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PubMed2003

Computational approaches to motor control and their potential role for interpreting motor dysfunction.

PURPOSE OF REVIEW: Computational frameworks, notably internal models and optimal control theory, have led to rapid advances in our understanding of how the brain plans and controls movement. The purpose of this review is to provide an overview of these theoretical ideas, how they have been used to interpret motor control, as well as their potential role for interpreting motor dysfunction. RECENT FINDINGS: There are two general types of internal models, neural processes that mimic the mechanical properties of the limb (and environment). Forward internal models parallel the normal causal flow of the motor periphery and estimate limb motion from motor commands. Inverse internal models perform the reverse process by estimating motor commands from signals related to intended limb motion and/or spatial targets. This framework has led to several important behavioural observations on motor planning, control and learning, and has also been influential for interpreting neural activity in awake, behaving non-human primates. A more recent framework for interpreting motor function is optimal control theory, which recognizes that noise or errors are an inherent feature of the motor system and may influence strategies to plan and control movement. SUMMARY: Internal models and optimal feedback control both provide frameworks for interpreting motor performance, and may be of value for interpreting many motor dysfunctions associated with neurological injuries. Advanced technologies such as robots that have played a key role in these frameworks may be also of considerable value for motor assessment and rehabilitation.

Animals↗

PubMed2003

An empirical model for electrostatic interactions in proteins incorporating multiple geometry-dependent dielectric constants.

Here we introduce an electrostatic model that treats the complexity of electrostatic interactions in a heterogeneous protein environment by using multiple parameters that take into account variations in protein geometry, local structure, and the type of interacting residues. The optimal values for these parameters were obtained by fitting the model to a large dataset of 260 experimentally determined pK(a) values distributed over 41 proteins. We obtain fits between the calculated and observed values that are significantly better than the null model. The model performs well on the groups that exhibit large pK(a) shifts from solution values in response to the protein environment and compares favorably with other, successful continuum models. The empirically determined values of the parameters correlate well with experimentally observed contributions of hydrogen bonds and ion pairs as well as theoretically predicted magnitudes of charge-charge and charge-polar interactions. The magnitudes of the dielectric constants assigned to different regions of the protein rank according to the strength of the relaxation effects expected for the core, boundary, and surface. The electrostatic interactions in this model are pairwise decomposable and can be calculated rapidly. This model is therefore well suited for the large computations required for simulating protein properties and especially for prediction of mutations for protein design.

Algorithms↗

PubMed1999

Dynamic models for nonstationary signal segmentation.

This paper investigates Hidden Markov Models (HMMs) in which the observations are generated from an autoregressive (AR) model. The overall model performs nonstationary spectral analysis and automatically segments a time series into discrete dynamic regimes. Because learning in HMMs is sensitive to initial conditions, we initialize the HMM model with parameters derived from a cluster analysis of Kalman filter coefficients. An important aspect of the Kalman filter implementation is that the state noise is estimated on-line. This allows for an initial estimation of AR parameters for each of the different dynamic regimes. These estimates are then fine-tuned with the HMM model. The method is demonstrated on a number of synthetic problems and on electroencephalogram data.

Algorithms↗

PubMed2002

Population pharmacokinetic and limited sampling models for carboplatin administered in high-dose combination regimens with peripheral blood stem cell support.

