[How Can We Reconstruct Mental Imagery from Brain Activities?].

Advances in machine learning and artificial intelligence (AI) have enabled the extraction of information such as perception and motor intention from neural activities, which is called neural decoding. A recent study demonstrated that mental imagery can be reconstructed from brain activity measured using functional magnetic resonance imaging. This article describes the method of mental image reconstruction and the underlying technologies that support it.

Distinct roles of monkey OFC-subcortical pathways in adaptive behavior.

Primates must adapt to changing environments by optimizing their behavior to make beneficial choices. At the core of adaptive behavior is the orbitofrontal cortex (OFC) of the brain, which updates choice value through direct experience or knowledge-based inference. Here, we identify distinct neural circuitry underlying these two separate abilities.

LineageVAE: reconstructing historical cell states and transcriptomes toward unobserved progenitors.

Motivation: Single-cell RNA sequencing (scRNA-seq) enables comprehensive characterization of the cell state. However, its destructive nature prohibits measuring gene expression changes during dynamic processes such as embryogenesis or cell state divergence due to injury or disease. Although recent studies integrating scRNA-seq with lineage tracing have provided clonal insights between progenitor and mature cells, challenges remain.

Fast, accurate, and interpretable decoding of electrocorticographic signals using dynamic mode decomposition.

Dynamic mode (DM) decomposition decomposes spatiotemporal signals into basic oscillatory components (DMs). DMs can improve the accuracy of neural decoding when used with the nonlinear Grassmann kernel, compared to conventional power features. However, such kernel-based machine learning algorithms have three limitations: large computational time preventing real-time application, incompatibility with non-kernel algorithms, and low interpretability.

Functional diversity of dopamine axons in prefrontal cortex during classical conditioning.

Midbrain dopamine neurons impact neural processing in the prefrontal cortex (PFC) through mesocortical projections. However, the signals conveyed by dopamine projections to the PFC remain unclear, particularly at the single-axon level. Here, we investigated dopaminergic axonal activity in the medial PFC (mPFC) during reward and aversive processing.

Muscle weakness is more strongly associated with functional outcomes in patients with stroke than sarcopenia or muscle wasting: an observational study.

Background: Stroke-related sarcopenia is an important prognosis factor and an intervention target for improving outcomes in patients with stroke.

Aim: This study aimed to identify the association between sarcopenia, possible sarcopenia, muscle weakness, muscle mass and calf circumference, and the functional outcomes 3 months after stroke.

Methods: In this single-centre prospective observational study, muscle strength, muscle mass, and calf circumference were measured in patients with acute stroke at hospital discharge.

Distinct roles of monkey OFC-subcortical pathways in adaptive behavior.

To be the most successful, primates must adapt to changing environments and optimize their behavior by making the most beneficial choices. At the core of adaptive behavior is the orbitofrontal cortex (OFC) of the brain, which updates choice value through direct experience or knowledge-based inference. Here, we identify distinct neural circuitry underlying these two separate abilities.

Mental image reconstruction from human brain activity: Neural decoding of mental imagery via deep neural network-based Bayesian estimation.

Visual images observed by humans can be reconstructed from their brain activity. However, the visualization (externalization) of mental imagery is challenging. Only a few studies have reported successful visualization of mental imagery, and their visualizable images have been limited to specific domains such as human faces or alphabetical letters.

Reconstructing visual illusory experiences from human brain activity.

Visual illusions provide valuable insights into the brain's interpretation of the world given sensory inputs. However, the precise manner in which brain activity translates into illusory experiences remains largely unknown. Here, we leverage a brain decoding technique combined with deep neural network (DNN) representations to reconstruct illusory percepts as images from brain activity.

Functional Diversity of Dopamine Axons in Prefrontal Cortex During Classical Conditioning.

Midbrain dopamine neurons impact neural processing in the prefrontal cortex (PFC) through mesocortical projections. However, the signals conveyed by dopamine projections to the PFC remain unclear, particularly at the single-axon level. Here, we investigated dopaminergic axonal activity in the medial PFC (mPFC) during reward and aversive processing.

Efficacy of exponentiation method with a convolutional neural network for classifying lung nodules on CT images by malignancy level.

Objectives: The aim of this study was to examine the performance of a convolutional neural network (CNN) combined with exponentiating each pixel value in classifying benign and malignant lung nodules on computed tomography (CT) images.

