Data associated with the publication: The cellular architecture of memory modules in Drosophila supports stochastic input integration

Article abstract: The ability to associate neutral stimuli with valence information and to store these associations as memories forms the basis for decision making. To determine the underlying computational principles, we build a realistic computational model of a central decision module within the Drosophila mushroom body (MB), the fly’s center for learning and memory. Our model combines the electron microscopy-based architecture of one MB output neuron (MBON-alpha 3), the synaptic connectivity of its 948 presynaptic Kenyon cells (KCs), and its in vivo membrane properties obtained from patch-clamp recordings. We show that this neuron is electrotonically compact and that synaptic input corresponding to simulated odor input robustly drives its spiking behavior. Therefore, sparse innervation by KCs can efficiently control and modulate MBON activity in response to learning with minimal requirements on the specificity of synaptic localization. This architecture allows efficient storage of large numbers of memories using the flexible stochastic connectivity of the circuit. The data-set contains the coding environment and scripts for running the computational model, experimental data for model fitting and all resulting data from computational simulations related to the above mentioned manuscript. The Fitting.zip file stores the resulting trace from fitting the model in tabular form. The Raw Experimental Traces for Fitting.zip file stores the experimental traces that were used for model fitting in tabular form. One .csv file per cell with the 35 traces and the corresponding time. The Simulation_Code.zip file contains the coding environment, simulation scripts and vector data for synapses and model as .py, .swc and .json files. The thirteen Simulation .zip files store all the raw data in a folder resulting from one specific simulation (.dat and .csv files) in tabular form . A subfolder contains .tif, .pdf, .ps files, for the visualization of the plotted data and in some cases example images of activated regions in the dendritic tree of the neuron. For example: Simulation 1 - 1 KC Synapses.zip includes all the data resulting from simulated successive activation of each individual KC. Each trial involved the activation of 10 synapses per KC. amp_PN/soma.dat contains the resulting amplitude of changes in membrane potential at the proximal neurite/soma in mV. num_alphas.csv contains a matrix of the number of activated synapses per trial. PN/soma_voltage.csv contains the resulting changes in membrane potential at the proximal neurite/soma over time in mV. synapse_sites.csv contains the specified numbers of each activated synaptic site during the trial. time.csv contains the time axis for each trial in ms. The subfolder Sim1_Figs contains .pdf and .ps of two example images of the activated synapses from trial 1 and trial 948. Other folders also contain files with plots of the corresponding data. (2022-02)