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G Sparacino

Publications and source records attributed to G Sparacino.

At least 19 recordsLinked to original sources
PubMed2004

Method for the deconvolution of auditory steady-state responses.

The potential evoked by a 'train' of N equally spaced auditory clicks, with an inter-click period shorter than the duration of the response to an isolated click, is said to be a steady-state response (SSR). Extracting the individual responses evoked by the clicks of the train during steady state can be key to understanding of the neurophysiological mechanisms underlying SSR generation. In the literature, this task has been dealt with only under the (unwarranted) assumption that the response of the system does not vary during the presentation of the clicks, i.e. no neurophysiological adaptation is present. In this work, a new, non-parametric algorithm is proposed that, relaxing the time-invariance hypothesis, allows the extraction from the SSR of the N waveforms individually evoked by the N clicks of the train. The performance of the approach is evaluated on simulated SSRs and on real data recorded from the temporal cortex of awake rats. Results show that the method is able to detect and assess possible adaptation of the neurophysiological system in the generation of SSRs.

Acoustic Stimulation↗
PubMed2001

Reconstructing insulin secretion rate after a glucose stimulus by an improved stochastic deconvolution method.

Reconstructing insulin secretion rate (ISR) after a glucose stimulus by deconvolution is difficult because of its biphasic pattern, i.e., a rapid secretion peak is followed by a slower release. Here, we refine a recently proposed stochastic deconvolution method by modeling ISR as the multiple integration of a white noise process with time-varying statistics. The unknown parameters are estimated from the data by employing a maximum likelihood criterion. A fast computational scheme implementing the method is presented. Monte Carlo simulation results are developed which numerically show a more reliable ISR profile reconstructed by the new method.

Biomedical Engineering↗
PubMed2000

Compound action potential and cochlear microphonic extracted from electrocochleographic responses to condensation or rarefaction clicks.

In electrocochleography (ECochG) compound action potential (CAP) and summation potential (SP) are usually separated from the cochlear microphonic (CM) by the CM cancellation technique consisting in averaging the responses evoked by rarefaction and condensation clicks. With the aim of analysing the ECochG responses evoked by monophasic clicks, we developed a numerical method based on the theory of optimal filtering, which makes no assumptions about the unknown potentials. The application of the filtering technique to the ECochG recordings obtained from 6 normally hearing children and 10 children with cochlear hearing loss allowed us to perform CAP extraction in cases where CM was not cancelled by the conventional method. Differences in SP amplitude and polarity were found between rarefaction and condensation click-evoked responses in cochlear hearing losses.

Acoustic Stimulation↗
PubMed2000

Maximum-likelihood versus maximum a posteriori parameter estimation of physiological system models: the C-peptide impulse response case study.

Maximum-likelihood (ML), also given its connection to least-squares (LS), is widely adopted in parameter estimation of physiological system models, i.e., assigning numerical values to the unknown model parameters from the experimental data. A more sophisticated but less used approach is maximum a posteriori (MAP) estimation. Conceptually, while ML adopts a Fisherian approach, i.e., only experimental measurements are supplied to the estimator, MAP estimation is a Bayesian approach, i.e., a priori available statistical information on the unknown parameters is also exploited for their estimation. In this paper, after a brief review of the theory behind ML and MAP estimators, we compare their performance in the solution of a case study concerning the determination of the parameters of a sum of exponential model which describes the impulse response of C-peptide (CP), a key substance for reconstructing insulin secretion. The results show that MAP estimation always leads to parameter estimates with a precision (sometimes significantly) higher than that obtained through ML, at the cost of only a slightly worse fit. Thus, a three exponential model can be adopted to describe the CP impulse response model in place of the two exponential model usually identified in the literature by the ML/LS approach. Simulated case studies are also reported to evidence the importance of taking into account a priori information in a data poor situation, e.g., when a few or too noisy measurements are available. In conclusion, our results show that, when a priori information on the unknown model parameters is available, Bayes estimation can be of relevant interest, since it can significantly improve the precision of parameter estimates with respect to Fisher estimation. This may also allow the adoption of more complex models than those determinable by a Fisherian approach.

Bayes Theorem↗
PubMed2000

Bayesian identification of a population compartmental model of C-peptide kinetics.

When models are used to measure or predict physiological variables and parameters in a given individual, the experiments needed are often complex and costly. A valuable solution for improving their cost effectiveness is represented by population models. A widely used population model in insulin secretion studies is the one proposed by Van Cauter et al. (Diabetes 41:368-377, 1992), which determines the parameters of the two compartment model of C-peptide kinetics in a given individual from the knowledge of his/her age, sex, body surface area, and health condition (i.e., normal, obese, diabetic). This population model was identified from the data of a large training set (more than 200 subjects) via a deterministic approach. This approach, while sound in terms of providing a point estimate of C-peptide kinetic parameters in a given individual, does not provide a measure of their precision. In this paper, by employing the same training set of Van Cauter et al., we show that the identification of the population model into a Bayesian framework (by using Markov chain Monte Carlo) allows, at the individual level, the estimation of point values of the C-peptide kinetic parameters together with their precision. A successful application of the methodology is illustrated in the estimation of C-peptide kinetic parameters of seven subjects (not belonging to the training set used for the identification of the population model) for which reference values were available thanks to an independent identification experiment.

