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Results for “multimodal modeling”

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PubMed1999

[A network capable of reading the temporal codes in the olfactory discrimination of insects].

Recent work on the insect olfactory system has shown that its mushroom bodies (one of its major components) are involved in the fine discrimination of odours and that the temporal organisation of spike discharges plays a fundamental role. We propose here a model of a network that is able to decode the temporal patterns which characterise an odour. This model has three fundamental properties that seem to exist in all mushroom bodies of insects studied so far: a) long lasting inhibitions with rebounds, able to facilitate delayed spike generation; b) synaptic plasticity, which allows the network to learn to recognise temporal patterns; c) above all a large interconnection, which allows this network to recognise intervals of various duration. This model thus appears suited to identify combinations of temporal patterns in the dendrites of Kenyon cells (the principal cells in the calyces of the mushroom bodies). Moreover, the mushroom bodies integrate multimodal inputs, suggesting that the detection of temporal patterns may be extended to the detection of a complex environment, combining in particular olfactive and visual inputs.

Animal Structures↗

PubMed2005

Immunotherapy of murine malignant mesothelioma using tumor lysate-pulsed dendritic cells.

RATIONALE: Exploiting the immunostimulatory capacities of dendritic cells holds great promise for cancer immunotherapy. Currently, dendritic cell-based immunotherapy is evaluated clinically in a number of malignancies, including melanoma and urogenital and lung cancer, showing variable but promising results. OBJECTIVE: To evaluate if pulsed dendritic cells induce protective immunity against malignant mesothelioma in a mouse model. METHODS: Malignant mesothelioma was induced in mice by intraperitoneal injection of the AB1 mesothelioma cell line, leading to death within 28 days. For immunotherapy, dendritic cells were pulsed overnight either with AB1 tumor cell line lysate, AB1-derived exosomes, or ex vivo AB1 tumor lysate, and injected either before (Days -14 and -7) at the day of (Day 0) or after (Days +1 and +8) tumor implantation. MAIN RESULTS: Mice receiving tumor lysate-pulsed dendritic cells before tumor implantation demonstrated protective antitumor immunity with prolonged survival (> 3 months) and even resisted secondary tumor challenge. Tumor protection was associated with strong tumor-specific cytotoxic T-lymphocyte responses. Adoptive transfer of splenocytes or purified CD8+ T lymphocytes transferred tumor protection to unimmunized mice in vivo. When given after tumor implantation in a therapeutic setting, pulsed dendritic cells prevented mesothelioma outgrowth. With higher tumor load and delayed administration after tumor implantation, dendritic cells were no longer effective. CONCLUSIONS: We demonstrate in this murine model that immunotherapy using pulsed dendritic cells may emerge as a powerful tool to control mesothelioma outgrowth. In the future, immunotherapy using dendritic cells could be used as adjuvant to control local recurrence after multimodality treatment for malignant mesothelioma.

Animals↗

PubMed1988

Energy efficiency of different mechanistic models for potassium ion uptake in lower eukaryotic cells.

Different mechanistic models for potassium ion uptake are analyzed by an equilibrium-thermodynamic formalism in terms of their comparative efficiency in setting chemical potential differences of the potassium ion of different magnitudes across the plasma membrane of lower eukaryotic cells. The possible adaptive advantages for a multimode mechanism(s) operating in alternative modes depending on the physiological and/or environmental conditions of the cells are discussed.

Cells↗

PubMed1991

Aneuploidy and progression in promoted preneoplastic foci during chemical hepatocarcinogenesis in the rat.

Since a number of rat hepatocarcinomas are aneuploid, the model DNA content of enzyme-altered foci was determined cytospectrophotometrically, to assess if ploidy changes occur before cancer is established. Male F344 rats treated with diethylnitrosamine and promoted with a choline-deficient, phenobarbital supplemented diet showed in most enzyme-altered foci a multimodal ploidy distribution with diploid, tetraploid and octoploid peaks. A minority of foci, however, exhibited an aneuploid pattern. This change in ploidy reflects irreversible genomic alterations, indicative of tumor progression. Thus, promotion and progression may coexist simultaneously in this model of carcinogenesis, long before hepatomas can be diagnosed.

Aneuploidy↗

PubMed2005

Reference frames for representing visual and tactile locations in parietal cortex.

