María-José Escobar

The paper introduces an automated method for detecting neuronal ensembles in spiking neural networks, showing it accurately identifies ensembles in both real and synthetic data.

This paper uses a thalamocortical computational model to identify optimal auditory stimulation parameters for enhancing slow-wave sleep events like slow oscillations and spindles.

The paper studies how retinal neuronal ensembles process natural images by analyzing their synchronized activity in response to visual stimuli.

The paper shows that retinal ganglion cells adjust their response to complex naturalistic stimuli more efficiently than to simple artificial ones, suggesting the retina encodes motion information more effectively with complex stimuli.

This paper introduces a dimensionality reduction framework for spatio-temporal maximum entropy models of spiking networks, showing significant reduction in retinal data.

This study identifies functional differences between central and peripheral retinal ganglion cells in diurnal rodents, showing distinct receptive field sizes, response dynamics, and temporal sensitivity.