Adult↗
PubMed2000

Approximate entropy studies of hormone pulsatility from plasma concentration time series: influence of the kinetics assessed by simulation.

Approximate entropy (ApEn) is a method developed in the early nineties to quantify the "regularity" of a time series. In recent years, it has been vigorously employed to study the oscillatory/pulsatile secretory behavior of many hormones and found capable of successfully identifying pathological or prepathological states characterized by an enhanced secretion irregularity. Since hormone secretion rate is nonaccessible to direct measurement, ApEn is usually calculated from the time series of the hormone concentrations in plasma. However, the plasma concentration time course also reflects the whole-body kinetics of the hormone and can thus only provide a distorted portrait of the secretion rate at the gland level. In this paper, we investigate by simulation whether and how this distortion can influence the study of the regularity of hormone pulsatility by ApEn. Pulsatile secretion time series with different degrees of irregularity are simulated by varying the statistics of the random parameters which describe the secretory pulses. Then, plasma concentration time series are obtained by convolution with the hormone impulse response. Different degrees of impulse response smoothness are also considered in order to vary the amount of the distortion introduced. Results show that ApEn computed from secretion time series consistently discriminated better than ApEn calculated from plasma concentration time series among processes with different degrees of regularity. In addition, smoother impulse responses decreased the ApEn differences between plasma concentration time series corresponding to different degrees of secretion regularity. Therefore, the power of the ApEn index in the study of hormone pulsatility can potentially be enhanced by applying it to the hormone secretion time series.

Algorithms↗
PubMed1997

Removal of catheter distortion in multiple indicator dilution studies: a deconvolution-based method and case studies on glucose blood-tissue exchange.

The study of blood-tissue exchange by the multiple indicator dilution technique often needs frequent sampling in the blood of the indicator dilution curves (IDC). Usually, this requires the use of a catheter supported by a pump. This causes a distortion in the IDC, which must be removed for proper interpretation of the data. A deconvolution-based methodology to remove IDC distortion is presented. First, the catheter impulse response is modelled by means of data obtained from a suitable experiment. Then the reconstruction of the blood IDC is tackled by a new nonparametric deconvolution algorithm, which provides (quasi) time-continuous signals and exploits statistically based criteria for the choice of the regularisation parameter. The methodology is applied to the removal of catheter distortion in studies of glucose blood-tissue exchange in the human forearm and myocardium.

Blood Glucose↗
PubMed1997

Estimation of endogenous glucose production after a glucose perturbation by nonparametric stochastic deconvolution.

The knowledge of the time course of endogenous glucose production (EGP) after a glucose perturbation is crucially important for understanding the glucose regulation system in both healthy and disease (e.g. diabetes) states. EGP is not directly accessible, and thus an indirect measurement approach is required. The estimation of EGP during an intravenous glucose tolerance test (IVGTT) can be posed as an input estimation problem solvable as a Fredholm integral equation of the first kind (A. Caumo and C. Cobelli, Am. J. Physiol., 264 (1993) E829-E841). The time-varying model of the kernel of the glucose system was identified from a concomitant tracer experiment, and EGP was reconstructed by employing the Phillips-Tikhonov regularization (deconvolution) algorithm. However, the proposed deconvolution approach left some issues open, e.g. how to choose the amount of regularization and how to deal with nonuniform/infrequent sampling. Here, a solution to these problems is provided by resorting to a new deconvolution algorithm. Thanks to the stochastic embedding into which the new deconvolution method is stated, the amount of regularization is determined in a statistically sound manner. In addition, in face of infrequent sampling, a time continuous profile of EGP is obtained. The method is shown to work reliably for reconstructing EGP in different IVGTT experimental protocols, both in normal and disease states.

Algorithms↗
PubMed1996

A stochastic deconvolution method to reconstruct insulin secretion rate after a glucose stimulus.

Insulin secretion rate (ISR) is not directly measurable in man but it can be reconstructed from C-peptide (CP) concentration measurements by solving an input estimation problem by deconvolution. The major difficulties posed by the estimation of ISR after a glucose stimulus, e.g., during an intravenous glucose tolerance test (IVGTT), are the ill-conditioning of the problem, the nonstationary pattern of the secretion rate, and the nonuniform/infrequent sampling schedule. In this work, a nonparametric method based on the classic Phillips-Tikhonov regularization approach is presented. The problem of nonuniform/infrequent sampling is addressed by a novel formulation of the regularization method which allows the estimation of quasi time-continuous input profiles. The input estimation problem is stated into a Bayesian context, where the a priori known nonstationary characteristics of ISR after the glucose stimulus are described by a stochastic model. Deconvolution is tackled by linear minimum variance estimation, thus allowing the derivation of new statistically based regularization criteria. Finally, a Monte-Carlo strategy is implemented to assess the uncertainty of the estimated ISR arising from CP measurement error and impulse response parameters uncertainty.

