Kenshu Koiso

The paper tests a two-stage model of perceptual filling-in by examining how early visual cortex properties like the oblique effect and surround suppression influence the phenomenon.

This study investigates perceptual filling-in in human V1 using fMRI, finding that deep cortical layers show neural correlates associated with feedback input during the phenomenon.

This paper introduces a fast whole-brain MRI protocol for mesoscopic venous imaging in humans, enabling detailed vascular mapping in under seven minutes without contrast agents.

This study investigates how eccentricity and movement of visual stimuli affect perceptual filling-in by measuring neural adaptation in early visual areas.

This study uses VASO 7T layer fMRI and MVPA to show that face information is structured in the middle layer of the fusiform face area during face processing.

This study shows that rapid neural information can be decoded from ultra-fast fMRI signals using multivariate pattern decoders, achieving significant accuracy within 2 seconds of stimulus onset.

This paper identifies and mitigates Fuzzy Ripple artifacts in high-resolution fMRI, enabling sub-millimeter resolution and faster acquisition protocols.

The paper develops acquisition protocols and processing pipelines for whole-brain layer-fMRI and introduces the Kenshu dataset for benchmarking and analysis.