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PubMed2007

Multimodal pattern formation in phenotype distributions of sexual populations.

During bouts of evolutionary diversification, such as adaptive radiations, the emerging species cluster around different locations in phenotype space. How such multimodal patterns in phenotype space can emerge from a single ancestral species is a fundamental question in biology. Frequency-dependent competition is one potential mechanism for such pattern formation, as has previously been shown in models based on the theory of adaptive dynamics. Here, we demonstrate that also in models similar to those used in quantitative genetics, phenotype distributions can split into multiple modes under the force of frequency-dependent competition. In sexual populations, this requires assortative mating, and we show that the multimodal splitting of initially unimodal distributions occurs over a range of assortment parameters. In addition, assortative mating can be favoured evolutionarily even if it incurs costs, because it provides a means of alleviating the effects of frequency dependence. Our results reveal that models at both ends of the spectrum between essentially monomorphic (adaptive dynamics) and fully polymorphic (quantitative genetics) yield similar results. This underscores that frequency-dependent selection is a strong agent of pattern formation in phenotype distributions, potentially resulting in adaptive speciation.

Animals↗

PubMed2025

Alzheimer's subtypes A supervised, unsupervised, multimodal, multilayered embedded recursive (SUMMER) AI study.

Since Alzheimer's disease (AD) is a heterogeneous disease, different subtypes may have distinct biological, genetic, and clinical characteristics, requiring tailored interventions. While several proposed subtypes of AD exist, there is still no clear consensus on a definitive classification. By leveraging complementary AI approaches, including supervised and unsupervised learning, within a recursive pipeline (SUMMER) that integrates multimodal datasets encompassing MRI measurements, phenotypes, and genetic data, our goal was to generate robust scientific evidence for identifying AD subtypes. Data was downloaded from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database and included neuroimaging data (MRI), genetics (SNPs), clinical diagnosis, and demographics. 1133 European American participants' images, aged 55-95, were included in this study. The analysis was multi-fold, where the first step involved applying an unsupervised application to a subset of the MRI sample (AD + cognitively normal (CN) aged matched groups, 100 men aged 68-85 years, and 76 women aged 68-85 years). The MRI brain gray matter was segmented into 44 regions of interest (ROIs) according to a standard atlas, and 618 features were extracted, including ROI voxel intensity measurements such as minimum, maximum, and histogram variables. Results identified a cluster of subtype AD men and a cluster of subtype AD women that were distinct from the rest of their respective samples. In the next step, the integrity of the identified subtype AD clusters was investigated using the XGBoost supervised machine learning application with genetic features (SNPs, N=36,724) and labels: the identified subtype AD cluster vs. the rest of the sample, stratified by sex. A significant AD subtype men model (accuracy=0.85, F1=0.72, AUC=0.83) and a significant women AD subtype model (accuracy=0.81, F1=0.81, AUC=0.81) were built, confirming the homogeneity of the isolated AD subtype clusters. Discriminative biomarkers were extracted from the significant models, including selected ROIs and SNPs. Finally, the subtype models were tested on an unseen subset of ADNI data. The genetic-based models identified clusters of AD subtype participants consisting of 34% of the men AD group and 47% of the women AD group. Phenotypic analysis indicates that lower body weight was associated with the women's AD subtype. Complex diseases like AD demand a sophisticated, multimodal approach for precise diagnosis. Effectively identifying disease subtypes enhances the potential for personalized treatment, ultimately improving patient outcomes.

Journal Article↗

PubMed2026

Unifying multimodal single-cell data with a mixture-of-experts β-variational autoencoder framework.

Multimodal single-cell assays profile complementary layers of cell state, but integration is complicated by modality mismatch, sparsity, and uneven cohort coverage. Here, we present Unified Variational Inference (UniVI), a scalable mixture-of-experts β-variational autoencoder that learns a shared latent space while preserving modality-specific structure. UniVI couples modality-specific encoders/decoders with a shared latent prior and a symmetric cross-modal alignment objective, enabling consistent integration of paired measurements without curated feature-link graphs or preannotated reference atlases; optional supervised heads can be added when labels are available. Across paired RNA-protein (CITE-seq) and RNA-chromatin (10x Genomics Multiome, SHARE-seq) data spanning human PBMCs and mouse back skin-a nonhematopoietic tissue with continuous differentiation hierarchies-UniVI produces coherent embeddings, improves label transfer, and enables cross-modal reconstruction and denoising. Extending to trimodal measurements, UniVI maintains robust three-way alignment among RNA, chromatin accessibility, and surface proteins (TEA-seq), and accommodates DNA methylation in a paired scNMT-seq mouse gastrulation proof-of-concept under beta-binomial likelihoods. Performance degrades gracefully under severe cell type imbalance and in the presence of modality-exclusive populations. In an acute myeloid leukemia mosaic design, a paired RNA-protein bridge anchors independent RNA-only and protein+genotype cohorts, revealing genotype-associated neighborhoods that sharpen with mutation-aware fine-tuning. UniVI thus provides a flexible, interpretable framework for multimodal integration across paired, trimodal, and mosaic study designs and supports practical reference-to-query projection in partially observed studies.