Materials And Methods: Images in the Lung Image Database Consortium-Image Database Resource Initiative (LIDC-IDRI) were analyzed. Four CNN models were then constructed to classify the lung nodules by malignancy level (malignancy level 1 vs.

Inter-individual deep image reconstruction via hierarchical neural code conversion.

The sensory cortex is characterized by general organizational principles such as topography and hierarchy. However, measured brain activity given identical input exhibits substantially different patterns across individuals. Although anatomical and functional alignment methods have been proposed in functional magnetic resonance imaging (fMRI) studies, it remains unclear whether and how hierarchical and fine-grained representations can be converted between individuals while preserving the encoded perceptual content.

Decoding distributed oscillatory signals driven by memory and perception in the prefrontal cortex.

Sensory perception and memory recall generate different conscious experiences. Although externally and internally driven neural activities signifying the same perceptual content overlap in the sensory cortex, their distribution in the prefrontal cortex (PFC), an area implicated in both perception and memory, remains elusive. Here, we test whether the local spatial configurations and frequencies of neural oscillations driven by perception and memory recall overlap in the macaque PFC using high-density electrocorticography and multivariate pattern analysis.

Brain hierarchy score: Which deep neural networks are hierarchically brain-like?

Achievement of human-level image recognition by deep neural networks (DNNs) has spurred interest in whether and how DNNs are brain-like. Both DNNs and the visual cortex perform hierarchical processing, and correspondence has been shown between hierarchical visual areas and DNN layers in representing visual features. Here, we propose the brain hierarchy (BH) score as a metric to quantify the degree of hierarchical correspondence based on neural decoding and encoding analyses where DNN unit activations and human brain activity are predicted from each other.

Longer withdrawal time is not associated with increased patient discomfort in colonoscopy: a retrospective observational study.

Purpose: Withdrawal time of sufficient length is a quality indicator for colonoscopies. Nonetheless, whether extending the withdrawal time contributes to patient discomfort remains unknown. This study aimed to clarify the relationship between colonoscopy withdrawal time and patient discomfort.

Recent trends in the prevalence and distribution of colonic diverticula in Japan evaluated using computed tomography colonography.

Background: Computed tomography colonography (CTC) may be superior to colonoscopy and barium enema for detecting diverticula. However, few studies have used CTC to diagnose diverticula.

Aim: To evaluate the current prevalence and distribution of colonic diverticula in Japan using CTC.

Diastereoselective Synthesis of a -1,3-Disubstituted Cyclobutane Carboxylic Acid Scaffold for TAK-828F, a Potent Retinoic Acid Receptor-Related Orphan Receptor (ROR)-γt Inverse Agonist.

A scalable synthesis of the -1,3-disubstituted cyclobutane carboxylic acid scaffold of TAK-828F () has been developed, featuring the diastereoselective reduction of a cyclobutylidene Meldrum's acid derivative with NaBH. Controlling acidic impurities was crucial for improving the diastereomeric ratio by recrystallization. Furthermore, reaction optimization and the streamlining of several steps established a scalable synthetic method free from column chromatography purification with an overall yield improved from 23 to 39%.

Quantum-inspired canonical correlation analysis for exponentially large dimensional data.

Canonical correlation analysis (CCA) serves to identify statistical dependencies between pairs of multivariate data. However, its application to high-dimensional data is limited due to considerable computational complexity. As an alternative to the conventional CCA approach that requires polynomial computational time, we propose an algorithm that approximates CCA using quantum-inspired computations with computational time proportional to the logarithm of the input dimensionality.

Inverse time trends of peptic ulcer and reflux esophagitis show significant association with reduced prevalence of infection.

Introduction: Recent prevalence and trends of gastric/duodenal ulcer (GU/DU) and reflux esophagitis (RE) are inadequate.

Methods: We reviewed the records of consecutive 211,347 general population subjects from 1991 to 2015.

Results: During the 25 years, the prevalence of GU and DU has gradually decreased (from 3.

The Reconstruction after a Giant Phyllodes Tumor Resection Using a DIEP Flap.

A phyllodes tumor of the breast is a rare neoplasm, accounting for 0.3%-1% of all breast cancers. The size is 4-5 cm on average but sometimes the tumor grows more and involves the entire breast.