The provided code represents a simulation for assessing basic firing statistics of simulated neurons, focusing on medium spiny neurons (MSNs) and fast-spiking interneurons (FSIs) within the basal ganglia, specifically the striatum, which is a critical component linked to motor control, learning, and many aspects of cognition. ### Biological Context #### Medium Spiny Neurons (MSNs) MSNs are the predominant type of neurons found in the striatum, constituting about 95% of its neuronal population. They are GABAergic neurons, meaning they release the inhibitory neurotransmitter gamma-aminobutyric acid. MSNs can be further classified based on their dopamine receptor type into D1 and D2 receptor-expressing neurons, each associated with separate signaling pathways. The firing patterns and rates of MSNs significantly influence motor control and are affected by dopaminergic inputs, relevant to diseases such as Parkinson's. #### Fast-Spiking Interneurons (FSIs) FSIs are a smaller population within the striatum and are crucial for modulating the activity of MSNs. They have distinct electrical properties characterized by fast-spiking action potentials and play a critical role in synchronizing network activity. Through inhibitory connections, FSIs can influence the firing patterns of MSNs, thereby impacting the overall output of the basal ganglia circuit. ### Model Objectives The code is essentially focusing on three elements of neuron firing behavior: 1. **Firing Rate**: The model calculates the firing rates of MSNs and FSIs. Understanding firing rates is vital because they correlate with the neural activity status and signal processing within the brain. 2. **Inter-Spike Interval (ISI) and its Coefficient of Variation (CV)**: The ISI is the time interval between consecutive spikes. The CV of the ISI, which is computed here, helps evaluate the regularity of the neuron's firing pattern. It provides insights into the stochastic nature of the neuronal firing. Lower CVs indicate more regular and rhythmic firing, while higher CVs suggest irregular activity. 3. **Empirical Cumulative Distribution Function (ECDF)**: The ECDFs for firing rates and ISI CVs are plotted to understand the statistical distribution of these firing behaviors across the neuronal population. ### Key Highlights in the Code - The simulation focuses on network parameters that define the number of MSNs and FSIs, as indicated by `SIMPARAMS.net.MS.N` and `SIMPARAMS.net.FS.N`. - Spiking data (`out.STms` for MSNs and `out.STfs` for FSIs) are analyzed to calculate firing statistics. - The ISI CV is calculated for each neuron, giving a measure of firing regularity. - Data visualization is performed through histograms and ECDF plots, providing visual insight into the variance and distribution of neuronal activity. Through this simulation, researchers can derive meaningful insights into the basal ganglia's role in motor control and diseases that affect this brain region, such as Parkinson's disease, Huntington's disease, and Tourette's syndrome.