BlinkLinMulT: Transformer-Based Eye Blink Detection.

This work presents BlinkLinMulT, a transformer-based framework for eye blink detection. While most existing approaches rely on frame-wise eye state classification, recent advancements in transformer-based sequence models have not been explored in the blink detection literature. Our approach effectively combines low- and high-level feature sequences with linear complexity cross-modal attention mechanisms and addresses challenges such as lighting changes and a wide range of head poses.

Cross-Viewpoint Semantic Mapping: Integrating Human and Robot Perspectives for Improved 3D Semantic Reconstruction.

Allocentric semantic 3D maps are highly useful for a variety of human-machine interaction related tasks since egocentric viewpoints can be derived by the machine for the human partner. Class labels and map interpretations, however, may differ or could be missing for the participants due to the different perspectives. Particularly, when considering the viewpoint of a small robot, which significantly differs from the viewpoint of a human.

Peripheral gene interactions define interpretable clusters of core ASD genes in a network-based investigation of the omnigenic theory.

According to the recently proposed omnigenic theory, all expressed genes in a relevant tissue are contributing directly or indirectly to the manifestation of complex disorders such as autism. Thus, holistic approaches can be complementary in studying genetics of these complex disorders to focusing on a limited number of candidate genes. Gene interaction networks can be used for holistic studies of the omnigenic nature of autism.

Tracking Highly Similar Rat Instances under Heavy Occlusions: An Unsupervised Deep Generative Pipeline.

Identity tracking and instance segmentation are crucial in several areas of biological research. Behavior analysis of individuals in groups of similar animals is a task that emerges frequently in agriculture or pharmaceutical studies, among others. Automated annotation of many hours of surveillance videos can facilitate a large number of biological studies/experiments, which otherwise would not be feasible.

The Autism Palette: Combinations of Impairments Explain the Heterogeneity in ASD.

Autism spectrum disorder (ASD) is a heterogeneous neuropsychiatric condition traditionally defined by core symptoms in social behavior, speech/communication, repetitive behavior, and restricted interests. Beyond the core symptoms, autism has strong association with other disorders such as intellectual disability (ID), epilepsy, schizophrenia among many others. This paper outlines a theory of ASD with capacity to connect heterogeneous "core" symptoms, medical and psychiatric comorbidities as well as other etiological theories of autism in a unifying cognitive framework rooted in neuroscience and genetics.

Role of oligo(malic acid) on the formation of unilamellar vesicles.

Stable unilamellar dipalmitoylphosphatidylcholine vesicles were produced by using oligo(malic acid) and cholesterol. Detailed physico-chemical characterization prove that by using oligo(malic acid) the substitution of PEGylated lipids for sterically stabilization comes possible. The polymer molecules cover the outer surface of spherical-shaped vesicles, and an asymmetrical composition occurs in the two leaflets of the phospholipid bilayer.

Correction: Strategic predictors of performance in a divided attention task.

[This corrects the article DOI: 10.1371/journal.pone.

Strategic predictors of performance in a divided attention task.

In this study we investigate the strategies of subjects in a complex divided attention task. We conducted a series of experiments with ten participants and evaluated their performance. After an extensive analysis, we identified four strategic measures that justify the achievement of the participants, by highlighting the individual differences and predicting performance in a regression analysis using generalized estimating equations.

Semi-Supervised Learning of Cartesian Factors: A Top-Down Model of the Entorhinal Hippocampal Complex.

The existence of place cells (PCs), grid cells (GCs), border cells (BCs), and head direction cells (HCs) as well as the dependencies between them have been enigmatic. We make an effort to explain their nature by introducing the concept of Cartesian Factors. These factors have specific properties: (i) they assume and complement each other, like direction and position and (ii) they have localized discrete representations predictive attractors enabling implicit metric-like computations.

MDR-1 and MRP-1 activity in peripheral blood leukocytes of rheumatoid arthritis patients.

Background: Rheumatoid Arthritis is a chronic disease leading to decreased quality of life with a rather variable response rate to Disease Modifying Anti Rheumatic Drugs. Methotrexate (MTX) is the gold standard therapy in Rheumatoid Arthritis. The Multidrug resistance Related Protein and Multi Drug Resistance protein 1, also called P-glycoprotein-170 transporters can alter the intracellular concentration of different drugs.

Decreased functional activity of multidrug resistance protein in primary colorectal cancer.

Background: The ATP-Binding Cassette (ABC)-transporter MultiDrug Resistance Protein 1 (MDR1) and Multidrug Resistance Related Protein 1 (MRP1) are expressed on the surface of enterocytes, which has led to the belief that these high capacity transporters are responsible for modulating chemosensitvity of colorectal cancer. Several immunohistochemistry and reverse transcription polymerase chain reaction (RT-PCR) studies have provided controversial results in regards to the expression levels of these two ABC-transporters in colorectal cancer. Our study was designed to determine the yet uninvestigated functional activity of MDR1 and MRP1 transporters in normal human enterocytes compared to colorectal cancer cells from surgical biopsies.

