Junji Ito

The paper introduces a quality measure for spatio-temporal spike patterns in multiple-neuron recordings to distinguish meaningful pattern repetitions from chance occurrences.

The paper identifies and removes hyper-synchronous artifacts in electrophysiological recordings using zero-phase component analysis.

This study shows that preprocessing steps in electrophysiological data can significantly affect spike correlation analysis results and proposes a correction method.

This study identifies two distinct neural manifolds in V1 correlated with eye state and shows top-down signals from V4 to V1, particularly in the foveal region, during eyes-open periods.

The paper analyzes resting state spiking activity in monkey motor cortex, finding higher dimensionality, lower firing rates, and less excitation-inhibition balance compared to task-related states.