Illusory Oscillation of the Central Rotation Axis.

In this study, we report a novel visual illusion for rotational motion, in which the central rotation axis of a partially invisible (apparent) square is perceived as exhibiting oscillatory rotation. To investigate the cause of this illusion, we measured the central position of a static apparent shape using an adjustment method (Experiment 1) and manipulated the speed of the rotating apparent square to test whether the illusion could be cancelled out by counteracting rotation using a constant method (Experiment 2). The results revealed that the perceived central position of a static apparent shape was shifted toward the outside.

A border-ownership model based on computational electromagnetism.

The mathematical relation between a vector electric field and its corresponding scalar potential field is useful to formulate computational problems of lower/middle-order visual processing, specifically related to the assignment of borders to the side of the object: so-called border ownership (BO). BO coding is a key process for extracting the objects from the background, allowing one to organize a cluttered scene. We propose that the problem is solvable simultaneously by application of a theorem of electromagnetism, i.

Computational study of depth completion consistent with human bi-stable perception for ambiguous figures.

We propose a computational model that is consistent with human perception of depth in "ambiguous regions," in which no binocular disparity exists. Results obtained from our model reveal a new characteristic of depth perception. Random dot stereograms (RDS) are often used as examples because RDS provides sufficient disparity for depth calculation.

Reprint of: Simulation Platform: a cloud-based online simulation environment.

For multi-scale and multi-modal neural modeling, it is needed to handle multiple neural models described at different levels seamlessly. Database technology will become more important for these studies, specifically for downloading and handling the neural models seamlessly and effortlessly. To date, conventional neuroinformatics databases have solely been designed to archive model files, but the databases should provide a chance for users to validate the models before downloading them.

Simulation Platform: a cloud-based online simulation environment.

For multi-scale and multi-modal neural modeling, it is needed to handle multiple neural models described at different levels seamlessly. Database technology will become more important for these studies, specifically for downloading and handling the neural models seamlessly and effortlessly. To date, conventional neuroinformatics databases have solely been designed to archive model files, but the databases should provide a chance for users to validate the models before downloading them.

Super resolution: another computational role of short-range horizontal connection in the primary visual cortex.

Recent physiological data related to the primary visual cortex (V1) have shown various contextual effects in the non-classical receptive field (nCRF). Contextual modulation, size tuning and altered sensitivity of orientation are typical examples of such contextual effects in the nCRF. These phenomena in the nCRF have been thought to be caused by short-range horizontal connection (SHC).

Engineering-approach accelerates computational understanding of V1-V2 neural properties.

We present two computational models (i) long-range horizontal connections and the nonlinear effect in V1 and (ii) the filling-in process at the blind spot. Both models are obtained deductively from standard regularization theory to show that physiological evidence of V1 and V2 neural properties is essential for efficient image processing. We stress that the engineering approach should be imported to understand visual systems computationally, even though this approach usually ignores physiological evidence and the target is neither neurons nor the brain.

Computational theory and applications of a filling-in process at the blind spot.

A mathematical model for filling-in at the blind spot is proposed. The general scheme of the standard regularization theory was used to derive the model deductively. First, we present the problems encountered with a diffusion equation, which is frequently used for various types of perceptual completion.

A visual model for object detection based on active contours and level-set method.

A visual model for object detection is proposed. In order to make the detection ability comparable with existing technical methods for object detection, an evolution equation of neurons in the model is derived from the computational principle of active contours. The hierarchical structure of the model emerges naturally from the evolution equation.