The ventral intraparietal area (VIP) receives converging inputs from visual, somatosensory, auditory and vestibular systems that use diverse reference frames to encode sensory information. A key issue is how VIP combines those inputs together. We mapped the visual and tactile receptive fields of multimodal VIP neurons in macaque monkeys trained to gaze at three different stationary targets. Tactile receptive fields were found to be encoded into a single somatotopic, or head-centered, reference frame, whereas visual receptive fields were widely distributed between eye- to head-centered coordinates. These findings are inconsistent with a remapping of all sensory modalities in a common frame of reference. Instead, they support an alternative model of multisensory integration based on multidirectional sensory predictions (such as predicting the location of a visual stimulus given where it is felt on the skin and vice versa). This approach can also explain related findings in other multimodal areas.

Animals↗

PubMed2006

Multimodal visualization interface for data management, self-learning and data presentation.

A multimodal visualization software, called the Data Manager (DM), has been developed to increase interdisciplinary communication around the topic of visualization and modeling of various aspects of the human anatomy. Numerous tools used in Radiology are integrated in the interface that runs on standard personal computers. The available tools, combined to hierarchical data management and custom layouts, allow analyzing of medical imaging data using advanced features outside radiological premises (for example, for patient review, conference presentation or tutorial preparation). The system is free, and based on an open-source software development architecture, and therefore updates of the system for custom applications are possible.

Anatomy↗

PubMed1994

Integrating human brain maps.

Perception, action, cognition, and emotion can now be mapped in the brain by a growing family of techniques. Positron emission tomography, functional magnetic resonance imaging, event-related electrical potentials, event-related magnetic fields, and other non-invasive imaging techniques are rapidly evolving and providing an increasingly rich literature on the functional organization of the human brain. Although no two techniques map identical physiological processes or physical parameters, replications of functionally specific maps by different techniques indicate sufficient common ground for multimodality integration. The process of integration is multi-tiered. Recent advances in integration range from simple image fusion, to model-based synthetic analyses, to collective databases for neural-system modeling. Spatially, temporally, physiologically, and cognitively accurate computational models of the neural systems of human behavior are the ultimate objective of functional brain mapping. This objective will be reached only through integrating the diversity of modern brain-mapping methods.

Brain Mapping↗

PubMed2006

Feasibility of a novel deformable image registration technique to facilitate classification, targeting, and monitoring of tumor and normal tissue.

PURPOSE: To investigate the feasibility of a biomechanical-based deformable image registration technique for the integration of multimodality imaging, image guided treatment, and response monitoring. METHODS AND MATERIALS: A multiorgan deformable image registration technique based on finite element modeling (FEM) and surface projection alignment of selected regions of interest with biomechanical material and interface models has been developed. FEM also provides an inherent method for direct tracking specified regions through treatment and follow-up. RESULTS: The technique was demonstrated on 5 liver cancer patients. Differences of up to 1 cm of motion were seen between the diaphragm and the tumor center of mass after deformable image registration of exhale and inhale CT scans. Spatial differences of 5 mm or more were observed for up to 86% of the surface of the defined tumor after deformable image registration of the computed tomography (CT) and magnetic resonance images. Up to 6.8 mm of motion was observed for the tumor after deformable image registration of the CT and cone-beam CT scan after rigid registration of the liver. Deformable registration of the CT to the follow-up CT allowed a more accurate assessment of tumor response. CONCLUSIONS: This biomechanical-based deformable image registration technique incorporates classification, targeting, and monitoring of tumor and normal tissue using one methodology.

Biomechanical Phenomena↗

PubMed2002

Sensory inputs stimulate progenitor cell proliferation in an adult insect brain.

Although most brain neurons are produced during embryonic and early postnatal development, recent studies clearly demonstrated in a wide range of species from invertebrates to humans that new neurons are added to specific brain structures throughout adult life. Hormones, neurotransmitters, and growth factors as well as environmental conditions modulate this neurogenesis. In this study, we address the role of sensory inputs in the regulation of adult neural progenitor cell proliferation in an insect model. In some insect species, adult neurogenesis occurs in the mushroom bodies, the main sensory integrative centers of the brain, receiving multimodal information and often considered as the analog of the vertebrate hippocampus. We recently showed that rearing adult crickets in enriched sensory and social conditions enhanced neuroblast proliferation in the mushroom bodies. Here, by manipulating hormonal levels and affecting olfactory and/or visual inputs, we show that environmental regulation of neurogenesis is in direct response to olfactory and visual stimuli rather than being mediated via hormonal control. Experiments of unilateral sensory deprivation reveal that neuroblast proliferation can be inhibited in one brain hemisphere only. These results, obtained in a relatively simple brain, emphasize the role of sensory inputs on stem cell division.

Animals↗

PubMed2003

Neurological disorders and the structure of human consciousness.

