Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.10.12.335901v1?rss=1 Authors: Herzog, R., Morales, A., Mora, S., Araya, J., Escobar, M.-J., Palacios, A. G., Cofre, R. Abstract: We propose a novel, scalable, and accurate automated method for detecting neuronal ensembles from a population of spiking neurons. Our approach offers a simple yet powerful tool to study ensemble activity. It allows the participation of neurons in different ensembles, has few parameters to tune and is computationally efficient. We used spike trains of retinal ganglion cells obtained from multi-electrode array recordings under a simple ON-OFF light stimulus to test our method. We found a consistent stimuli-evoked ensemble activity intermingled with spontaneously active ensembles and irregular activity. Our results suggest that the early visual system activity is already organized in clearly distinguishable functional ensembles. To validate the performance and generality of our method, we generated synthetic data, where we found that our method accurately detects neuronal ensembles for a wide range of simulation parameters. Additionally, we found that our method outperforms current alternative methodologies. Finally, we provide a Graphic User Interface, which aims to facilitate our method's use by the scientific community. Copy rights belong to original authors. Visit the link for more info