively interpret the experimental NMR results. Proteins 2000;40:367-377.

Computer Simulation↗

PubMed2001

Protein folding simulation with solvent-induced force field: folding pathway ensemble of three-helix-bundle proteins.

We propose a coarse-grained model of proteins that take into account solvent effects and apply it for simulating folding of a three-helix-bundle protein. The energy functional form, refined from our previous work (Takada et al., J Chem Phys 1999;110:11616-11629), tries to closely imitate real physico-chemical interactions. In particular, the hydrogen bond that depends on local dielectric constant, the helix capping effect, and side-chain entropic effects are included. With use of the model, we simulate folding of the GA module of an albumin binding domain, 1prb(7-53), finding most trajectories reach at the native topology within 1 micros. In the simulation, helices 1 and 3 are mostly formed earlier accompanied by non-specific collapse, while second helix is intrinsically less stable and is formed with the help of tertiary contacts at later stage. We compute an analog of the transition state ensemble and compare it with those of other three-helix-bundle proteins. The transition state of 1prb(7-53) includes a few specific tertiary contacts of C terminus of helix 3 with the loop region between helices 1 and 2. This resembles, but is not equivalent to, an early formed region of fragment B of staphylococcal protein A, but is quite different from the folding transient structures of a de novo designed three-helix-bundle peptide.

Albumins↗