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At least 433 records · Page 24Linked to original sources
PubMed2003

Emergence of neural integration in the head-direction system by visual supervision.

Head-direction (HD) cells in subcortical areas of the mammalian brain are tuned to a particular head direction in space; a population of such neurons forms a neural compass that may be relevant for spatial navigation. The development of neural circuits constituting the head-direction system is poorly understood. Inspired by electrophysiological experiments about the role of recurrent synaptic connections, we investigate a learning rule that teaches neurons to amplify feed-forward inputs. We simulate random head movements of a rat, during which neurons receive both visual and vestibular (head-velocity) inputs. Remarkably, as recurrent connections learn to amplify exclusively the visual inputs, a neural network emerges that performs spatio-temporal integration. That is, during head movements in darkness, neurons resemble HD cells by maintaining a fixed tuning to head direction. The proposed learning rule exhibits similarities with known forms of anti-Hebbian synaptic plasticity. We conclude that selective amplification could serve as a general principle for the synaptic development of multimodal feedback circuits in the brain.

Algorithms↗
PubMed2003

Diagnosis and classification of eating disorders in adults with intellectual disability: the Diagnostic Criteria for Psychiatric Disorders for Use with Adults with Learning Disabilities/Mental Retardation (DC-LD) approach.

BACKGROUND: Previous classifications of eating disorders [EDs] employed a narrower concept of EDs. They did not include the wide range of abnormal eating behaviours [AEBs], persistent feeding disorders and EDs psychopathology, aetiological and comorbidity factors seen in adults with intellectual disability [ID]. METHODS: The International Classification of Diseases--10 [ICD-10], ICD-10-MR, Diagnostic and Statistical Manual--IV [DSM-IV] and Diagnostic Criteria for Psychiatric Disorders for Use with Adults with Learning Disabilities/Mental Retardation[DC-LD] diagnostic approaches to EDs in adults with ID are compared. RESULTS: The DC-LD encourages conceptually clearer and systematic hierarchical differential diagnostic classification of AEBs and EDs. The DC-LD also allows consideration of relevant aetiological and comorbidity issues. DC-LD-based multi-axial case formulation supports the multimodal clinical assessment of AEBs and EDs. CONCLUSIONS: Further research should develop similar systematic and evidence-based multicomponent clinical diagnostic, management and service models for adults with ID and EDs.

Diagnosis, Differential↗
PubMed1994

Artificial neural networks and simulated molecular evolution are potential tools for sequence-oriented protein design.

The potential of artificial neural filter systems for feature extraction from amino acid sequences is discussed. Analysis of signal peptidase I cleavage-sites in protein precursor sequences serves as an example application. Trained neural networks can be used as the fitness function in an evolutionary protein design cycle termed 'simulated molecular evolution' which is an entirely computer-based method for the rational design of locally encoded amino acid sequence features. The design procedure itself is regarded as an optimization process which can follow several schemes. Gradient search, diffusive search, and evolution strategy have been compared with regard to their usefulness for optimization. It turns out that gradient search is well suited for optimization in smooth fitness landscapes without local minima, whereas evolution strategy seems to be a method of choice for optimization in a high-dimensional multimodal search space. This is concluded from optimization experiments using a multimodal example function.

Amino Acid Sequence↗
PubMed2004

Inversion of guided-wave dispersion data with application to borehole acoustics.

The problem of inferring unknown geometry and material parameters of a waveguide model from noisy samples of the associated modal dispersion curves is considered. In a significant reduction of the complexity of a common inversion methodology, the inner of two nested iterations is eliminated: The approach described does not employ explicit fitting of the data to computed dispersion curves. Instead, the unknown parameters are adjusted to minimize a cost function derived directly from the determinant of the boundary condition system matrix. This results in an efficient inversion scheme that, in the case of noise-free data, yields exact results. Multimode data can be simultaneously processed without extra complications. Furthermore, the inversion scheme can accommodate an arbitrary number of unknown parameters, provided that the data have sufficient sensitivity to these parameters. As an important application, we consider the sonic guidance condition for a fluid-filled borehole in an elastic, homogeneous, and isotropic rock formation for numerical forward and inverse dispersion analysis. We investigate numerically the parametric inversion with errors in the model parameters and the influence of bandwidth and noise, and examine the cases of multifrequency and multimode data, using simulated flexural and Stoneley dispersion data.