OBJECTIVE: By means of a nonlinear mixed effect modeling technique, a population pharmacokinetic (PK) model was developed to evaluate the effects of a variety of covariates on clearance and other pharmacokinetic parameters of ultrafilterable carboplatin administered in high-dose combination regimens with peripheral blood stem cell support. In addition, single-sample and two-sample limited sampling models (LSMs) were derived to estimate carboplatin's AUC that could be used in the design of drug dosing regimens. METHODS: A total of 44 female patients with advanced ovarian cancer participated in two phase I studies. All 44 patients received a high-dose carboplatin chemotherapy with other anticancer drugs. A population PK model was applied to the plasma concentration-time data of ultrafilterable carboplatin using the NONMEM and Xpose computer programs. The Xpose program utilized a general additive modeling technique to identify significant patient covariates and PK parameter relationships. The resultant PK model was validated using a bootstrap method. Stepwise linear regression analyses were used to develop LSMs based on the correlation between carboplatin's AUC and plasma concentrations. RESULTS: The best structural covariate-free model for high-dose carboplatin was a linear two-compartment model with an exponential error model to account for intersubject variability and a CCV error model to account for intrasubject variability. Subsequently, a final covariate model for clearance (l/min) was obtained as follows: TVCL=0.101+0011*(WT-62.35)-0.0658*(SCR-0.65) where WT is body weight (kg) and SCR is serum creatinine (mg/dl). Both WT and SCR were found to significantly influence carboplatin's total clearance. It was determined that the best single-sample LSM was AUC(LSM)=0.553*C(240min) ( r=0.998). CONCLUSION: Both a population PK model and a LSM for high-dose carboplatin were developed following its administration in combination chemotherapeutic regimens with peripheral blood stem cell support. In both cases, the models performed well when analyzed in the context of the retrospective and bootstrap analyses. Prospective studies in ovarian cancer patients should be conducted to further tailor the current models.

Adult↗

PubMed2004

Cellular parameters for track structure modeling of radiation hazard in space.

Based on irradiation with 45 MeV/u N and B ions and with Co-60 gamma rays, cellular parameters of Katz's track structure model have been fitted for the survival of V79-379A Chinese hamster lung fibroblasts. Cellular parameters representing neoplastic transformations in C3H10T/1/2 cells after their irradiation with heavy ion beams, taken from earlier work, were also used to model the radiation hazard in deep space, following the system for evaluating, summing and reporting occupational exposures proposed in 1967 by a subcommittee of NCRP. We have performed model calculations of the number of transformations in surviving cells, after a given fluence of heavy charged particles of initial energy 500 MeV/u, penetrating thick layers of cells. We take the product of cell transformation and survival probabilities, calculated along the path lengths of charged particles using cellular survival and transformation parameters, to represent a quantity proportional to the "radiation risk factor" discussed in the NCRP document. The "synergistic" effect of simultaneous charged particle transfers is accounted for by the "track overlap" mode inherent in the model of Katz.

Animals↗

PubMed2005

Functional multi-layer perceptron: a non-linear tool for functional data analysis.

In this paper, we study a natural extension of multi-layer perceptrons (MLP) to functional inputs. We show that fundamental results for classical MLP can be extended to functional MLP. We obtain universal approximation results that show the expressive power of functional MLP is comparable to that of numerical MLP. We obtain consistency results, which imply that the estimation of optimal parameters for functional MLP is statistically well defined. We finally show on simulated and real world data that the proposed model performs in a very satisfactory way.

Algorithms↗

PubMed2000

At-line monitoring of a submerged filamentous bacterial cultivation using near-infrared spectroscopy.

The use of near infra-red spectroscopy (NIRS) to monitor a submerged filamentous bacterial bioprocess was investigated. An industrial strain of the filamentous bacterium Streptomyces fradiae was cultured in a 12 litre stirred tank reactor (STR) using a complex medium. This mycelial 4 phase (oil, water, gas and solid) system produced highly complex and variable matrices, therefore monitoring such a complex fluid with NIRS represented a considerable challenge. Nevertheless, successful models for four key analytes (methyl oleate, glucose, glutamate and ammonium) were built at-line (rapid off-line) using NIRS. In the present study, the methods used to formulate, select and validate the models for the key analytes are discussed, with particular emphasis on how the model performance can be critically evaluated. Since previous reports on NIRS in monitoring bioprocesses have either involved simpler matrices, or, in filamentous systems, have not discussed how NIRS models can be critically assessed, the emphasis in the present study on providing an insight into the modelling process in such a complex matrix, may be particularly important to the applicability of NIRS to such industrial bioprocesses.

