Neural network simulation with hyperploid neurons

This data set comprises Comma Separated Values (.CSV) files containing the results of the simulated spiking neuronal network, MATLAB variable files (.MAT) and PNG figure files. All data was obtained by the Brian2 neural network simulator. CSV file can be visualized by any text editor. MATLAB files require MATLAB or Octave. We’ve created a neuronal network composed of 4,000 neurons of three types, with different proportion of hyperploid neurons – namely, condition (from 1% to 80%) - in each of these types: (i) excitatory neurons (EXC); (ii) leading neurons (LEAD), a subtype of excitatory neurons that constitute relevant hubs of the circuit; and (iii) interneurons, with inhibitory capacity (INH). Control networks (CONTROL) did not contain hyperploid neurons. Five repetitions of each condition were simulated. All data is organized hierarchically regarding condition and repetition, and experimental folder names contains date of creation (October 2018). Estibaliz Barrio-Alonso and Manuel Valero coded the simulation and the analysis scripts. All simulations were performed under a Windows 10 machine, with Python 2.7 and MATLAB R2018a.