Merve Kaptan

This study uses simultaneous spinal cord-brain fMRI to show how nociceptive stimuli and pain perception are encoded in corticospinal networks, with spinal cord activity primarily reflecting stimulus temperature.

This study uses ultra-high-field fMRI to reveal layer-specific responses in the human spinal cord during heat-pain stimulation, identifying phasic and tonic response components in dorsal horn layers.

The paper introduces EPISeg, a deep learning model for automated spinal cord segmentation on gradient-echo EPI data, showing improved performance over existing methods.

This study uses simultaneous brain-spinal cord fMRI to map neural activity related to hand strength and dexterity, revealing graded activation and inhibition patterns across motor and sensory regions.

This paper develops a multi-channel electrophysiology method to non-invasively record human spinal cord activity with high temporal resolution and demonstrates its application in studying somatosensation and nociception.

This study evaluates the reliability of task-based fMRI in the human spinal cord, finding poor reliability of BOLD responses across days but good reliability of autonomic responses.

This study assesses the reliability of resting-state functional connectivity in the human spinal cord, finding reliable connectivity between dorsal and ventral horns but poor reliability in segmental and within-hemicord connections.

This paper develops automated methods for slice-specific z-shimming in spinal cord fMRI to improve signal quality and reproducibility.