Márton Rózsa

This study uses biologically realistic simulations to show that cortical circuit stability and information integration increase with hierarchy, linked to increased connectivity and SST cell proportion.

This study evaluates and optimizes spike inference methods for GCaMP8 calcium imaging data, showing improved detection of high-frequency spikes and real-time activity.

This study shows how rapid learning in mice involves structured changes in motor cortex connectivity, rerouting preparatory activity to control a conditioned neuron.

The paper maps functional connectivity in the motor cortex of mice during naturalistic reward-seeking behavior, revealing columnar architecture and hub neurons that influence neighboring cells.

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

The paper reports spontaneously occurring retroaxonal action potentials in interneurons that are independent of network inputs, showing distinct temporal contributions to network activity compared to AIS-APs.

The paper develops fast and sensitive GCaMP indicators for neural activity imaging, achieving ultra-fast kinetics and high sensitivity.

SUPPORT is a self-supervised method that denoises voltage imaging data by leveraging spatiotemporal dependencies, preserving dynamics without requiring action potential information.

This paper introduces a method to accurately estimate spikes and subthreshold waveforms from 1-photon voltage imaging in vivo, even with noise.

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