Journal Article↗

PubMed2001

Trunk posture and spinal stability.

OBJECTIVE: The influence of trunk posture on musculoskeletal stability of the spine was investigated. DESIGN: A biomechanical model was developed to evaluate the influence of posture on spinal stability. Model performance was assessed by comparing predicted muscle recruitment patterns with measured EMG activity from the trunk muscles during static lifting exertions. METHOD: An inverted double-pendulum model of the spine controlled by 12 muscle equivalents of the trunk was implemented to determine spinal load and stability. Model input included trunk posture and lifted mass, output included muscle recruitment patterns necessary to achieve stability of the spine and spinal load. EMG activity recorded from the trunk muscles of 10 subjects were recorded during static exertions in various trunk flexion and asymmetric postures to compare with model output. Stable spinal load was examined as a function of trunk flexion and asymmetry during the lifting exertions. RESULTS: Antagonistic co-contraction was necessary to achieve spinal stability, particularly in upright postures. Stable spinal load was increased in asymmetric postures as a result of antagonistic muscle recruitment, suggesting greater neuromuscular control is necessary to maintain stability in asymmetric lifting postures. As trunk flexion angle increased, stability improved but spinal load was greater. CONCLUSIONS: Results illustrate that muscle recruitment patterns are more accurately explained by stability than by equilibrium alone. Spinal stability is influenced by posture. Specifically, control of spinal stability is reduced in asymmetric postures associated with low-back disorder risk. RELEVANCE: Traditional assessment of low-back disorder risk have focussed on spinal loading. Results illustrate that postural risk factors for low-back pain may be partially attributable to stability considerations.

Adult↗

PubMed1995

Afferent synaptic drive of rat medial nucleus tractus solitarius neurons: dynamic simulation of graded vesicular mobilization, release, and non-NMDA receptor kinetics.

1. We have developed a comprehensive mathematical model of an afferent synaptic connection to the soma of a medial nucleus tractus solitarius (mNTS) neuron. Model development is based on numerical fits to quantitative data recorded in our laboratory. This work is part of a continuing collaborative effort aimed at identifying and characterizing the mechanisms responsible for the non-linear integrative properties of this first synapse in the baroreceptor reflex. 2. The complete model consists of three major parts: 1) a Hodgkin-Huxley (HH)-type membrane model of the prejunctional sensory terminal bouton; 2) a multistage model describing vesicular storage, adenosine 3',5'-cyclic monophosphate (cAMP)- and Ca(2+)-dependent mobilization, release and recycling; and 3) a HH-type membrane model of the postjunctional mNTS cell that includes descriptions for a desensitizing non-N-methyl-D-aspartate (NMDA) ionic current that is responsible for the fast excitatory postsynaptic potentials (EPSPs) observed in mNTS cells. The membrane models for both the terminal bouton and the mNTS neuron are coupled to separate lumped fluid compartment models describing intracellular Ca2+ ion concentration dynamics. 3. Our modeling strategy is twofold. The first is to validate model performance by reproducing a wide variety of experimental data both from our laboratory and from the literature. The second is to explore the functional aspects of the model in order to gain a greater appreciation for the balance between presynaptic mechanisms (e.g., terminal membrane properties and vesicular dynamics) and postsynaptic mechanisms (e.g., non-NMDA receptor kinetics and neuronal dynamics) that underlie the afferent synaptic drive of mNTS neurons. 4. The model accurately reproduces EPSP dynamics recorded with the use of a wide range of stimulus protocols. The model can also mirror the unique pattern of graded frequency- and use-dependent reduction in peak EPSP magnitude observed experimentally through 60 s of constant, suprathreshold synaptic activation. We demonstrate how vesicular mobilization, recycling, and receptor kinetics can function synergistically in establishing synaptic transfer. Furthermore, we show that by allowing the aggregate rate of vesicle mobilization to respond in a use-dependent manner, it is possible to compensate for the attenuating affects of desensitization at elevated rates of stimulation. 5. Our simulations indicate that the low-frequency characteristics of this synapse are dominated by vesicular dynamics, whereas the high-frequency properties arise from a combination of Ca(2+)-dependent vesicular mobilization and the kinetics of the non-NMDA receptor. Desensitization can influence the peak magnitude and decay time of the EPSP, thereby affecting synaptic throughput. However, we demonstrate that, as the time course of neurotransmitter in the synaptic cleft decreases, the influence of desensitization should be somewhat diminished. As a result, the effective bandwidth of the synapse increases and becomes limited by the gating characteristics of the non-NMDA channel. 6. The model also includes a neuromodulatory aspect in that the frequency response of the synapse can be modulated by an adenylate cyclase-mediated regulatory mechanism. Although our simulations indicate the behavior of a limited number of possible neuromodulatory agents, the results demonstrate the pivotal role such agents could play in modifying synaptic transfer characteristics presynaptically. 7. Both continuous and burst-mode tract stimulation evoke patterns of action potentials in spontaneously active mNTS neurons that are mimicked very well by our model. Our simulations demonstrate that, as the rate of stimulation increases beyond approximately 20-30 Hz, the inherent low-pass frequency-response characteristics of the synapse limit the overall dynamic range of the mNTS neuron, causing the postsynaptic cell to "entrain" at frequencies within its normal operating range.

