Kazuyuki Aihara

Dynamical Biomarkers of Creative Cognition Across Divergent and Convergent Problem-Solving

This paper identifies dynamical biomarkers of creative cognition using EEG data from problem-solving tasks, showing that creative success is linked to specific patterns of neural state traversal.

Controlling Integration and Segregation in Echo State Networks via Noradrenaline and Acetylcholine Neuromodulation

This paper introduces a modular echo state network with neuromodulation to control integration and segregation, showing improved performance on context-dependent tasks.

BrainBeacon: A Cross-Species Foundation Model for Single-cell Resolved Brain Spatial Transcriptomics

BrainBeacon is a cross-species foundation model for whole-brain spatial transcriptomics that enables cross-species alignment and uncovers spatial regulatory mechanisms of aging.

Longitudinal analysis of antibody titers after primary and booster mRNA COVID-19 vaccination can identify individuals at risk for breakthrough infection

The paper analyzes longitudinal antibody titers post-vaccination to identify individuals at risk for breakthrough infections and identifies three population groups with distinct immune response patterns.

Steering cell-state and phenotype transitions by causal disentanglement learning

CauFinder identifies and steers cell-state and phenotype transitions by causal disentanglement learning, outperforming existing methods in simulated and real-world scenarios.

STAMarker: Determining spatial domain-specific variable genes with saliency maps in deep learning

STAMarker identifies spatial domain-specific variable genes using saliency maps in deep learning, outperforming existing methods on sparse spatial transcriptomic data.

Early Dynamics of Chronic Myeloid Leukemia on Nilotinib Predicts Deep Molecular Response

This paper develops a mathematical model using early clinical data to predict deep molecular response in CML patients treated with nilotinib.

Electrical coupling controls dimensionality and chaotic firing of inferior olive neurons

This study models how electrical coupling between inferior olive neurons affects firing dimensionality and chaos, supporting the hypothesis that coupling controls learning efficiency in the cerebellum.

Task-dependent recurrent dynamics in visual cortex

The paper shows that task-dependent attractor dynamics in visual cortex enhance task-relevant information for perceptual decisions.

Personalized characterization of diseases using sample-specific networks

This paper introduces a sample-specific network method to construct individual-specific disease networks from single-sample expression data, identifying disease modules and driver genes without sequencing.