Recent studies that identify distinct neural correlates of perceptual awareness offer a promising step towards improved understanding of the neurological underpinnings of conscious experience. Such studies indicate that perceptual awareness is modular in nature, with neural correlates of awareness consisting of the specialized structures involved in perceptual processing. However, the integrative, multimodal nature of conscious experience appears to require a functional architecture that overcomes this modular segregation of function. We propose a model in which experience emerges from the dynamic interactions of specialized component processes via a distributed neural network. Such a model offers a mechanism to explain several empirical observations of the neural correlates of perceptual awareness, cognitive function, and symptoms of neurological damage.

Journal Article↗

PubMed2003

Initial three-dimensional finite-difference time-domain phenomenology study of the transient response of a large vertically coupled photonic racetrack.

We report the initial three-dimensional finite-difference time-domain modeling of a vertically coupled photonic racetrack. The modeling reveals details of the full suite of space-time behavior of electromagnetic-wave phenomena involved in guiding, coupling, multimoding, dispersion, and radiation. This behavior is not easily obtainable by analytical or full-vector frequency-domain methods, measurements of terminal properties, or near-field scanning optical microscopy.

Journal Article↗

PubMed2006

Precise segmentation of multimodal images.

We propose new techniques for unsupervised segmentation of multimodal grayscale images such that each region-of-interest relates to a single dominant mode of the empirical marginal probability distribution of grey levels. We follow the most conventional approaches in that initial images and desired maps of regions are described by a joint Markov-Gibbs random field (MGRF) model of independent image signals and interdependent region labels. However, our focus is on more accurate model identification. To better specify region borders, each empirical distribution of image signals is precisely approximated by a linear combination of Gaussians (LCG) with positive and negative components. We modify an expectation-maximization (EM) algorithm to deal with the LCGs and also propose a novel EM-based sequential technique to get a close initial LCG approximation with which the modified EM algorithm should start. The proposed technique identifies individual LCG models in a mixed empirical distribution, including the number of positive and negative Gaussians. Initial segmentation based on the LCG models is then iteratively refined by using the MGRF with analytically estimated potentials. The convergence of the overall segmentation algorithm at each stage is discussed. Experiments show that the developed techniques segment different types of complex multimodal medical images more accurately than other known algorithms.

Algorithms↗

PubMed2006

Heterarchical reinforcement-learning model for integration of multiple cortico-striatal loops: fMRI examination in stimulus-action-reward association learning.

The brain's most difficult computation in decision-making learning is searching for essential information related to rewards among vast multimodal inputs and then integrating it into beneficial behaviors. Contextual cues consisting of limbic, cognitive, visual, auditory, somatosensory, and motor signals need to be associated with both rewards and actions by utilizing an internal representation such as reward prediction and reward prediction error. Previous studies have suggested that a suitable brain structure for such integration is the neural circuitry associated with multiple cortico-striatal loops. However, computational exploration still remains into how the information in and around these multiple closed loops can be shared and transferred. Here, we propose a "heterarchical reinforcement learning" model, where reward prediction made by more limbic and cognitive loops is propagated to motor loops by spiral projections between the striatum and substantia nigra, assisted by cortical projections to the pedunculopontine tegmental nucleus, which sends excitatory input to the substantia nigra. The model makes several fMRI-testable predictions of brain activity during stimulus-action-reward association learning. The caudate nucleus and the cognitive cortical areas are correlated with reward prediction error, while the putamen and motor-related areas are correlated with stimulus-action-dependent reward prediction. Furthermore, a heterogeneous activity pattern within the striatum is predicted depending on learning difficulty, i.e., the anterior medial caudate nucleus will be correlated more with reward prediction error when learning becomes difficult, while the posterior putamen will be correlated more with stimulus-action-dependent reward prediction in easy learning. Our fMRI results revealed that different cortico-striatal loops are operating, as suggested by the proposed model.

Association Learning↗

PubMed2000

Radiation physics and genetic targeting: new directions for radiotherapy. The Douglas Lea Lecture 1999.