Afferent Pathways↗

PubMed2000

Least-cost ration formulations for Holstein dairy heifers by using linear and stochastic programming.

Four mathematical programming models were developed to formulate rations for large breed replacement dairy heifers in each of 11 different weight classes from 50 to 550 kg and daily growth rates of 600, 700, and 800 g, with the objective of achieving a final calving weight of 600 kg. First, a base linear programming model was developed; then, to account for variability in the crude protein content of ration ingredients three other methods were used: right-hand side adjustment, incorporation of a safety margin, and stochastic programming. The average daily cost to calving, given a daily gain of 600, 700, and 800 g, was $0.62, $0.64, and $0.68, respectively. The total feed cost to 600 kg was $89.87 more for a growth rate of 600 over 800 g/d. The stochastic programming model performed better, on the bases of cost and protein-feeding, than did the right-hand side adjustment or the safety margin methods. The stochastic programming model over-adjusted crude protein by 5% and cost an average of 3.5% more than the linear programming solution for a dairy heifer growing at 800 g/d with a desired probability of 80% of crude protein intake achieving the NRC minimum. The other two methods over-adjusted crude protein by 10 and 13% and cost an extra 5.5 and 7.6%, respectively, for the right-hand side adjustment and the safety margin methods.

Animal Feed↗

PubMed1994

Identification of dynamic myoelectric signal-to-force models during isometric lumbar muscle contractions.

A 14-muscle myoelectric signal (MES)-driven muscle force prediction model of the L3-L4 cross section is developed which includes a dynamic MES-force relationship and allows for cocontraction. Model parameters are estimated from MES and moments data recorded during rapid exertions in trunk flexion, extension, lateral bending and axial twist. Nine young healthy males participated in the experimental testing. The model used in the parameter estimation is of the output error type. Consistent and physically feasible parameter estimates were obtained by normalizing the RMS MES to maximum exertion levels and using nonlinear constrained optimization to minimize a cost function consisting of the trace of the output error covariance matrix. Model performance was evaluated by comparing measured and MES-predicted moments over a series of slow and rapid exertions. Moment prediction errors were on the order of 25, 30 and 40% during attempted trunk flexion-extensions, lateral bends and axial twists, respectively. The model and parameter estimation methods developed provide a means to estimate lumbar muscle and spine loads, as well as to empirically investigate the use and effects of cocontraction during physical task performances.

