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PubMed1998

Ensemble firing of muscle afferents recorded during normal locomotion in cats.

1. The main purpose of this study was to collate population data on the firing characteristics of muscle afferents recorded chronically during normal stepping in cats. 2. Ensemble firing profiles of forty-seven muscle spindle and tendon organ afferents were compiled from stored data. The relationships between the firing profiles and the displacement and force signals were analysed with the help of mathematical models of the response characteristics of spindle primary and secondary afferents and tendon organs. 3. Whereas the firing of hamstring spindle afferents could be predicted with reasonable accuracy from the length and velocity signals alone, the firing profiles of triceps surae spindle afferents deviated from the predicted profiles, particularly during electromyogram (EMG) activity. This indicated that the components of fusimotor action linked to extrafusal muscle activity were significant in triceps surae, possibly because this muscle is more strongly recruited in the cat step cycle. 4. From the limited data available, it was not possible to identify the 'best' or most general mathematical function to predict spindle secondary firing. In the two triceps surae spindle secondary units studied, firing was well predicted by using the simplest possible model, rate proportional to displacement, whereas in the hamstring spindle secondary data, a more complex linear transfer function was needed. The results of modelling the spindle secondary data were consistent with a modest amount of phasic, static fusimotor action linked to EMG activity. 5. The averaged ensemble of tendon organ afferent activity from the triceps surae gave predictions of whole-muscle force that agreed well with separate triceps force measurements in normal cat locomotion. This supports the idea that ensembles of tendon organ afferents signal whole-muscle force. 6. Our overall conclusion is that to a first approximation, large muscle afferents in the cat hindlimb signal muscle velocity, muscle length and muscle force, at least in movements of the speed and amplitude seen in locomotion.

Animals↗

PubMed2006

Ensembles of Bayesian-regularized genetic neural networks for modeling of acetylcholinesterase inhibition by huprines.

Acetylcholinesterase inhibition was modeled for a set of huprines using ensembles of Bayesian-regularized Genetic Neural Networks. In the Bayesian-regularized Genetic Neural Network approach the Bayesian regularization avoids overfitted regressions and the genetic algorithm allows exploring a wide pool of three-dimensional descriptors. The predictive capacity of our selected model was evaluated by averaging multiple validation sets generated as members of neural network ensembles. When 60 members are assembled, the neural network ensemble provides a reliable measure of training and test set R(2)-values of 0.945 and 0.850 respectively. In other respects, the ability of the nonlinear selected genetic algorithm space for differentiate the data were evidenced when total data set was well distributed in a Kohonen self-organizing map. The analysis of the self-organizing map zones allows establishing the main structural features differentiated by our vectorial space.

Acetylcholinesterase↗

PubMed2000

Complex tone processing in primary auditory cortex of the awake monkey. I. Neural ensemble correlates of roughness.

Previous physiological studies [e.g., Bieser and Muller-Preuss, Exp. Brain Res. 108, 273-284 (1996); Schulze and Langner, J. Comp. Physiol. A 181, 651-663 (1997); Steinschneider et al., J. Acoust. Soc. Am. 104, 2935-2955 (1998)] have suggested that neural activity in primary auditory cortex (A1) phase-locked to the waveform envelope of complex sounds with low (<300 Hz) periodicities may represent a neural correlate of roughness perception. However, a correspondence between these temporal response patterns and human psychophysical boundaries of roughness has not yet been demonstrated. The present study examined whether the degree of synchronized phase-locked activity of neuronal ensembles in A1 of the awake monkey evoked by complex tones parallels human psychoacoustic data defining the existence region and frequency dependence of roughness. Stimuli consisted of three consecutive harmonics of fundamental frequencies (f(0)s) ranging from 25 to 4000 Hz. The center frequency of the complex tones was fixed at the best frequency (BF) of the cortical sites, which ranged from 0.3 to 10 kHz. Neural ensemble activity in the thalamorecipient zone (lower lamina III) and supragranular cortical laminae (upper lamina III and lamina II) was measured using multiunit activity and current source density techniques and the degree of phase-locking to the f0 was quantified by spectral analysis. In the thalamorecipient zone, the stimulus f0 at which phase-locking was maximal increased with BF and reached an upper limit between 75 and 150 Hz for BFs greater than about 3 kHz. Estimates of limiting phase-locking rates also increased with BF and approximated psychoacoustic values for the disappearance of roughness. These physiological relationships parallel human perceptual data and therefore support the relevance of phase-locked activity of neuronal ensembles in A1 for the physiological representation of roughness.