Journal Article↗
PubMed2026

AI-driven diagnostic and prognostic models for metabolic dysfunction-associated steatotic liver disease: insights from clinical, imaging, and multi-omics studies-a scoping review.

Metabolic dysfunction-associated steatotic liver disease (MASLD), formerly known as non-alcoholic fatty liver disease (NAFLD), is the most common chronic liver disease around the world, affecting 33.6% of the adult population (95% CI: 28.1%-39.5%; I 2 = 99.9%), or roughly one in three. The extent of the liver damage is variable, from simple steatosis to metabolic dysfunction-associated steatohepatitis (MASH, formerly NASH), cirrhosis and hepatocellular carcinoma (HCC). Early diagnosis is essential to prevent serious liver damage. Traditional diagnostic techniques such as liver biopsy, imaging, and biomarker testing are all invasive, costly, reduced sensitive to early-stage disease, and they also have variability among observers. Modern diagnostic and prognostic approaches based on the principles of Artificial Intelligence (AI) and specifically on machine learning (ML) and deep learning (DL) have enabled multimodal approaches integrating clinical, imaging and molecular data. This scoping review conducted per PRISMA-ScR guidelines, synthesizes findings from 73 studies (search window 2020-2026) across three dimensions: clinical data driven models, imaging-based classifiers (ultrasound, CT and MRI), and multi-omics (genomics, transcriptomics and proteomics) techniques. Moreover, emergence of models such as U-Net and LiverNet 2.x, classification models like DeepLiverNet and BiLSTM models, as well as transformer frameworks and the identification of biomarkers models are also described. This study also investigates challenges such as data heterogeneity, data interpretability, fairness and real-world clinical application. Finally, important areas of research opportunities and future directions are highlighted to present a developing clinically applicable, explainable and ethical AI solutions to manage MASLD.

MASLD↗
PubMed2005

Dynamic physiological modeling for functional diffuse optical tomography.

Diffuse optical tomography (DOT) is a noninvasive imaging technology that is sensitive to local concentration changes in oxy- and deoxyhemoglobin. When applied to functional neuroimaging, DOT measures hemodynamics in the scalp and brain that reflect competing metabolic demands and cardiovascular dynamics. The diffuse nature of near-infrared photon migration in tissue and the multitude of physiological systems that affect hemodynamics motivate the use of anatomical and physiological models to improve estimates of the functional hemodynamic response. In this paper, we present a linear state-space model for DOT analysis that models the physiological fluctuations present in the data with either static or dynamic estimation. We demonstrate the approach by using auxiliary measurements of blood pressure variability and heart rate variability as inputs to model the background physiology in DOT data. We evaluate the improvements accorded by modeling this physiology on ten human subjects with simulated functional hemodynamic responses added to the baseline physiology. Adding physiological modeling with a static estimator significantly improved estimates of the simulated functional response, and further significant improvements were achieved with a dynamic Kalman filter estimator (paired t tests, n=10, P<0.05). These results suggest that physiological modeling can improve DOT analysis. The further improvement with the Kalman filter encourages continued research into dynamic linear modeling of the physiology present in DOT. Cardiovascular dynamics also affect the blood-oxygen-dependent (BOLD) signal in functional magnetic resonance imaging (fMRI). This state-space approach to DOT analysis could be extended to BOLD fMRI analysis, multimodal studies and real-time analysis.

Blood Pressure↗
PubMed2005

Role of the surface heterogeneity in adsorption of hydrogen ions on metal oxides: theory and simulations.

In this article we study the effect of energetic heterogeneity of a crystalline surface on the adsorption of hydrogen ions (protons) from the liquid phase. In particular, we examine the influence of the shape of the adsorption energy distribution on the equilibrium isotherms of hydrogen ions. To that purpose, a few popular distribution functions, including rectangular, exponential, and asymmetric Gaussian are considered. Additionally, multimodal distribution functions, which may correspond to the adsorption on different crystal planes of the oxide, are also used. Lateral interactions between adsorbed charges are modeled using the potential function proposed by Borkovec et al., which accounts also for polarization of the liquid medium. The results presented here are obtained using both Monte Carlo (MC) simulations and theoretical calculations involving Mean Field Approximation (MFA). They indicate that increased energetic heterogeneity of the adsorbing surface may, in general, considerably change the behavior of the adsorption isotherms, regardless of the assumed distribution function. It is also shown that the predictions of the proposed theory are consistent with the data obtained from the MC simulations.

