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Okada, D.

Publications and source records attributed to Okada, D..

6 recordsLinked to original sources

Population geometries in frontal cortex coordinate value-based decisions

Decisions often involve trade-offs between benefits and costs, such as a small payment now vs. a larger payment after a delay. Although decision variables are distributed across frontal cortex, how these regions transform competing attributes into a choice remains unclear. Combining large-scale electrophysiology with causal perturbations as mice chose between different reward amounts and delays, we found that population geometry of decision variables differed across regions, reflecting distinct computations. Dorsal frontal areas, including motor cortex, collapsed competing attributes onto a decision axis shared across reward-delay contexts, with projection amplitude predicting choice probability; silencing these areas impaired action selection regardless of delay. In contrast, ventral prefrontal cortex (vPFC) represented choice in higher-dimensional subspaces organized by reward delay, whose geometry predicted how strongly delay influenced choice. Notably, inhibiting vPFC preserved the dorsal decision representation but selectively removed its modulation by reward delay, causing animals to behave as if delay no longer influenced choice. vPFC inhibition had no effect when mice chose between reward amounts. Frontal cortex therefore solves multi-attribute decisions through a generator-modulator architecture: dorsal frontal circuits maintain a shared choice axis guiding decisions across contexts, whereas vPFC maintains competing attributes in distinct subspaces that modulate decisions when options conflict.

neuroscience↗

Dynamic belief representation and updating through learned attractor-like dynamics in the frontal cortex

To act adaptively, animals must infer hidden states of the world from incomplete sensory information and update beliefs as new observations accrue. While dopamine signals are well explained by reinforcement learning models that incorporate belief states, how the brain implements belief-state inference remains unknown. Prior modeling work showed that recurrent neural networks trained to predict value (Value-RNN) develop task-specific, attractor-like dynamics that mirror evolution of beliefs. Here we performed high-density electrophysiological recordings from orbitofrontal cortex (OFC) and other brain areas of mice performing two variants of a Pavlovian task that differ in reward probability, which produce different within-trial belief dynamics. We find that OFC population activity exhibits task-specific attractor-like dynamics that mirror the within-trial dynamics in the Value-RNN. These dynamics are absent in motor and olfactory regions, are not explained by behavioral differences, and emerge progressively with learning. Our findings indicate that the brain approximates belief-state inference through learned, task-specific attractor-like dynamics.

neuroscience↗

Evaluation of fluorescent proteins for compatibility with STED microscopy systems using two-color spectroscopies

Stimulated emission depletion (STED) microscopy is a super-resolution fluorescence imaging technique that achieves high spatial and temporal resolution by exploiting stimulated emission to induce fluorescence depletion (FD) and is expected to have substantial utility for imaging applications using fluorescent proteins. However, the compatibility of fluorescent proteins with STED microscopy systems has been understood primarily through empirical observations, and there is no established methodology for the rational selection of fluorescent proteins for STED microscopy. In this study, we systematically evaluated the compatibility of commonly used fluorescent proteins with STED microscopy systems by measuring FD properties using transient absorption spectroscopy and fluorescence dip spectroscopy, both of which are classified as two-color spectroscopy (TCS). Fluorescent proteins identified as compatible with the STED microscopy system based on the TCS measurements were employed for three-dimensional STED imaging of cellular samples expressing each protein. In all samples, three-dimensional spatial resolution was improved relative to confocal laser microscopy, with particularly marked improvements in z-axis resolution. These findings demonstrate that measurements of FD properties via TCS provide a robust approach for evaluating the compatibility of fluorescent proteins with the STED microscopy system and for selecting suitable fluorescent proteins for STED imaging.

biophysics↗

NK Cells Effectively Mediating Antibody-Mediated Kidney Allograft Rejection Requires a Specific Activation Receptor and Graft Expression of the Ligand

Acute antibody-mediated rejection (aABMR) is an important cause of clinical kidney graft injury and failure. Transcripts associated with NK cell activation in graft biopsies are diagnostic of aABMR, but mechanisms underlying NK cell activation during ABMR remain poorly understood. In contrast to the long-term (> 60 days) survival of complete MHC-mismatched kidney allografts in wild type C57BL/6 mice, B6.CCR5-/- recipients develop high titers of donor-specific antibody (DSA) with allograft rejection between days 18 to 28 post-transplant. This has allowed investigation of mechanisms underlying NK cell activation within kidney allografts during aABMR. DSA titers first became detectable in B6.CCR5-/- (H-2b) recipients of A/J (H-2a) kidney allografts at day 8 and peaked on day 15 post-transplant and was accompanied by a parallel increase in mRNA levels of Rae-1e, a ligand for the NK cell activation receptor NKG2D. A/J kidneys in B6.CCR5-/-NKG2D-/- recipients and A/J.Rae-1e-/- kidneys in B6.CCR5-/- recipients survived >60 days, despite high serum DSA levels. Flow cytometric analysis of allograft infiltrating cells in B6.CCR5-/- recipients on day 15 post-transplant revealed inflammatory monocyte and NK cell infiltration and NK cell activation to proliferate and express CD107a, a marker of cytotoxic function. These features of aABMR were absent or markedly reduced by recipient NKG2D- or donor graft Rae-1e-deficiency. These findings suggest that interference with expression of allograft Rae-1e or recipient NK cell NKG2D abrogates aABMR despite persistently high DSA levels and that aABMR requires coordination between infiltrating NK cell and inflammatory monocyte activation within the kidney allograft.

immunology↗

The opposite aging effect to single cell transcriptome profile among cell subsets.

Comparing transcriptome profiling between younger and older samples reveals genes related to aging and provides insight into the biological functions affected by aging. Recent research has identified sex, tissue, and cell type-specific age-related changes in gene expression. This study reports the overall picture of the opposite aging effect, in which aging increases gene expression in one cell subset and decreases it in another cell subset. Using the Tabula Muris Senes dataset, a large public single-cell RNA sequencing dataset from mice, we compared the effects of aging in different cell subsets. As a result, the opposite aging effect was observed widely in genome-wide genes, particularly enriched in genes related to ribosomal function and translation. The opposite aging effect was observed in the known aging-related genes. Furthermore, the opposite aging effect was observed in the transcriptome diversity quantified by the number of expressed genes and the Shannon entropy. This study highlights the importance of considering the cell subset when intervening with aging-related genes.

genomics↗

LAVENDER: latent axes discovery from multiple cytometry samples with non-parametric divergence estimation and multidimensional scaling reconstruction

Computational cytometry methods are now frequently used in flow and mass cytometric data analyses. However, systematic bias-free methodologies to assess inter-sample variability have been lacking, thereby hampering efficient data mining from a large set of samples. Here, we devised a computational method termed LAVENDER (latent axes discovery from multiple cytometry samples with nonparametric divergence estimation and multidimensional scaling reconstruction). It measures the Jensen-Shannon distances between samples using the k-nearest neighbor density estimation and reconstructs samples in a new coordinate space, called the LAVENDER space. The axes of this space can then be compared against other omics measurements to obtain biological information. Application of LAVENDER to multidimensional flow cytometry datasets of 301 Japanese individuals immunized with a seasonal influenza vaccine revealed an axis related to baseline immunological characteristics of each individual. This axis correlated with the proportion of plasma cells and the neutrophil-to-lymphocyte ratio, a clinical marker of the systemic inflammatory response. The same method was also applicable to mass cytometry data with more molecular markers. These results demonstrate that LAVENDER is a useful tool for identifying critical heterogeneity among similar, yet different, single-cell datasets.

bioinformatics↗