Belief inference for hierarchical hidden states in spatial navigation.

Uncertainty abounds in the real world, and in environments with multiple layers of unobservable hidden states, decision-making requires resolving uncertainties based on mutual inference. Focusing on a spatial navigation problem, we develop a Tiger maze task that involved simultaneously inferring the local hidden state and the global hidden state from probabilistically uncertain observation. We adopt a Bayesian computational approach by proposing a hierarchical inference model. Applying this to human task behaviour, alongside functional magnetic resonance brain imaging, allows us to separate the neural correlates associated with reinforcement and reassessment of belief in hidden states. The imaging results also suggest that different layers of uncertainty differentially involve the basal ganglia and dorsomedial prefrontal cortex, and that the regions responsible are organised along the rostral axis of these areas according to the type of inference and the level of abstraction of the hidden state, i.e. higher-order state inference involves more anterior parts.

Deep learning-based image deconstruction method with maintained saliency.

Visual properties that primarily attract bottom-up attention are collectively referred to as saliency. In this study, to understand the neural activity involved in top-down and bottom-up visual attention, we aim to prepare pairs of natural and unnatural images with common saliency. For this purpose, we propose an image transformation method based on deep neural networks that can generate new images while maintaining the consistent feature map, in particular the saliency map. This is an ill-posed problem because the transformation from an image to its corresponding feature map could be many-to-one, and in our particular case, the various images would share the same saliency map. Although stochastic image generation has the potential to solve such ill-posed problems, the most existing methods focus on adding diversity of the overall style/touch information while maintaining the naturalness of the generated images. To this end, we developed a new image transformation method that incorporates higher-dimensional latent variables so that the generated images appear unnatural with less context information but retain a high diversity of local image structures. Although such high-dimensional latent spaces are prone to collapse, we proposed a new regularization based on Kullback-Leibler divergence to avoid collapsing the latent distribution. We also conducted human experiments using our newly prepared natural and corresponding unnatural images to measure overt eye movements and functional magnetic resonance imaging, and found that those images induced distinctive neural activities related to top-down and bottom-up attentional processing.

Confidence modulates the decodability of scene prediction during partially-observable maze exploration in humans.

Prediction ability often involves some degree of uncertainty-a key determinant of confidence. Here, we sought to assess whether predictions are decodable in partially-observable environments where one's state is uncertain, and whether this information is sensitive to confidence produced by such uncertainty. We used functional magnetic resonance imaging-based, partially-observable maze navigation tasks in which subjects predicted upcoming scenes and reported their confidence regarding these predictions. Using a multi-voxel pattern analysis, we successfully decoded both scene predictions and subjective confidence from activities in the localized parietal and prefrontal regions. We also assessed confidence in their beliefs about where they were in the maze. Importantly, prediction decodability varied according to subjective scene confidence in the superior parietal lobule and state confidence estimated by the behavioral model in the inferior parietal lobule. These results demonstrate that prediction in uncertain environments depends on the prefrontal-parietal network within which prediction and confidence interact.

Solubilization of Paclitaxel by Self-Assembled Amphiphilic Phospholipid-Mimetic Polymers with Varied Hydrophobicity.

2-Methacryloyloxyethyl phosphorylcholine (MPC) polymers have been used as a coating agent on medical devices and as a carrier in drug delivery systems (DDSs). Paclitaxel (PTX) is a water-insoluble anticancer drug whose solubilizer is necessary for administration. Block and random copolymers composed of hydrophilic MPC and butyl methacrylate, named PMB, show different properties, depending on the polymer sequence and MPC content. In the present study, we used amphiphilic MPC polymers comprising hydrophobic dodecyl methacrylate (DMA). The self-assembling properties and PTX solubilization of random and block poly(MPC-co-DMA)s (rPMDs and bPMDs) with different compositions were examined and compared. rPMDs with high DMA content formed large and relatively loose self-assembled structures, which solubilized PTX. However, bPMDs formed small and compact self-assembled structures with poor PTX solubilization. PTX solubilized by PMB with small and loose self-assembled structures showed efficient drug action, similar to free PTX; however, rPMDs fell short of demonstrating PTX efficiency. Our results suggest that the self-assembling properties and the hydrophobicity of amphiphilic MPC polymers largely affect PTX solubilization as well as drug action, which is required to be controlled by the polymer sequence, as well as the structure and composition of the hydrophobic monomer for efficient DDS.

Characterization of the Hydration Process of Phospholipid-Mimetic Polymers Using Air-Injection-Mediated Liquid Exclusion Methods.

2-Methacryloyloxyethyl phosphorylcholine (MPC) polymers including hydrophobic units such as poly(MPC-co-butyl methacrylate) (PMB) and poly(MPC-co-dodecyl methacrylate) (PMD) are used as coating agents for medical devices because of their antifouling effects. In this study, the whole hydration process of MPC polymer-coated surfaces was investigated using air-injection-mediated liquid exclusion (AILE) methods in which the liquid exclusion diameter during air injection was correlated to the water-repelling property. The prejetted and standard AILE methods showed the initial change from a dry to a wet state and the swelling behaviors of the MPC polymers, respectively. The liquid exclusion diameter of the MPC polymer-coated surfaces increased with an increase in the immersion time in various aqueous solutions such as deionized water, phosphate-buffered saline (PBS), and cell culture media. Moreover, the liquid exclusion diameter of the PMD-coated surface was larger than that of the PMB-coated one. Ellipsometry directly indicated the polymer layers swollen in water. Scanning probe microscopy (SPM) revealed that nanosized protuberances were formed in water, especially at the PMD-coated surface. The different swelling behaviors of these MPC polymer-coated surfaces affected the liquid exclusion diameters. Thus, the AILE methods are a powerful tool to elucidate the hydration process in various liquid media.

Formation of Hydrophobic Domains on the poly(MPC-co-Dodecyl Methacrylate)-Coated Surface Recognized by Macrophage-like Cells.

Copolymers comprising 2-methacryloyloxyethyl phosphorylcholine (MPC) and hydrophobic methacrylic esters were used as biomembrane-mimetic polymers to provide blood compatibility. In the present study, we compared the surfaces coated with two MPC polymers with different alkyl groups, namely, poly(MPC-co-butyl methacrylate) (PMB) and poly(MPC-co-dodecyl methacrylate) (PMD), to clarify the effect of their hydrophobic units. Various substrates, such as poly(ethylene terephthalate), polycarbonate, polypropylene, acrylonitrile-butadiene-styrene copolymer, and stainless steel, were coated with ethanol solutions containing various concentrations of PMD or PMB. The solubility of PMD in ethanol changed depending on the water content. Scanning probe microscopy and rhodamine 6G staining revealed heterogeneous microstructures on the PMD-coated surface but not on the PMB-coated surface. Adhesion of various cells was efficiently suppressed by the PMD coating at lower concentration than the PMB coating, except regarding the adhesion of macrophage-like RAW264.7 cells. Our results suggest that the dodecyl groups in PMD increased its affinity for the substrates and simultaneously induced the formation of hydrophobic domains recognized by RAW264.7 cells.