Journal Article↗
PubMed1989

On cross-modal similarity: the perceptual structure of pitch, loudness, and brightness.

Examined how pitch and loudness correspond to brightness. In the Experiment 1, 16 Ss identified which of 2 lights more resembled each of 16 tones; in Experiment 2, 8 of the same 16 Ss rated the similarity of lights to lights, tones to tones, and lights to tones. (1) Pitch and loudness both contributed to cross-modal similarity, but for most Ss pitch contributed more. (2) Individuals differed as to whether pitch or loudness contributed more; these differences were consistent across matching and similarity scaling. (3) Cross-modal similarity depended largely on relative stimulus values. (4) Multidimensional scaling revealed 2 perceptual dimensions, loudness and pitch, with brightness common to both. A simple quantitative model can describe the cross-modal comparisons, compatible with the view that perceptual similarity may be characterized through a malleable spatial representation that is multimodal as well as multidimensional.

Attention↗
PubMed2006

Reaction time distribution analysis of neuropsychological performance in an ADHD sample.

Differences in reaction time (RT) variability have been documented between children with and without Attention Deficit Hyperactivity Disorder (ADHD). Most previous research has utilized estimates of normal distributions to examine variability. Using a nontraditional approach, the present study evaluated RT distributions on the Conners' Continuous Performance Test in children and adolescents from the Multimodal Treatment Study of ADHD sample compared to a matched sample of normal controls (n = 65 pairs). The ex-Gaussian curve was used to model RT and RT variability. Children with ADHD demonstrated faster RT associated with the normal portion of the curve and a greater proportion of abnormally slow responses associated with the exponential portion of the curve. These results contradict previous interpretation that children with ADHD have slower than normal responding and demonstrate why slower RT is found when estimates of variability assume normal Gaussian distributions. Further, results of this study suggest that the greater number of abnormally long RTs of children with ADHD reflect attentional lapses on some but not all trials.

Attention Deficit Disorder with Hyperactivity↗
PubMed2026

CAUSAL artificial intelligence and data-driven decision intelligence in personalized medicine: a review of healthcare informatics systems.

This review examines the integration of causal artificial intelligence (AI) and data-driven decision intelligence within healthcare informatics systems to advance personalized medicine and clinical decision-making. A narrative review methodology was employed, synthesizing interdisciplinary literature from major databases, including PubMed, Scopus, Web of Science, IEEE Xplore, and ScienceDirect. Studies focusing on causal inference, decision intelligence, and healthcare informatics applications in personalized medicine were included. Data were extracted on methodological approaches, healthcare settings, analytical techniques, and clinical applications, followed by thematic synthesis. Findings indicate that causal AI enhances clinical decision support by enabling estimation of treatment effects and simulation of intervention outcomes at the individual patient level. Integration of multimodal health data such as electronic health records, genomic data, and real-time monitoring improves prediction accuracy and supports tailored treatment strategies. Additionally, causal models improve interpretability, fostering clinician trust and facilitating transparent decision-making. Robust healthcare informatics infrastructures, including interoperable systems and data warehouses, were identified as critical enablers of causal analytics. Overall, causal AI represents a transformative advancement in healthcare analytics, supporting more informed, individualized, and evidence-based clinical decisions. Its integration within healthcare informatics systems has significant potential to improve patient outcomes and guide the future of intelligent, personalized healthcare delivery.

Precision Medicine↗
PubMed2002

High-resolution spatio-temporal functional neuroimaging of brain activity.

The past decades have shown extraordinary progress in our ability to noninvasively image the functions of the human brain. Of particular interest is the recent trend in combining information from electrophysiological and magnetic resonance imaging, which we termed eMRI, to achieve high-resolution functional neuroimaging in both space and time domains. In this article, we review the recent progress in high-resolution functional neuroimaging, in particular the multimodal integration of electroencephalography (EEG) and magnetic resonance imaging (MRI). The state-of-the-art EEG inverse solutions based on different brain electric source models and various approaches to integrate the information from MRI are reviewed. The remaining challenges, future trends, and potential applications of the high-resolution functional neuroimaging research are discussed.

Action Potentials↗
PubMed1994

Contemplating the plasmalemmal control center model.

