Takaki Komiyama

The paper identifies cell-type-specific activity dynamics in striatal neurons during movement by analyzing cortical and thalamic inputs in mice.

The paper shows optogenetic activation of VIP-INs in HD mice restores motor function by normalizing activity in VIP-INs and CSPNs.

The paper shows that stimulating specific M1 neurons in mice can induce learned movements and activity patterns, supporting M1's active role in motor learning.

This study shows that cholinergic feedback axons in the olfactory bulb shift their activity from movement-correlated to odor-aligned responses during odor discrimination tasks in mice, enhancing task performance.

The paper develops high-density transparent graphene electrodes to record neural activity from deeper cortical layers and decodes calcium activity from surface potentials using dimensionality reduction and neural networks.

This study examines how functional connectomes in the motor cortex of mice rewire during motor skill learning, revealing a biphasic pattern of connectivity changes that optimize performance and maintain network density.

PatchWarp corrects non-uniform image distortions in two-photon calcium imaging data using patchwork affine transformations, improving accuracy over existing methods.

FARCI infers neuronal connectomes from two-photon calcium imaging data, showing accuracy and efficiency across network sizes and noise levels.

This study decodes large-scale cortical activity from local surface potentials using a recurrent neural network, showing that surface potentials contain rich information about neural activity across multiple regions.