Animals↗

PubMed2005

Atmospheric science. Weather forecasting with ensemble methods.

Traditional weather forecasting has been built on a foundation of deterministic modeling--start with initial conditions, put them into a supercomputer model, and end up with a prediction about future weather. But as Gneiting and Raftery discuss in their Perspective, a new approach--ensemble forecasting--was introduced in the early 1990s. In this method, up to 100 different computer runs, each with slightly different starting conditions or model assumptions, are combined into a weather forecast. In concert with statistical techniques, ensembles can provide accurate statements about the uncertainty in daily and seasonal forecasting. The challenge now is to improve the modeling, statistical analysis, and visualization technologies for disseminating the ensemble results.

Journal Article↗

PubMed1993

Dynamics of the hippocampal ensemble code for space.

Ensemble recordings of 73 to 148 rat hippocampal neurons were used to predict accurately the animals' movement through their environment, which confirms that the hippocampus transmits an ensemble code for location. In a novel space, the ensemble code was initially less robust but improved rapidly with exploration. During this period, the activity of many inhibitory cells was suppressed, which suggests that new spatial information creates conditions in the hippocampal circuitry that are conducive to the synaptic modification presumed to be involved in learning. Development of a new population code for a novel environment did not substantially alter the code for a familiar one, which suggests that the interference between the two spatial representations was very small. The parallel recording methods outlined here make possible the study of the dynamics of neuronal interactions during unique behavioral events.

Animals↗

PubMed2000

The Ensemble/Legacy Chimera extension: standardized user and programmer interface to molecular Ensemble data and Legacy modeling programs.

Ensemble/Legacy is a toolkit extension of the Object Technology Framework (OTF) that exposes an object oriented interface for accessing and manipulating ensembles (collections of molecular conformations that share a common chemical topology) and driving Legacy programs (such as MSMS, AMBER, X-PLOR, CORMA/MARDIGRAS, Dials and Windows, and CURVES). Ensemble/Legacy provides a natural programming interface for running Legacy programs on ensembles of molecules and accessing the resulting data. Using the OTF reduces the time cost of developing a new library to store and manipulate molecular data and also allows Ensemble/Legacy to integrate into the Chimera visualization program. The extension to Chimera exposes the Legacy functionality using a graphical user interface that greatly simplifies the process of modeling and analyzing conformational ensembles. Furthermore, all the C++ functionality of the Ensemble/Legacy toolkit is "wrapped" for use in the Python programming language. More detailed documentation on using Ensemble/Legacy is available online (http:¿picasso.nmr.ucsf.edu/dek/ensemble. html).

Computer Graphics↗

PubMed2000

Tuning diversity in bagged ensembles.

In this paper, we investigate how the level of diversity amongst individual neural networks in a bagged ensemble can significantly influence overall ensemble generalization performance. We propose a new technique that tunes this diversity so that ensemble generalization performance is optimized and evaluate its performance on benchmark regression data-sets.

Algorithms↗

PubMed1995

Ensemble competitive learning neural networks with reduced input dimension.

Conventional neural networks utilize all the dimensions of the original input patterns for training and classification. However, a particular attribute of the input patterns does not necessarily contribute to classification and may even cause misclassification in certain cases. A new ensemble competitive learning method using the reduced input dimension is proposed. In contrast to the previous ensemble neural networks which adjust learning parameters, the proposed method takes advantage of the information in each dimension of the input patterns. Since the degree of contribution of each attribute to classification is not known beforehand, the different input data sets with one dimension reduced are presented to multiple neural networks. The classification information from each competitive learning neural network is then combined to make a final decision for classification. In order to improve classification accuracy, the ambiguous output neurons are eliminated which cannot be assigned to any class after training. We use three consensus schemes to judge the classification using ensemble neural networks. The experimental results with remote sensing and speech data indicate the improved performance of the proposed method.

Algorithms↗

PubMed2004

Dynamics of population rate codes in ensembles of neocortical neurons.