An abundant epidermal mechanosensory calcium-selective ion channel appears able not only to detect mechanical stimuli such as those that initiate gravitropism but also to detect thermal, electrical, and various chemical stimuli. Because it responds to multimodal input with a second messenger output, this channel system seems likely to be an integrator that can engage in feedbacks with many other systems of the cell--and feedback is the hallmark of regulation. In general, the mechanical tension required for channel activation is likely transmitted from the relatively rigid cell wall to the plasma membrane system via linkage or adhesion sites that display antigenicities recognized by antibodies to animal beta-1 integrin, vitronectin, and fibronectin and which have mechanical connections to the cytoskeleton. Thus, functionally, leverage exerted against any given adhesion site will tend to control channels within a surrounding domain. Reactions initiated by passage of calcium ions through the channels could presumably be more effectively regulated if channels within the domains were somewhat clustered and if appropriate receptors, kinases, porters, pumps, and some key cytoskeletal anchoring sites were in turn clustered about them. Accumulating evidence suggests not only that activity of clusters of channels may contribute to control of cytoskeletal architecture and of regulatory protein function within their domain, but also that both a variety of regulatory proteins and components of the cortical cytoskeleton may contribute to control of channel activity. The emerging capabilities of electronic optical microscopy are well suited for resolving the spatial distributions of many of these cytoskeletal and regulatory molecules in living cells, and for following some of their behaviors as channels are stimulated to open and cytosolic calcium builds in their vicinity. Such microscopy, coupled with biochemical and physiological probing, should help to establish the nature of the feedback loops putatively controlled by the linkage sites and their channel domains.

Calcium Channels↗
PubMed2004

Imaging tri-fusion multimodality reporter gene expression in living subjects.

Imaging reporter gene expression in living subjects with various imaging modalities is a rapidly accelerating area of research. Applications of these technologies to cancer research, gene therapy, and transgenic models are rapidly expanding. We report construction and testing of several triple fusion reporter genes compatible with bioluminescence, fluorescence and positron emission tomography (PET) imaging. A triple fusion reporter vector harboring a bioluminescence synthetic Renilla luciferase (hrl) reporter gene, a reporter gene encoding the monomeric red fluorescence protein (mrfp1), and a mutant herpes simplex virus type 1 sr39 thymidine kinase [HSV1-truncated sr39tk (ttk); a PET reporter gene] was found to preserve the most activity for each protein component and was therefore investigated in detail. After validating the activities of all three proteins encoded by the fusion gene in cell culture, we imaged living mice bearing 293T cells transiently expressing the hrl-mrfp-ttk vector by microPET and using a highly sensitive cooled charge-coupled device camera compatible with both bioluminescence and fluorescence imaging. A lentiviral vector carrying the triple fusion reporter gene was constructed and used to isolate stable expressers by fluorescence-activated cell sorting. These stable 293T cells were further used to show good correlation (R(2) approximately 0.74-0.85) of signal from each component by imaging tumor xenografts in living mice with all three modalities. Furthermore, metastases of a human melanoma cell line (A375M) stably expressing the triple fusion were imaged by microPET and optical technologies over a 40-50-day time period in living mice. Imaging of reporter gene expression from single cells to living animals with the help of a single tri-fusion reporter gene will have the potential to accelerate translational cancer research.

Animals↗
PubMed1991

Common projection areas of antennal and visual pathways in the honeybee brain, Apis mellifera.

The convergence of primary sensory neurons of the antennae, higher order visual interneurons, and antennal motoneurons was analysed with neuroanatomical techniques in the honeybee, Apis mellifera. The different modalities evoke specific antennal responses in this insect. Three different fluorescent dyes were applied successively in the same preparation in order to visualise the various fiber projections from the antennae and the lobula in the brain of the honeybee. Three neuropile areas where sensory fibers of the antennae overlap with visual projection neurons from the lobula were found. Within the posterior-median protocerebrum the antennal tract T6-1 comes in close vicinity to the lobula tract LoT-9 and to some other lobula fibers that cannot be assigned to a special tract. Antennal T6-3 fibers overlap with lobula LoT-7 neurons within the posterior protocerebrum more laterally. Antennal T5 fibers arborise in the dorsal lobe and show common projection sites with lobula LoT-3 neurons. The multimodal convergence in the three common neuropiles demonstrates that these areas are important centers for multimodal information processing between sensory, motor, and descending neurons in insects.

Animals↗
PubMed1977

Brain-tumor therapy. Quantitative analysis using a model system.