Journal Article↗

PubMed1999

Wakefield excitation in multimode structures by a train of electron bunches.

We discuss wakefield excitation and propagation in dielectric structures, particularly concentrating on the case of multiple drive beam excitation in multimoded structures. We emphasize calculations of the energy loss of the drive beam train, the amplitude of the wakefield, and the relationship between power flow and stored energy in the dielectric wakefield device. We show that for a collinear multimode structure the amplitude of the wakefield generated by a bunch train is less than or equal to the wakefield generated by a single bunch of the same total charge. Furthermore, the transformer ratio R is shown to be always less than 2, even in the multiple drive beam case.

Journal Article↗

PubMed2005

Multimode lasing in two-dimensional fully chaotic cavity lasers.

Multimode lasing in a fully chaotic cavity is investigated numerically by using a nonlinear dynamics model. We report a transition process from single-mode lasing to multimode lasing and reveal interactions among the lasing modes. In particular, both mode-pulling and mode-pushing interactions are shown to decrease the number of effective lasing modes. In addition, coexistence of different types of attractors of the final lasing states is numerically confirmed.

Journal Article↗

PubMed2005

Bona fide stochastic resonance and multimodality in the stochastic Hodgkin-Huxley neuron.

The phenomena of stochastic resonance (SR) has attracted much attention in the studies of the excitable systems, in particular, the nervous systems under noise. Recently, an alternative SR condition, called the bona fide SR, was proposed for the bistable system under noise, based on the notion of the residence time distribution. As the forcing frequency increases, there exists an optimal resonant frequency. We study the SR in a stochastic Hodgkin-Huxley neuron, which has an inherent natural frequency in addition to the stochastic time scale. We have observed two resonant conditions; one between periodic forcing and natural frequencies, and the other between the periodic forcing and the stochastic frequencies. These resonance conditions show the bona fide stochastic resonance with multimodality. For comparison, we have studied the bona fide SR in the stochastic FitzHugh-Nagumo neuron, where, the multimodality is not observed. The differences in the resonance structure of two neuron models are understood in terms of differences in the phase portraits.

Action Potentials↗

PubMed2000

Low frequency fluctuations in a multimode semiconductor laser with optical feedback.

We study a multimode semiconductor laser subject to a moderate optical feedback. The steady state is destabilized by either a simple Hopf bifurcation leading to in phase dynamics or by a degenerate Hopf bifurcation leading to antiphase dynamics. The degenerate bifurcation is also a source of multiple coexisting attractors. We show that a simple interpretation of the low frequency fluctuations in the multimode regime is provided by a chaotic itinerancy among the many coexisting unstable attractors produced by the degenerate Hopf bifurcation.

Journal Article↗

PubMed2006

Multimode uncertainty relations and separability of continuous variable states.

A multimode uncertainty relation (generalizing the Robertson-Schrödinger relation) is derived as a necessary constraint on the second moments of n pairs of canonical operators. In turn, necessary conditions for the separability of multimode continuous variable states under (m+n)-mode bipartitions are derived from the uncertainty relation. These conditions are proven to be necessary and sufficient for (1+n)-mode Gaussian states and for (m+n)-mode bisymmetric Gaussian states.

Journal Article↗

PubMed1999

A multimodal registration algorithm of eye fundus images using vessels detection and Hough transform.

Image registration is a real challenge because physicians handle many images. Temporal registration is necessary in order to follow the various steps of a disease, whereas multimodal registration allows us to improve the identification of some lesions or to compare pieces of information gathered from different sources. This paper presents an algorithm for temporal and/or multimodal registration of retinal images based on point correspondence. As an example, the algorithm has been applied to the registration of fluorescein images (obtained after a fluorescein dye injection) with green images (green filter of a color image). The vascular tree is first detected in each type of images and bifurcation points are labeled with surrounding vessel orientations. An angle-based invariant is then computed in order to give a probability for two points to match. Then a Bayesian Hough transform is used to sort the transformations with their respective likelihoods. A precise affine estimate is finally computed for most likely transformations. The best transformation is chosen for registration.

