[en] Description
This dataset contains large-scale spike-train recordings generated from conductance-based neuron models, including the stomatogastric ganglion (STG) neuron and a midbrain dopamine (DA) neuron model. Conductance parameters were sampled using both Monte Carlo and Dynamic Input Conductances (DICs) - constrained strategies to produce physiologically degenerate neuronal populations. Simulations were performed in parallel with optional noisy current injection, and outputs are provided as spike times (CSV) rather than full voltage traces to enable efficient downstream analysis and model inference. The dataset is intended for research in computational neuroscience, neural modeling, degeneracy analysis, and spike-based machine learning.
Disciplines :
Engineering, computing & technology: Multidisciplinary, general & others
Author, co-author :
Brandoit, Julien ; Université de Liège - ULiège > Montefiore Institute of Electrical Engineering and Computer Science
Language :
English
Title :
Spike-Train Datasets from Conductance-Based Neuron Models
