Masaki Takeda

This study uses a 3D deep neural network to decode real-world object size from fMRI data, revealing a distributed neural network for subtle size differences beyond traditional visual areas.

This paper challenges the standard model of memory consolidation by showing persistent hippocampal engagement and brain-wide network reorganization during remote memory retrieval.

This study identifies neural dynamics associated with human psychological resilience after acute stress exposure using multimodal neuroimaging and physiological data.

This study examines the asynchronous recovery of brain activity after awakening from deep NREM sleep, finding that frontal regions recover faster than posterior regions.

This study investigates how perceptual uncertainty affects response inhibition by analyzing brain activity in specific regions during a go/no-go task.

This study uses fMRI and EEG with deep neural networks to show how visual objects are represented in the brain through spatially organized and temporally sequential patterns.

This study identifies a cross-hemispheric excitatory-inhibitory loop between the prefrontal cortex and cerebellum that resolves the Stroop effect by regulating interference between language and color information.

This study examines decision-making in a multifactor gambling task, finding that fronto-parietal cognitive control influences reaction times and strategy switching in complex value-based decisions.

The paper shows that reversible fronto-occipitotemporal signaling supports task encoding and behavioral flexibility under ambiguous cues by alternating top-down and bottom-up signals.