Information processing in neocortex can be very fast, indicating that neuronal ensembles faithfully transmit rapidly changing signals to each other. Apart from signal-to-noise issues, population codes are fundamentally constrained by the neuronal dynamics. In particular, the biophysical properties of individual neurons and collective phenomena may substantially limit the speed at which a graded signal can be represented by the activity of an ensemble. These implications of the neuronal dynamics are rarely studied experimentally. Here, we combine theoretical analysis and whole cell recordings to show that encoding signals in the variance of uncorrelated synaptic inputs to a neocortical ensemble enables faithful transmission of graded signals with high temporal resolution. In contrast, the encoding of signals in the mean current is subject to low-pass filtering.

Models, Neurological↗

PubMed1997

Neonatal whisker removal reduces the discrimination of tactile stimuli by thalamic ensembles in adult rats.

Simultaneous recordings of up to 48 single neurons per animal were used to characterize the long-term functional effects of sensory plastic modifications in the ventral posterior medial nucleus (VPM) of the thalamus following unilateral removal of facial whiskers in newborn rats. One year after this neonatal whisker deprivation, neurons in the contralateral VPM responded to cutaneous stimulation of the face at much longer minimal latencies (15.2 +/- 8.2 ms, mean +/- SD) than did normal cells (8.8 +/- 5.3 ms) in the same subregion of the VPM. In 69% of these neurons, the initial sensory responses to stimulus offset were followed for up to 700 ms by reverberant trains of bursting discharge, alternating in 100-ms cycles with inhibition. Receptive fields in the deafferented VPM were also atypical in that they extended over the entire face, shoulder, forepaw, hindpaw, and even ipsilateral whiskers. Discriminant analysis (DA) was then used to statistically evaluate how this abnormal receptive field organization might affect the ability of thalamocortical neuronal populations to "discriminate" somatosensory stimulus location. To standardize this analysis, three stimulus targets ("groups") were chosen in all animals such that they triangulated the central region of the "receptive field" of the recorded multineuronal ensemble. In the normal animals these stimulus targets were whiskers or perioral hairs; in the deprived animals the targets typically included hairy skin of the body as well as face. The measured variables consisted of each neuron's spiking response to each stimulus differentiated into three poststimulus response epochs (0-15, 15-30, and 30-45 ms). DA quantified the statistical contribution of each of these variables to its overall discrimination between the three stimulus sites. In the normal animals, the stimulus locations were correctly classified in 88.2 +/- 3.7% of trials on the basis of the spatiotemporal patterns of ensemble activity derived from up to 18 single neurons. In the deprived animals, the stimulus locations were much less consistently discriminated (reduced to 73.5 +/- 12.6%; difference from controls significant at P < 0.01) despite the fact that much more widely spaced stimulus targets were used and even when up to 20 neurons were included in the ensemble. Overall, these results suggest that neonatal damage to peripheral sense organs may produce marked changes in the physiology of individual neurons in the somatosensory thalamus. Moreover, the present demonstration that these changes can profoundly alter sensory discrimination at the level of neural populations in the thalamus provides important evidence that the well-known perceptual effects of chronic peripheral deprivation may be partially attributable to plastic reorganization at subcortical levels.

Animals↗

PubMed1998

Information about spatial view in an ensemble of primate hippocampal cells.

Hippocampal function was analyzed by making recordings from hippocampal neurons in monkeys actively walking in the laboratory. "Spatial view" cells, which respond when the monkey looks at a part of the environment, were analyzed. To assess quantitatively the information about the spatial environment represented by these cells, we applied information theoretic techniques to their responses. The average information provided by these cells about which location the monkey was looking at was 0.32 bits, and the mean across cells of the maximum information conveyed about which location was being looked at was 1.19 bits, measured in a period of 0.5 s. There were 16 locations for this analysis, each being one-quarter of one of the walls of the room. It also was shown that the mean spontaneous rate of firing of the neurons was 0.1 spikes/s, that the mean firing rate in the center of the spatial field of the neurons was 13.2 spikes/s, and that the mean sparseness of the representation measured in a 25-ms period was 0.04 and in a 500-ms time period was 0.19. (The sparseness is approximately equivalent to the proportion of the 25- or 500-ms periods in which the neurons showed one or more spikes.) Next it was shown that the mean size of the view fields of the neurons was 0.9 of a wall. In an approach to the issue of how an ensemble of neurons might together provide more precise information about spatial location than a single neuron, it was shown that in general the neurons had different centers for their view fields. It then was shown that the information from an ensemble of these cells about where in space is being looked at increases approximately linearly with the number of cells in the ensemble. This indicates that the number of places that can be represented increases approximately exponentially with the number of cells in the population. It is concluded that there is an accurate representation of space "out there" in the primate hippocampus. This representation of space out there would be an appropriate part of a primate memory system involved in memories of where in an environment an object was seen, and more generally in the memory of particular events or episodes, for which a spatial component normally provides part of the context.