C-Peptide↗
PubMed1996

Reconstruction of insulin secretion rate by deconvolution: domain of validity of a monoexponential C-peptide impulse response model.

Insulin secretion rate (ISR) in vivo is reconstructed by deconvolution from plasma concentration of C-peptide (CP), a peptide with linear kinetics which is co-secreted with insulin but is not extracted by the liver. Deconvolution requires the knowledge of the CP impulse response. A two-exponential (2E) model is usually chosen to describe the CP impulse response but a one-exponential (1E) model is also used in the literature. The purpose here is to discuss the domain of validity of the 1E model in reconstructing the ISR by deconvolution. In particular, we show that the 1E model can be reliably used only if the ISR spectrum is concentrated in a narrow frequency band and a suitable input is designed for its identification.

Activity Cycles↗
PubMed1994

The subjective, behavioral and cognitive effects of subanesthetic concentrations of isoflurane and nitrous oxide in healthy volunteers.

A prospective, crossover, double-blind trial was conducted in nine healthy volunteers in which the subjective, psychomotor and memory effects of isoflurane (0.0, 0.3 and 0.6%) and nitrous oxide (N2O) (0, 20 and 40%) were examined. Dependent measures included visual analog scales and a standardized drug effects inventory (subjective effects), reaction time and eye-hand coordination (e.g., psychomotor performance), and immediate and delayed free recall (memory). There were some similarities in subjective effects between the two inhaled drugs (e.g., increased ratings of "drunk" and "spaced out"), but isoflurane had effects which N2O did not have. Isoflurane but not N2O increased visual analog scale ratings of "confused," "sedated," and "carefree," and decreased ratings of "in control of thoughts" and "in control of body." An odor was detected with isoflurane and it was disliked. Psychomotor performance was more grossly impaired during isoflurane inhalation than during N2O inhalation. Psychomotor recovery from both agents was rapid and complete so that 5 min after the inhalation period had ceased, performance had returned to baseline levels. Both isoflurane and nitrous oxide impaired immediate and delayed free recall. The feasibility of using isoflurane in conscious sedation procedures is discussed.

Adult↗
PubMed1989

Role of intraoperative ultrasound in the screening of liver metastases from colorectal carcinoma: initial experiences.

The aim of this study was to assess the utility of intraoperative ultrasound (IOUS) in the diagnosis and management of liver metastases from colorectal carcinoma. IOUS was performed on a consecutive series of 70 patients undergoing surgery for colorectal carcinoma, with follow-up ranging from 6 to 24 months. In ten cases (14.3%), 13 metastatic tumours were diagnosed; only six of these had been found by preoperative workup and/or surgical inspection. Seven (53.9%) small metastatic liver lesions were identified only by IOUS. None of the lesions diagnosed by IOUS was palpable, and they were all extremely small--ranging from 4 x 6 to 12 x 16 mm. Seventy-three locations were examined in order to compare the results of IOUS with those of other methods. The sensitivity of the former proved to be higher (P less than .05) than that of conventional pre- and intraoperative screening.

Carcinoma↗
PubMed1988

Carcinoma of the lung, stage III. Experience with the new TNM-AJCC classification.

The records of 228 patients who underwent surgery for primary lung cancer in 1970-1986 were reviewed. In 115 cases (94 men, 21 women) the disease was in stage III according to the 1978 classification of the American Joint Committee on Cancer (AJCC). These 115 cases were retrospectively reassessed, using a recently proposed new TNM classification with subdivision of stage III into IIIa, in which the patients may benefit from surgery, and IIIb, in which surgery is not advisable. Stage IIIa disease was present at operation in 87 cases and stage IIIb in 28. Actuarial analysis of survival rates showed that the new subclassification permits identification of those stage III patients who may benefit from surgical therapy.

Actuarial Analysis↗
PubMedDate not supplied

Impulse response model in reconstruction of insulin secretion by deconvolution: role of input design in the identification experiment.

Insulin secretion rate (ISR) in vivo can be reconstructed by deconvolution of plasma concentration of C-peptide (CP), a peptide co-secreted with insulin but not extracted by the liver and exhibiting linear kinetics. Deconvolution requires the knowledge of the CP impulse response. A two exponential model is usually chosen to describe the CP impulse response but three exponential and one exponential models have also been used. The purpose of this paper is to investigate the role of the CP impulse response model order in reconstructing ISR by deconvolution in three standard physiological/clinical situations: ultradian oscillations, rapid pulses, and biphasic response to a glucose stimulus. By resorting to simulation, we first show that, in each situation, the validity of impulse response models with different orders depends on the input chosen in the impulse response identification experiment. Real data are then used which support the simulation results.

Activity Cycles↗