Radiation as a cancer treatment modality is of high physical precision but limited biological specificity. Targeted radiotherapy, the delivery of radiation to cancer cells by radioisotopes conjugated to tumour-seeking targeting agents, is a biologically attractive option but is currently effective for just a few tumour types (neuroblastoma, lymphoma) for which efficacious targeting agents are available. Radiobiological modelling and radiation microdosimetry have provided useful guidelines in choosing treatment strategies for targeted radiotherapy. These considerations generally favour the incorporation of targeted radiotherapy as one component of a multimodal treatment regimen. Very recently, gene therapy techniques have been developed which should enhance the clinical efficacy of both external beam radiation and targeted radiotherapy. Typically, non-harmful viruses are modified to incorporate therapeutic genes which cause altered cellular radiosensitivity or which facilitate the cellular uptake of targeting agents. To achieve specificity, therapeutic genes would be co-transfected with tissue-specific promoter genes causing the therapeutic genes to be expressed in cells of particular types. In laboratory models, our research group are exploring the transfection-mediated uptake of the targeting agents MIBG and sodium iodide. These approaches do not require transfection of every cell in order to cure a tumour-cells which have escaped transfection may be sterilized by radiation cross-fire from transfected neighbours. A new task for radiation microdosimetry is to quantify the cross-fire effect and to compute the efficacies of gene transfection which will be required for tumour cure. In the spirit of Douglas Lea, the analytic approach of physics can be used to illuminate and enhance developments in genetics, to the benefit of medicine.

3-Iodobenzylguanidine↗

PubMed2004

Geometrical accuracy and fusion of multimodal vascular images: a phantom study.

The aim of this work was to compare the geometrical accuracy of x-ray angiography, magnetic resonance imaging (MRI), x-ray computed tomography (XCT), and ultrasound imaging (B-mode and IVUS, or intravascular ultrasound) for measuring the lumen diameters of blood vessels. An image fusion method was also developed to improve these measurements. The images were acquired from a phantom that mimic vessels of known diameters. After acquisition, the multimodal images were coregistered by manual alignment of fiducial markers, and then by maximization of mutual information. The fusion method was performed by means of a fuzzy logic modeling approach followed by a combination process based on a possibilistic theory. The results showed (i) the better geometrical accuracy of XCT and IVUS compared to the other modalities, and (ii) the better accuracy and smaller variability of fused images compared to single modalities, with respect to most diameters investigated. For XCT, the error varied from 0.4% to 5.4%, depending on the vessel diameter that ranged from 0.93 to 6.24 mm. For IVUS, the error ranged from -0.3% to 1.7% but the smallest vessel (0.93 mm) could not be investigated because of the probe size. Compared to others fusion schemes, the XCT-MRI fused images provided the best results for both accuracy (from -1.6% to 0.2% for the three largest vessels) and robustness (mean relative error of 1.9%). To conclude, this work underlined both the usefulness of the multimodality vascular phantom as a validation tool and the utility of image fusion in the vascular context.

Angiography↗

PubMed2006

Parametric and nonparametric population methods: their comparative performance in analysing a clinical dataset and two Monte Carlo simulation studies.

BACKGROUND AND OBJECTIVES: This study examined parametric and nonparametric population modelling methods in three different analyses. The first analysis was of a real, although small, clinical dataset from 17 patients receiving intramuscular amikacin. The second analysis was of a Monte Carlo simulation study in which the populations ranged from 25 to 800 subjects, the model parameter distributions were Gaussian and all the simulated parameter values of the subjects were exactly known prior to the analysis. The third analysis was again of a Monte Carlo study in which the exactly known population sample consisted of a unimodal Gaussian distribution for the apparent volume of distribution (V(d)), but a bimodal distribution for the elimination rate constant (k(e)), simulating rapid and slow eliminators of a drug. METHODS: For the clinical dataset, the parametric iterative two-stage Bayesian (IT2B) approach, with the first-order conditional estimation (FOCE) approximation calculation of the conditional likelihoods, was used together with the nonparametric expectation-maximisation (NPEM) and nonparametric adaptive grid (NPAG) approaches, both of which use exact computations of the likelihood. For the first Monte Carlo simulation study, these programs were also used. A one-compartment model with unimodal Gaussian parameters V(d) and k(e) was employed, with a simulated intravenous bolus dose and two simulated serum concentrations per subject. In addition, a newer parametric expectation-maximisation (PEM) program with a Faure low discrepancy computation of the conditional likelihoods, as well as nonlinear mixed-effects modelling software (NONMEM), both the first-order (FO) and the FOCE versions, were used. For the second Monte Carlo study, a one-compartment model with an intravenous bolus dose was again used, with five simulated serum samples obtained from early to late after dosing. A unimodal distribution for V(d) and a bimodal distribution for k(e) were chosen to simulate two subpopulations of 'fast' and 'slow' metabolisers of a drug. NPEM results were compared with that of a unimodal parametric joint density having the true population parameter means and covariance. RESULTS: For the clinical dataset, the interindividual parameter percent coefficients of variation (CV%) were smallest with IT2B, suggesting less diversity in the population parameter distributions. However, the exact likelihood of the results was also smaller with IT2B, and was 14 logs greater with NPEM and NPAG, both of which found a greater and more likely diversity in the population studied. For the first Monte Carlo dataset, NPAG and PEM, both using accurate likelihood computations, showed statistical consistency. Consistency means that the more subjects studied, the closer the estimated parameter values approach the true values. NONMEM FOCE and NONMEM FO, as well as the IT2B FOCE methods, do not have this guarantee. Results obtained by IT2B FOCE, for example, often strayed visibly away from the true values as more subjects were studied. Furthermore, with respect to statistical efficiency (precision of parameter estimates), NPAG and PEM had good efficiency and precise parameter estimates, while precision suffered with NONMEM FOCE and IT2B FOCE, and severely so with NONMEM FO. For the second Monte Carlo dataset, NPEM closely approximated the true bimodal population joint density, while an exact parametric representation of an assumed joint unimodal density having the true population means, standard deviations and correlation gave a totally different picture. CONCLUSIONS: The smaller population interindividual CV% estimates with IT2B on the clinical dataset are probably the result of assuming Gaussian parameter distributions and/or of using the FOCE approximation. NPEM and NPAG, having no constraints on the shape of the population parameter distributions, and which compute the likelihood exactly and estimate parameter values with greater precision, detected the more likely greater diversity in the parameter values in the population studied. In the first Monte Carlo study, NPAG and PEM had more precise parameter estimates than either IT2B FOCE or NONMEM FOCE, as well as much more precise estimates than NONMEM FO. In the second Monte Carlo study, NPEM easily detected the bimodal parameter distribution at this initial step without requiring any further information. Population modelling methods using exact or accurate computations have more precise parameter estimation, better stochastic convergence properties and are, very importantly, statistically consistent. Nonparametric methods are better than parametric methods at analysing populations having unanticipated non-Gaussian or multimodal parameter distributions.