Algorithms↗

PubMed1994

A continuum of non-Gaussian self-similar image ensembles with white power spectra.

We introduce a scaling procedure that acts on visual textures to produce new textures having the same resolution, display size, and mean contrast power. We derive the form of the scaling fixed-point textures (image ensembles) resulting from repeated application of this scale transformation to the 'even' texture with an arbitrary amount of sporadic decorrelation. The result is a continuum of scaling fixed-point or 'self-similar' image ensembles, ranging from a strongly non-Gaussian white texture with higher-order spatial correlations at one extreme to Gaussian white noise at the other. The simple construction of a continuum of self-similar ensembles possessing phase correlations provides a tool for investigating human perception of structure in the absence of useful length scales. The fixed-point textures have luminance histogram differences, a direct result of their higher-order spatial properties. This suggests that scaling might afford an extension of our understanding of IID (independent identically distributed) texture discrimination (Chubb et al., J. Opt. Soc. Am. A 11, 2350-2374, 1994) to more general texture discrimination tasks in which spatial correlations play a role.

Form Perception↗

PubMed2006

Ensemble attribute profile clustering: discovering and characterizing groups of genes with similar patterns of biological features.

BACKGROUND: Ensemble attribute profile clustering is a novel, text-based strategy for analyzing a user-defined list of genes and/or proteins. The strategy exploits annotation data present in gene-centered corpora and utilizes ideas from statistical information retrieval to discover and characterize properties shared by subsets of the list. The practical utility of this method is demonstrated by employing it in a retrospective study of two non-overlapping sets of genes defined by a published investigation as markers for normal human breast luminal epithelial cells and myoepithelial cells. RESULTS: Each genetic locus was characterized using a finite set of biological properties and represented as a vector of features indicating attributes associated with the locus (a gene attribute profile). In this study, the vector space models for a pre-defined list of genes were constructed from the Gene Ontology (GO) terms and the Conserved Domain Database (CDD) protein domain terms assigned to the loci by the gene-centered corpus LocusLink. This data set of GO- and CDD-based gene attribute profiles, vectors of binary random variables, was used to estimate multiple finite mixture models and each ensuing model utilized to partition the profiles into clusters. The resultant partitionings were combined using a unanimous voting scheme to produce consensus clusters, sets of profiles that co-occurred consistently in the same cluster. Attributes that were important in defining the genes assigned to a consensus cluster were identified. The clusters and their attributes were inspected to ascertain the GO and CDD terms most associated with subsets of genes and in conjunction with external knowledge such as chromosomal location, used to gain functional insights into human breast biology. The 52 luminal epithelial cell markers and 89 myoepithelial cell markers are disjoint sets of genes. Ensemble attribute profile clustering-based analysis indicated that both lists contained groups of genes with the functional properties of membrane receptor biology/signal transduction and nucleic acid binding/transcription. A subset of the luminal markers was associated with metabolic and oxidoreductase activities, whereas a subset of myoepithelial markers was associated with protein hydrolase activity. CONCLUSION: Given a set of genes and/or proteins associated with a phenomenon, process or system of interest, ensemble attribute profile clustering provides a simple method for collating and sythesizing the annotation data pertaining to them that are present in text-based, gene-centered corpora. The results provide information about properties common and unique to subsets of the list and hence insights into the biology of the problem under investigation.

Algorithms↗

PubMed2005

RNA secondary structure prediction by centroids in a Boltzmann weighted ensemble.

Prediction of RNA secondary structure by free energy minimization has been the standard for over two decades. Here we describe a novel method that forsakes this paradigm for predictions based on Boltzmann-weighted structure ensemble. We introduce the notion of a centroid structure as a representative for a set of structures and describe a procedure for its identification. In comparison with the minimum free energy (MFE) structure using diverse types of structural RNAs, the centroid of the ensemble makes 30.0% fewer prediction errors as measured by the positive predictive value (PPV) with marginally improved sensitivity. The Boltzmann ensemble can be separated into a small number (3.2 on average) of clusters. Among the centroids of these clusters, the "best cluster centroid" as determined by comparison to the known structure simultaneously improves PPV by 46.5% and sensitivity by 21.7%. For 58% of the studied sequences for which the MFE structure is outside the cluster containing the best centroid, the improvements by the best centroid are 62.5% for PPV and 31.4% for sensitivity. These results suggest that the energy well containing the MFE structure under the current incomplete energy model is often different from the one for the unavailable complete model that presumably contains the unique native structure. Centroids are available on the Sfold server at http://sfold.wadsworth.org.

