Alexander Kleinjohann

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

The paper shows that spontaneous spiking statistics uniquely identify cortical areas and correlate with their hierarchical position in the cerebral cortex.

UnitRefine automates spike sorting curation using machine learning models trained on expert annotations, achieving human-level performance across species and datasets.

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 models spatio-temporal spike patterns in monkey motor cortex using synfire chains and finds that overlapping chains with broad spatial distribution can explain the observed patterns.