Algorithms↗

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↗

PubMed2004

Phantom-based multimodal interactions for medical education and training: the Munich Knee Joint Simulator.

Simulation environments based on virtual reality technologies can support medical education and training. In this paper, the novel approach of an "interactive phantom" is presented that allows a realistic display of haptic contact information typically generated when touching and moving human organs or segments. The key idea of the haptic interface is to attach passive phantom objects to a mechanical actuator. The phantoms look and feel as real anatomical objects. Additional visualization of internal anatomical and physiological information and sound generated during the interaction with the phantom yield a multimodal approach that can increase performance, didactic value, and immersion into the virtual environment. Compared to classical approaches, this multimodal display is convenient to use, provides realistic tactile properties, and can be partly adjusted to different, e.g., pathological properties. The interactive phantom is exemplified by a virtual human knee joint that can support orthopedic education, especially for the training of clinical knee joint evaluation. It is suggested that the technical principle can be transferred to many other fields of medical education and training such as obstetrics and dentistry.

Computer Graphics↗

PubMed2004

Multimodal and ubiquitous computing systems: supporting independent-living older users.

We document the rationale and design of a multimodal interface to a pervasive/ubiquitous computing system that supports independent living by older people in their own homes. The Millennium Home system involves fitting a resident's home with sensors--these sensors can be used to trigger sequences of interaction with the resident to warn them about dangerous events, or to check if they need external help. We draw lessons from the design process and conclude the paper with implications for the design of multimodal interfaces to ubiquitous systems developed for the elderly and in healthcare, as well as for more general ubiquitous computing applications.

Activities of Daily Living↗

PubMed2004

Multimodal registration of retinal images using self organizing maps.

In this paper, an automatic method for registering multimodal retinal images is presented. The method consists of three steps: the vessel centerline detection and extraction of bifurcation points only in the reference image, the automatic correspondence of bifurcation points in the two images using a novel implementation of the self organizing maps and the extraction of the parameters of the affine transform using the previously obtained correspondences. The proposed registration algorithm was tested on 24 multimodal retinal pairs and the obtained results show an advantageous performance in terms of accuracy with respect to the manual registration.

Algorithms↗

PubMed2005

Augmented virtuality based on stereoscopic reconstruction in multimodal image-guided neurosurgery: methods and performance evaluation.

Displaying anatomical and physiological information derived from preoperative medical images in the operating room is critical in image-guided neurosurgery. This paper presents a new approach referred to as augmented virtuality (AV) for displaying intraoperative views of the operative field over three-dimensional (3-D) multimodal preoperative images onto an external screen during surgery. A calibrated stereovision system was set up between the surgical microscope and the binocular tubes. Three-dimensional surface meshes of the operative field were then generated using stereopsis. These reconstructed 3-D surface meshes were directly displayed without any additional geometrical transform over preoperative images of the patient in the physical space. Performance evaluation was achieved using a physical skull phantom. Accuracy of the reconstruction method itself was shown to be within 1 mm (median: 0.76 mm +/- 0.27), whereas accuracy of the overall approach was shown to be within 3 mm (median: 2.29 mm +/- 0.59), including the image-to-physical space registration error. We report the results of six surgical cases where AV was used in conjunction with augmented reality. AV not only enabled vision beyond the cortical surface but also gave an overview of the surgical area. This approach facilitated understanding of the spatial relationship between the operative field and the preoperative multimodal 3-D images of the patient.

Algorithms↗

PubMed2004

On a multimode test sequencing problem.

Test sequencing is a binary identification problem wherein one needs to develop a minimal expected cost test procedure to determine which one of a finite number of possible failure states, if any, is present. In this paper, we consider a multimode test sequencing (MMTS) problem, in which tests are distributed among multiple modes and additional transition costs will be incurred if a test sequence involves mode changes. The multimode test sequencing problem can be solved optimally via dynamic programming or AND/OR graph search methods. However, for large systems, the associated computation with dynamic programming or AND/OR graph search methods is substantial due to the rapidly increasing number of OR nodes (denoting ambiguity states and current modes) and AND nodes (denoting next modes and tests) in the search graph. In order to overcome the computational explosion, we propose to apply three heuristic algorithms based on information gain: information gain heuristic (IG), mode capability evaluation (MC), and mode capability evaluation with limited exploration of depth and degree of mode Isolation (MCLEI). We also propose to apply rollout strategies, which are guaranteed to improve the performance of heuristics, as long as the heuristics are sequentially improving. We show computational results, which suggest that the information-heuristic based rollout policies are significantly better than traditional information gain heuristic. We also show that among the three information heuristics proposed, MCLEI achieves the best tradeoff between optimality and computational complexity.