A recently developed colony-formation assay has been used to evaluate in vivo 1,3-bis(2-chloroethyl)-1-nitrosourea (BCNU) therapy of a transplantable rat brain-tumor model. A comparison of the in vitro colony-forming capacity of treated and untreated tumor cells permits calculation of the fraction of clonogenic tumor cells surviving in vivo therapy; The plateau that we previously observed o the BCNU dose-response curve is not the result of repair of potentially lethal damage, since no change in the 0.1% of surviving clonogenic tumor cells occurs during the first 2 to 4 days after treatment. Although reanalysis of the dose-response curve indicates that sublethal damage exists, its repair is probably minimal. The most likely explanation for the observed limitation of the BCNU effect is the drug's failure to reach all clonogenic cells. A dose of BCNU that kills more than 99.9% of clonogenic tumor cells within 30 minutes of treatment results in only a 60% decrease in tumor weight by Day 14. This disparity is explained by retarded removal of dead cells, and, along with a previously determined 90% cell-kill threshold necessary to appreciate increased animal survival, demonstrates the inherent limitations of measurements of tumor size (including brain scans and clinical patient evaluations) in evaluating the efficacy of brain-tumor therapy. Following at LD10 dose of BCNU the surviving clonogenic tumor cells increase in number after latency period of 2 to 4 days; during regrowth the cell doubling time is 40 hours. Marked variability in tumor response and regrowth was noted. The determination of information regarding disturbed tumor cell kinetics and tumor heterogeneityis essential for the proper planning of combination chemotherapy and multimodality regimens.

Animals↗
PubMed1988

Standardization and analysis of digitized photographic data in the longitudinal documentation of cataractous growth.

Age-related cataract formation in man can be documented with slit and retroillumination photographs. With digitization and image analysis of such photographs a cataract may be characterized by a frequency distribution of picture elements over a 255 step gray scale spectrum. Transition from a clear to a cataractous lens may be manifested as a change from a unimodal, Gaussian to a multimodal, non Gaussian frequency distribution respectively. How should one compare and contrast these two distributions, so to accurately describe the extent and significance of a change in lens opacification? The in vitro system of cold cataract formation in the rabbit lens was used as a model of the much slower process of age-related cataract formation in man. As in the human lens undergoing progressive opacification, the frequency distribution (number of pixels vs. intensity of gray) for a digitized image of a clear lens at 26 degrees C is unimodal and Gaussian; that of a fully developed cold cataract at 10 degrees C is multimodal and non-gaussian. In spite of the increasing multimodality of the frequency distribution as the temperature dropped and the cataract grew in density and size, the mean gray density proved to be a valid and useful measure to characterize the distribution and to compare different unaligned images. The Wilcoxon Rank Sum Test proved to be useless in comparing the frequency distributions from cataract images because it proved to be too sensitive to subtle changes in the degree of opacification. Anomalous behavior of the opacification process--i.e. clarification as well as opacification of the lens during cold cataract formation caused all pairs to appear statistically significantly different when in appearance there was no difference. The mean of the frequency distribution is less sensitive to this anomalous behavior and is useful as a comparative index. The method of calculating the threshold of significant change in the mean density of a cataract image is presented.

Animals↗
PubMed2006

The Israel Center for Medical Simulation: a paradigm for cultural change in medical education.

Simulation-based medical education (SBME) is a rapidly growing field, as is illustrated by the increased development of simulation centers worldwide. SBME is becoming a powerful force in addressing the need to increase patient safety through quality-care training. Recognizing the benefits of SBME, increasing numbers of bodies involved in medical and health care education and training are establishing simulation centers worldwide. The general model of most facilities focuses on a single simulation modality or a specific branch of medicine or health care, limiting their overall impact on patient safety and quality of care across the health care systems. MSR, the Israel Center for Medical Simulation, is a comprehensive, national, multimodality, multidisciplinary medical simulation center dedicated to enhancing hands-on medical education, performance assessment, patient safety, and quality of care by improving clinical and communication skills. The center uses an "error-driven" educational approach, which recognizes that errors provide an opportunity to create a unique beneficial learning experience. The authors present the Israeli experience as an alternative model, and describe the impact of the MSR model on the Israeli medical community during four years of activity. They also describe the opportunities this model has opened towards changing the culture of medical education and patient safety within Israel Although this model may require modification when implemented in other medical systems, it highlights important lessons regarding the power of SBME in triggering and bringing about cultural changes in traditional medical education.

Computer Simulation↗