Adult↗

PubMed2006

Semicircular canal geometry, afferent sensitivity, and animal behavior.

The geometry of the semicircular canals has been used in evolutionary studies to predict the behaviors of extinct animals. These predictions have relied on an assumption that the responses of the canals can be determined from their dimensions, and that an organism's behavior can be determined from these responses. However, the relationship between a canal's sensitivity and its size is not well known. An intraspecies comparison among canal responses in each of three species (cat, squirrel monkey, and pigeon) was undertaken to evaluate various models of canal function and determine how their dimensions may be related to afferent physiology. All models predicted the responses of the cat afferents, but the models performed less well for squirrel monkey and pigeon. Possible causes for this discrepancy include incorrectly assuming that afferent responses accurately represent canal function or errors in current biophysical models of the canals. These findings leave open the question as to how reliably canal anatomy can be used to estimate afferent responses and how closely afferent responses are related to behavior. Other labyrinthine features, such as orientation of the horizontal canal, which is reliably held near earth-horizontal across many species, may be better to use when extrapolating the posture and related behavior of extinct animals from labyrinthine morphology.

Animals↗

PubMed2000

In vivo detection of dysplastic tissue by Raman spectroscopy.

The detection of dysplasia and early cancer is important because of the improved survival rates associated with early treatment of cancer. Raman spectroscopy is sensitive to the changes in molecular composition and molecular conformation that occur in tissue during carcinogenesis, and recent developments in fiber-optic probe technology enable its application as an in vivo technique. In this study, the potential of Raman spectroscopy for in vivo classification of normal and dysplastic tissue was investigated. A rat model was used for this purpose, in which dysplasia in the epithelium of the palate was induced by topical application of the carcinogen 4-nitroquinoline 1-oxide. High quality in vivo spectra of normal and dysplastic rat palate tissue, obtained using signal integration times of 100 s were used to create tissue classification models based on multivariate statistical analysis methods. These were tested with an independent set of in vivo spectra, obtained using signal collection times of 10 s. The best performing model, in which signal variance due to signal contributions of the palatal bone was eliminated, was able to distinguish between normal tissue, low-grade dysplasia, and high-grade dysplasia/carcinoma in situ with a selectivity of 0.93 and a sensitivity of 0.78 for detecting low-grade dysplasia and a specificity of 1 and a sensitivity of 1 for detecting high-grade dysplasia/ carcinoma in situ.

Animals↗

PubMed2004

Comparison of Li-Wong and loglinear mixed models for the statistical analysis of oligonucleotide arrays.

MOTIVATION: Li and Wong have described some useful statistical models for probe-level, oligonucleotide array data based on a multiplicative parametrization. In earlier work, we proposed similar analysis-of-variance-style mixed models fit on a log scale. With only subtle differences in the specification of their mean and stochastic error components, a question arises as to whether these models could lead to varying conclusions in practical application. RESULTS: In this paper, we provide an empirical comparison of the two models using a real data set, and find the models perform quite similarly across most genes, but with some interesting and important distinctions. We also present results from a simulation study designed to assess inferential properties of the models, and propose a modified test statistic for the Li-Wong model that provides an improvement in Type 1 error control. Advantages of both methods include the ability to directly assess and account for key sources of variability in the chip data and a means to automate statistical quality control.

Algorithms↗

PubMed1998

Blood lead slope factor models for adults: comparisons of observations and predictions.

