Temporal and spatial analysis of event-related potentials in response to color saliency differences among various color vision types.

Introduction: Human color vision exhibits significant diversity that cannot be fully explained by categorical classifications. Understanding how individuals with different color vision phenotypes perceive, recognize, and react to the same physical stimuli provides valuable insights into sensory characteristics. This study aimed to identify behavioral and neural differences between different color visions, primarily classified as typical trichromats and anomalous trichromats, in response to two chromatic stimuli, blue-green and red, during an attention-demanding oddball task.

Probing the link between vision and language in material perception using psychophysics and unsupervised learning.

We can visually discriminate and recognize a wide range of materials. Meanwhile, we use language to describe what we see and communicate relevant information about the materials. Here, we investigate the relationship between visual judgment and language expression to understand how visual features relate to semantic representations in human cognition.

Stick to your role! Stability of personal values expressed in large language models.

The standard way to study Large Language Models (LLMs) through benchmarks or psychology questionnaires is to provide many different queries from similar minimal contexts (e.g. multiple choice questions).

Decoding time-resolved neural representations of orientation ensemble perception.

The visual system can compute summary statistics of several visual elements at a glance. Numerous studies have shown that an ensemble of different visual features can be perceived over 50-200 ms; however, the time point at which the visual system forms an accurate ensemble representation associated with an individual's perception remains unclear. This is mainly because most previous studies have not fully addressed time-resolved neural representations that occur during ensemble perception, particularly lacking quantification of the representational strength of ensembles and their correlation with behavior.

Probing the Link Between Vision and Language in Material Perception Using Psychophysics and Unsupervised Learning.

We can visually discriminate and recognize a wide range of materials. Meanwhile, we use language to express our subjective understanding of visual input and communicate relevant information about the materials. Here, we investigate the relationship between visual judgment and language expression in material perception to understand how visual features relate to semantic representations.

Unsupervised learning reveals interpretable latent representations for translucency perception.

Humans constantly assess the appearance of materials to plan actions, such as stepping on icy roads without slipping. Visual inference of materials is important but challenging because a given material can appear dramatically different in various scenes. This problem especially stands out for translucent materials, whose appearance strongly depends on lighting, geometry, and viewpoint.

An Open-Source Cognitive Test Battery to Assess Human Attention and Memory.

Cognitive test batteries are widely used in diverse research fields, such as cognitive training, cognitive disorder assessment, or brain mechanism understanding. Although they need flexibility according to their usage objectives, most test batteries are not available as open-source software and are not be tuned by researchers in detail. The present study introduces an open-source cognitive test battery to assess attention and memory, using a javascript library, p5.

Visual discrimination of optical material properties: A large-scale study.

Complex visual processing involved in perceiving the object materials can be better elucidated by taking a variety of research approaches. Sharing stimulus and response data is an effective strategy to make the results of different studies directly comparable and can assist researchers with different backgrounds to jump into the field. Here, we constructed a database containing several sets of material images annotated with visual discrimination performance.

Crystal or jelly? Effect of color on the perception of translucent materials with photographs of real-world objects.

Translucent materials are ubiquitous in nature (e.g. teeth, food, and wax), but our understanding of translucency perception is limited.

The roles of lower- and higher-order surface statistics in tactile texture perception.

Humans can haptically discriminate surface textures when there is a significant difference in the statistics of the surface profile. Previous studies on tactile texture discrimination have emphasized the perceptual effects of lower-order statistical features such as carving depth, inter-ridge distance, and anisotropy, which can be characterized by local amplitude spectra or spatial-frequency/orientation subband histograms. However, the real-world surfaces we encounter in everyday life also differ in the higher-order statistics, such as statistics about correlations of nearby spatial-frequencies/orientations.

Discounting mechanism underlies extinction illusion.

Humans can perceive a coherent visual scene despite a low spatial resolution in peripheral vision. How does the visual system determine whether an object exists in the periphery? We addressed this question by focusing on the extinction illusion in which a disk becomes subjectively invisible when presented at the intersection of grids. We hypothesized that the disk would go unnoticed when the stimuli with and without the disk produced the same strength of visual signals.

A Computational Mechanism for Seeing Dynamic Deformation.

Human observers perceptually discriminate the dynamic deformation of materials in the real world. However, the psychophysical and neural mechanisms responsible for the perception of dynamic deformation have not been fully elucidated. By using a deforming bar as the stimulus, we showed that the spatial frequency of deformation was a critical determinant of deformation perception.

Motion Perception: From Detection to Interpretation.

Visual motion processing can be conceptually divided into two levels. In the lower level, local motion signals are detected by spatiotemporal-frequency-selective sensors and then integrated into a motion vector flow. Although the model based on V1-MT physiology provides a good computational framework for this level of processing, it needs to be updated to fully explain psychophysical findings about motion perception, including complex motion signal interactions in the spatiotemporal-frequency and space domains.

Material and shape perception based on two types of intensity gradient information.

Visual estimation of the material and shape of an object from a single image includes a hard ill-posed computational problem. However, in our daily life we feel we can estimate both reasonably well. The neural computation underlying this ability remains poorly understood.

Visual wetness perception based on image color statistics.

Color vision provides humans and animals with the abilities to discriminate colors based on the wavelength composition of light and to determine the location and identity of objects of interest in cluttered scenes (e.g., ripe fruit among foliage).

Human perception of subresolution fineness of dense textures based on image intensity statistics.

We are surrounded by many textures with fine dense structures, such as human hair and fabrics, whose individual elements are often finer than the spatial resolution limit of the visual system or that of a digitized image. Here we show that human observers have an ability to visually estimate subresolution fineness of those textures. We carried out a psychophysical experiment to show that observers could correctly discriminate differences in the fineness of hair-like dense line textures even when the thinnest line element was much finer than the resolution limit of the eye or that of the display.

Stain on texture: perception of a dark spot having a blurred edge on textured backgrounds.

When distinguishing illumination from reflectance edges, both edge blurriness and textural continuity across an edge are generally used as cues to promote the illumination-edge interpretation. However, when these cues were combined, i.e.

Spatial organization affects lightness perception on articulated surrounds.

The articulation effect refers to a change in lightness contrast induced by adding small patches of different luminances to a uniform background surrounding a target in a lightness contrast display. This study investigated how local luminance signals are integrated to generate the articulation effect. We asked whether spatial organization due to perceptual grouping can influence the articulation effect even when the spatially averaged luminance of the surrounds is held constant.

Local computation of lightness on articulated surrounds.

Lightness of a grey target on a uniform light (or dark) surround changes by articulating the surround (articulation effect). To elucidate the processing of lightness underlying the articulation effect, the present study introduced transparency over a dark surround and investigated its effects on lightness of the target. The transparency was produced by adding a contiguous external field to the dark surround while keeping local stimulus configuration constant.