349 citations · 427 across the 5 of their papers we have counts for
5 papers
Optimization and Validation of Diffusion MRI-based Fiber Tracking with Neural Tracer Data as a Reference
Carlos Enrique Gutierrez, Henrik Skibbe, Ken Nakae +11
Diffusion-weighted magnetic resonance imaging (dMRI) allows non-invasive investigation of whole-brain connectivity, which can potentially help to reveal the brain's global network…
MarmoNet: a pipeline for automated projection mapping of the common marmoset brain from whole-brain serial two-photon tomography
Henrik Skibbe, Akiya Watakabe, Ken Nakae +10
Understanding the connectivity in the brain is an important prerequisite for understanding how the brain processes information. In the Brain/MINDS project, a connectivity study on…
Distributional Smoothing with Virtual Adversarial Training
Takeru Miyato, Shin-ichi Maeda, Masanori Koyama +2
We propose local distributional smoothness (LDS), a new notion of smoothness for statistical model that can be used as a regularization term to promote the smoothness of the model…
Deep learning of fMRI big data: a novel approach to subject-transfer decoding
Sotetsu Koyamada, Yumi Shikauchi, Ken Nakae +2
As a technology to read brain states from measurable brain activities, brain decoding are widely applied in industries and medical sciences. In spite of high demands in these appli…
Principal Sensitivity Analysis
Sotetsu Koyamada, Masanori Koyama, Ken Nakae +1
We present a novel algorithm (Principal Sensitivity Analysis; PSA) to analyze the knowledge of the classifier obtained from supervised machine learning techniques. In particular, w…