Aged↗

PubMed1997

Analysis of phosphorescence in heterogeneous systems using distributions of quencher concentration.

A continuous distribution approach, instead of the traditional mono- and multiexponential analysis, for determining quencher concentration in a heterogeneous system has been developed. A mathematical model of phosphorescence decay inside a volume with homogeneous concentration of phosphor and heterogeneous concentration of quencher was formulated to obtain pulse-response fitting functions for four different distributions of quencher concentration: rectangular, normal (Gaussian), gamma, and multimodal. The analysis was applied to parameter estimates of a heterogeneous distribution of oxygen tension (PO2) within a volume. Simulated phosphorescence decay data were randomly generated for different distributions and heterogeneity of PO2 inside the excitation/emission volume, consisting of 200 domains, and then fit with equations developed for the four models. Analysis using a monoexponential fit yielded a systematic error (underestimate) in mean PO2 that increased with the degree of heterogeneity. The fitting procedures based on the continuous distribution approach returned more accurate values for parameters of the generated PO2 distribution than did the monoexponential fit. The parameters of the fit (M = mean; sigma = standard deviation) were investigated as a function of signal-to-noise ratio (SNR = maximum signal amplitude/peak-to-peak noise). The best-fit parameter values were stable when SNR > or = 20. All four fitting models returned accurate values of M and sigma for different PO2 distributions. The ability of our procedures to resolve two different heterogeneous compartments was also demonstrated using a bimodal fitting model. An approximate scheme was formulated to allow calculation of the first moments of a spatial distribution of quencher without specifying the distribution. In addition, a procedure for the recovery of a histogram, representing the quencher concentration distribution, was developed and successfully tested.

Light↗

PubMed2002

Dimensional structure of the Yale-Brown Obsessive-Compulsive Scale (Y-BOCS).

The Yale-Brown Obsessive-Compulsive Scale (Y-BOCS) is a widely used instrument to assess obsessive-compulsive symptomatology. The present study provides evidence that the Y-BOCS is best represented by a three-dimensional model comprising severity of obsessions (factor 1), severity of compulsions (factor 2) and resistance to symptoms (factor 3). On the basis of exploratory factor analysis, this structure was found for both baseline (n = 109) and discharge ratings (n = 68) following a multimodal cognitive-behavioral intervention. The factor solution remained essentially unchanged when two optional items (items 1b and 6b) were dropped from analysis. The three-factor structure was replicated with confirmatory factor analysis and showed better fit than previously proposed single- and two-factor models. For future research, we propose a new Y-BOCS scoring algorithm that takes this factor structure into account. A further result was that resistance significantly declined in response to cognitive-behavioral intervention, whereas drug treatment alone did not seem to moderate this variable according to previous research conducted by Kim et al. [Psychiatry Research 51 (1994) 203-211].

Adult↗