Base Pairing↗

PubMed2003

Scattering mueller matrix of an ensemble of variously shaped small particles.

A description is given of an analytical solution to the scattering Mueller matrix of an ensemble of small particles that may be of different shape, size, composition, and structure. It is derived within the framework of the generalized multiparticle Mie solution (GMM). Provided that all individual T matrices of a group of particles are known analytically or can be computed accurately, light scattering by an arbitrary configuration of these particles can be predicted precisely for both fixed and random orientations. In practical implementations, the applicability of the solution is limited by the size of individual particles only, and there is no restriction on the overall dimension of an ensemble. This multiparticle-scattering formulation of the GMM has been implemented in several public-domain computer codes. In practical calculations, the maximum total number of particles in an ensemble that can be handled depends on the largest size of the individual components and the availability of computer memory.

Journal Article↗

PubMed2004

Energy spectrum of a nonstationary ensemble of pulses.

We introduce a new definition of the energy spectrum of a nonstationary ensemble of pulses that reduces to the usual ones in the limit of statistically stationary ensembles of signals and of fully temporarily coherent ensembles.

Journal Article↗

PubMed2004

The ventral striatum in off-line processing: ensemble reactivation during sleep and modulation by hippocampal ripples.

Previously it has been shown that the hippocampus and neocortex can spontaneously reactivate ensemble activity patterns during post-behavioral sleep and rest periods. Here we examined whether such reactivation also occurs in a subcortical structure, the ventral striatum, which receives a direct input from the hippocampal formation and has been implicated in guidance of consummatory and conditioned behaviors. During a reward-searching task on a T-maze, flanked by sleep and rest periods, parallel recordings were made from ventral striatal ensembles while EEG signals were derived from the hippocampus. Statistical measures indicated a significant amount of reactivation in the ventral striatum. In line with hippocampal data, reactivation was especially prominent during post-behavioral slow-wave sleep, but unlike the hippocampus, no decay in pattern recurrence was visible in the ventral striatum across the first 40 min of post-behavioral rest. We next studied the relationship between ensemble firing patterns in ventral striatum and hippocampal ripples-sharp waves, which have been implicated in pattern replay. Firing rates were significantly modulated in close temporal association with hippocampal ripples in 25% of the units, showing a marked transient enhancement in the average response profile. Strikingly, ripple-modulated neurons in ventral striatum showed a clear reactivation, whereas nonmodulated cells did not. These data suggest, first, the occurrence of pattern replay in a subcortical structure implied in the processing and prediction of reward and, second, a functional linkage between ventral striatal reactivation and a specific type of high-frequency population activity associated with hippocampal replay.

Action Potentials↗

PubMed2005

Exploring the helix-coil transition via all-atom equilibrium ensemble simulations.

The ensemble folding of two 21-residue alpha-helical peptides has been studied using all-atom simulations under several variants of the AMBER potential in explicit solvent using a global distributed computing network. Our extensive sampling, orders of magnitude greater than the experimental folding time, results in complete convergence to ensemble equilibrium. This allows for a quantitative assessment of these potentials, including a new variant of the AMBER-99 force field, denoted AMBER-99 phi, which shows improved agreement with experimental kinetic and thermodynamic measurements. From bulk analysis of the simulated AMBER-99 phi equilibrium, we find that the folding landscape is pseudo-two-state, with complexity arising from the broad, shallow character of the "native" and "unfolded" regions of the phase space. Each of these macrostates allows for configurational diffusion among a diverse ensemble of conformational microstates with greatly varying helical content and molecular size. Indeed, the observed structural dynamics are better represented as a conformational diffusion than as a simple exponential process, and equilibrium transition rates spanning several orders of magnitude are reported. After multiple nucleation steps, on average, helix formation proceeds via a kinetic "alignment" phase in which two or more short, low-entropy helical segments form a more ideal, single-helix structure.

Algorithms↗