Algorithms↗

PubMedDate not supplied

A study of multimodal motherese: the role of temporal synchrony between verbal labels and gestures.

This study examined European American and Hispanic American mothers' multimodal communication to their infants (N = 24). The infants were from three age groups representing three levels of lexical-mapping development: prelexical (5 to 8 months), early-lexical (9 to 17 months), and advanced-lexical (21 to 30 months). Mothers taught their infants four target (novel) words by using distinct objects during a semistructured play episode. Recent research suggests that young infants rely on temporal synchrony to learn syllable-object relations, but later, the role of synchrony diminishes. Thus, mothers' target and nontarget naming were coded for synchrony and other communication styles. The results indicated that mothers used target words more often than nontarget words in synchrony with object motion and sometimes touch. Thus, "multimodal motherese" likely highlights target word-referent relations for infants. Further, mothers tailored their communication to infants' level of lexical-mapping development. Mothers of prelexical infants used target words in synchrony with object motion more often than mothers of early- and advanced-lexical infants. Mothers' decreasing use of synchrony across age parallels infants' decreasing reliance on synchrony, suggesting a dynamical and reciprocal environment-organismic relation.

Adult↗

PubMed2026

Multimodal Therapy With Metformin, Inositol and Dietary Restriction Improves Insulin Resistance and Endocrine Outcomes in Women With Polyendocrine Metabolic Ovarian Syndrome: A Randomized Controlled Trial.

INTRODUCTION: Polyendocrine metabolic ovarian syndrome (PMOS), formerly known as polycystic ovary syndrome (PCOS), is a common endocrine-metabolic disorder characterized by insulin resistance, hyperandrogenism and ovulatory dysfunction. Metformin, inositol supplementation and lifestyle modification are widely used treatments, but direct comparative evidence remains limited. Multimodal therapy combining metformin, inositol and dietary restriction produces greater metabolic and reproductive improvement than single-modality interventions. METHODS: We conducted a 12-week randomized controlled trial in 192 women aged 18-35 years diagnosed with PMOS according to Rotterdam criteria. Participants were allocated to metformin (1500-2000 mg/day), inositol (myo-inositol 2 g plus d-chiro-inositol 50 mg twice daily), calorie-restricted diet (1200-1500 kcal/day), or combination therapy. Primary outcomes included changes in body mass index (BMI) and insulin resistance assessed by HOMA-IR. Secondary outcomes included testosterone, LH/FSH ratio and menstrual regularity. Analysis was performed using analysis of covariance (ANCOVA), with post-intervention values as dependent variables and corresponding baseline values as covariates. Categorical outcomes were compared using the Chi-square test. RESULTS: All interventions improved metabolic and endocrine parameters. Combination therapy resulted in the greatest reduction in HOMA-IR (- 2.64, 95% CI - 2.82 to -2.46, p < 0.001) and BMI (- 2.8 kg/m2, 95% CI - 3.05 to -2.55, p < 0.001). Menstrual cyclicity improved across all groups, with the highest proportion of participants reporting cycle regularisation in the combination therapy group (85.4%), compared with dietary restriction (72.9%), inositol (64.6%), and metformin (39.6%) (p < 0.001). Given the short follow-up duration, these findings reflect early improvements rather than sustained normalisation. CONCLUSION: Multimodal therapy was associated with superior metabolic and reproductive outcomes compared with single-modality interventions in women with PMOS. CLINICAL TRIAL REGISTRATION: ClinicalTrials. gov (NCT07380841).

Humans↗

PubMed1994

Treating the sexually abused child: a recursive, multimodal program.

This article describes a recursive, multimodal therapy approach for children who have been sexually abused by members of their family. The different therapeutic modalities (family, group, and individual) are conceived of as different "communities" that provide a variety of relationships, information, and perspectives on the incest experience. The child's involvement in these different communities allows her or him to develop a multiplicity of self-accounts. Meaning is further expanded through the recursive transfer of material across modalities. By determining the content that is discussed in any particular session, and by participating actively in decisions about transferring material across modalities, the child both develops an enhanced sense of personal agency and a connection to trustworthy family members. This approach is designed to allow each child's unique experience with incest to emerge. Clinical examples are provided, along with a description of the program that provides the setting for our multimodal approach to incest.

Adult↗