Effects of ursolic acid on the structural and morphological behaviours of dipalmitoyl lecithin vesicles.

Effects of ursolic acid on the structural and morphological characteristics of dipalmitoyl lecithin(DPPC)-water system was studied by using differential scanning calorimetry (DSC), small- and wide-angle X-ray scattering (SWAXS), freeze-fracture method combined with transmission electron-microscopy (FF-TEM) and infrared spectroscopy (FT-IR). The surface of the uncorrelated lipid system is rippled or grained and a huge number of small, presumably unilamellar vesicles are present if the UA/DPPC molar ratio is 0.1 mol/mol or higher.

Spatio-temporal Event Classification using Time-series Kernel based Structured Sparsity.

In many behavioral domains, such as facial expression and gesture, sparse structure is prevalent. This sparsity would be well suited for event detection but for one problem. Features typically are confounded by alignment error in space and time.

Efficient sparse coding in early sensory processing: lessons from signal recovery.

Sensory representations are not only sparse, but often overcomplete: coding units significantly outnumber the input units. For models of neural coding this overcompleteness poses a computational challenge for shaping the signal processing channels as well as for using the large and sparse representations in an efficient way. We argue that higher level overcompleteness becomes computationally tractable by imposing sparsity on synaptic activity and we also show that such structural sparsity can be facilitated by statistics based decomposition of the stimuli into typical and atypical parts prior to sparse coding.

Perception based method for the investigation of audiovisual integration of speech.

Speech comprehension is significantly improved by visual input on the speaker's mouth movements. Audiovisual integration underlying this phenomenon is often studied in EEG experiments in which the event related brain potential (ERP) elicited by a bimodal stimulus is compared to the sum of ERPs triggered by auditory and visual signals of the same source. However, this method leads to spurious results in time ranges when ERP components common to all these stimulus types are present.

Here and now: how time segments may become events in the hippocampus.

The hippocampal formation is believed to play a central role in memory functions related to the representation of events. Events are usually considered as temporally bounded processes, in contrast to the continuous nature of sensory signal flow they originate from. Events are then organized and stored according to behavioral relevance and are used to facilitate prediction of similar events.

Learning Tetris using the noisy cross-entropy method.

The cross-entropy method is an efficient and general optimization algorithm. However, its applicability in reinforcement learning (RL) seems to be limited because it often converges to suboptimal policies. We apply noise for preventing early convergence of the cross-entropy method, using Tetris, a computer game, for demonstration.

Novel anti-cholesterol monoclonal immunoglobulin G antibodies as probes and potential modulators of membrane raft-dependent immune functions.

Natural autoantibodies against cholesterol are present in the sera of all healthy individuals; their function, production, and regulation, however, are still unclear. Here, we managed to produce two monoclonal anti-cholesterol antibodies (ACHAs) by immunizing mice with cholesterol-rich liposomes. The new ACHAs were specific to cholesterol and to some structurally closely related 3beta-hydroxyl sterols, and they reacted with human lipoproteins VLDL, LDL, and HDL.

Competitive spiking and indirect entropy minimization of rate code: efficient search for hidden components.

Our motivation, which originates from the psychological and physiological evidences of component-based representations in the brain, is to find neural methods that can efficiently search for structures. Here, an architecture made of coupled parallel working reconstruction subnetworks is presented. Each subnetwork utilizes non-negativity constraint on the generative weights and on the internal representation.

Kalman filter control embedded into the reinforcement learning framework.

There is a growing interest in using Kalman filter models in brain modeling. The question arises whether Kalman filter models can be used on-line not only for estimation but for control. The usual method of optimal control of Kalman filter makes use of off-line backward recursion, which is not satisfactory for this purpose.

Cost component analysis.

In optimizations the dimension of the problem may severely, sometimes exponentially increase optimization time. Parametric function approximatiors (FAPPs) have been suggested to overcome this problem. Here, a novel FAPP, cost component analysis (CCA) is described.

Parallel and robust skeletonization built on self-organizing elements.

A massively parallel neural architecture is suggested for the approximate computation of the skeleton of a planar shape. Numerical examples demonstrate the robustness of the method. The architecture is constructed from self-organizing elements that allow the extension of the concept of skeletonization to areas remote to image processing.

The mystery of structure and function of sensory processing areas of the neocortex: a resolution.

Many different neural models have been proposed to account for major characteristics of the memory phenomenon family in primates. However, in spite of the large body of neurophysiological, anatomical and behavioral data, there is no direct evidence for supporting one model while falsifying the others. And yet, we can discriminate models based on their complexity and/or their predictive power.