Attila Ozsvár

The paper identifies a molecular marker, NDNF, to selectively target neurogliaform neurons in the mouse basolateral amygdala using a combination of genetic and electrophysiological methods.

This study identifies that glioblastoma cells in the tumor's invasive leading edge exhibit electrophysiological properties similar to neurons, including action potentials, and show reduced proliferation signaling.

The paper identifies transcriptomic and morpho-electric diversity in human neocortical layer 1 interneurons, revealing greater subclass distinction compared to mouse.

The paper uses viral labeling and Patch-seq to define morpho-electric properties of GABAergic interneurons in human neocortex, revealing functional insights and reclassifying some SST neurons into PVALB subclass.

The paper shows that metabotropic GABAB responses sum linearly while ionotropic GABAA responses sum sublinearly in neurogliaform interneurons.

The paper develops an automated patch clamp system using deep learning and image analysis to measure neurons in human and rodent brain slices.

The paper identifies transcriptomic diversity in human supragranular neurons and links it to functional specialization and disease vulnerability.

The paper identifies a novel human cortical GABAergic interneuron subtype with unique transcriptomic, morphological, and physiological features not observed in rodents.