Here we explore the appropriateness of various parameter values for the Bowers et al. model [Risk Anal 14:183-189, 1994] in the context of predicting the influence of site-related exposure to lead in soil on the blood lead (PbB) levels of women of childbearing age. We outline the parameters prescribed by Bowers et al. as well as those prescribed by the U.S. Environmental Protection Agency (U.S. EPA). Comparison of the PbB levels predicted by the Bowers et al. model to those predicted by the validated O'Flaherty pharmacokinetic model indicates that the Bowers et al. model performs favorably when parameter values prescribed here are used. Use of the U.S. EPA-prescribed parameters yields predicted PbB levels that substantially exceed the validated O'Flaherty model predictions. Finally, both the U.S. EPA-prescribed parameter values and the parameter values recommended herein are used to predict PbB levels among adults living in four Superfund communities. Comparison of predicted PbB levels for these communities indicates that the U.S. EPA parameters overstate the incremental influence of lead in soil on PbB levels. Differences between the parameter values prescribed here and the U.S. EPA-prescribed parameters yield substantially different cleanup criteria for lead in soil, although conservative parameter values may still be appropriate for screening purposes.

Adult↗

PubMed2001

Compilation and evaluation of a Paso del Norte emission inventory.

Emission inventories of ozone precursors are routinely used as input to comprehensive photochemical air quality models. Photochemical model performance and the development of effective control strategies rely on the accuracy and representativeness of an underlying emission inventory. This paper describes the tasks undertaken to compile and evaluate an ozone precursor emission inventory for the El Paso/Ciudad Juárez/Southern Doña Ana region. Point, area and mobile source emission data were obtained from local government agencies and were spatially and temporally allocated to a gridded domain using region-specific demographic and land-cover information. The inventory was then processed using the US Environmental Protection Agency (EPA) recommended Emissions Preprocessor System 2.0 (UAM-EPS 2.0) which generates emissions files compatible with the Urban Airshed Model (UAM). A top down evaluation of the emission inventory was performed to examine how well the inventory represented ambient pollutant compositions. The top-down evaluation methodology employed in this study compares emission inventory ratios of non-methane hydrocarbon (NMHC)/nitrogen oxide (NOx) and carbon monoxide (CO)/NOx ratios to corresponding ambient ratios. Detailed NMHC species comparisons were made in order to investigate the relative composition of individual hydrocarbon species in the emission inventory and in the ambient data. The emission inventory compiled during this effort has since been used to model ozone in the Paso del Norte airshed (Emery et al., CAMx modeling of ozone and carbon monoxide in the Paso del Norte airshed. In: Proc of Ninety-Third Annual Meeting of Air & Waste Management Association, 18-22 June 2000, Air & Waste Management Association, Pittsburgh, PA, 2000).

Databases, Factual↗

PubMed1995

A model for global symmetry detection in dense images.

In this paper, a model is proposed for bilateral symmetry detection in images consisting of dense arrangements of local features. The model is elaborated on the basis of a psychophysical experiment showing that grouping precedes and facilitates symmetry detection. The proposed computational model consists of three stages: a grouping stage, a symmetry-detection stage, and a symmetry-subsumption stage. Reliance upon a preliminary grouping stage enables a significant reduction of the computational load for detecting symmetry. An implementation of the model is described, and results are presented, showing a good agreement of the model performance with human symmetry perception.

Computer Simulation↗

PubMed2002

An oscillatory correlation model of visual motion analysis.

We describe and evaluate a model of motion perception based on the integration of information from two parallel pathways: a motion pathway and a luminance pathway. The motion pathway has two stages. The first stage measures and pools local motion across the input animation sequence and assigns reliability indices to these pooled measurements. The second stage groups locations on the basis of these measurements. In the luminance pathway, the input scene is segmented into regions on the basis of similarities in luminance. In a subsequent integration stage, motion and luminance segments are combined to obtain the final estimates of object motion. The neural network architecture we employ is based on LEGION (locally excitatory globally inhibitory oscillator networks), a scheme for feature binding and region labeling based on oscillatory correlation. Many aspects of the model are implemented at the neural network level, whereas others are implemented at a more abstract level. We apply this model to the computation of moving, uniformly illuminated, two-dimensional surfaces that are either opaque or transparent. Model performance replicates a number of distinctive features of human motion perception.

Humans↗