Stanislav Jiříček

This study examines how behavioural activity affects EEG power spectrum, source localization, and global functional connectivity in freely moving rats, identifying specific frequency band changes.

This study identifies cortical cell-type and receptor gradients that correlate with resting-state alpha-BOLD coupling patterns.

This study detects and characterizes microstates in rat EEG, showing they can be captured using human-like metrics and identifying their frequency bands and sources.

This study uses fMRI and EEG to distinguish internally and externally oriented spontaneous thoughts during rest, finding distinct neural patterns in brain networks and alpha power.

This study uses a mathematical model of cortical microcircuits to show that input variability affects EEG-BOLD correlations, revealing negative alpha-BOLD and positive gamma-BOLD relationships.

This paper compares EEG and fMRI data using spatio-spectral decomposition, finding that EEG patterns show weak but significant spatial similarity to fMRI BOLD signatures, with complementary information.

The paper quantifies non-linear brain connectivity across modalities and scales, finding that non-linear interactions are more prominent in microscale recordings than in non-invasive, large-scale modalities.