# Biological Basis of the Code The provided code models the stimulation of axons within a nerve structure and analyzes the resultant neural activity. This involves simulating the responses of nerve fibers to electrical stimulation, which is critical in understanding nerve function, designing neural prosthetics, or studying neurophysiological mechanisms. ## Key Biological Components ### Axons and Action Potentials (APs) - **Axons** are the long, thread-like part of a nerve cell along which impulses are conducted from the cell body to other cells. The code reads and processes axon-related data stored as csv files, presumably containing voltage recordings from simulated axons. - **Action Potentials (APs)** are spikes of electrical activity that represent signals traveling along the axon. The code calculates AP peak times and latencies, analyzing when and if the simulated axons fire action potentials during stimulation. ### Electrical Stimulation - The code processes data related to electrical **stimulation protocols**, a common method to evoke action potentials in neurons and study their responses. The current involved in these stimulation protocols is extracted from settings files and associated with the resultant recruitment of APs. - The threshold for identifying APs is set at a specific voltage (vcrit = 15 mV), which is biologically significant as it represents the typical threshold that needs to be exceeded for depolarization and the subsequent initiation of an action potential. ### Nerve and Fascicular Structure - The structure being simulated is a nerve, which contains multiple **fascicles**, or bundles of axonal fibers. The code maintains data about the geometric properties of these axons (such as their spatial coordinates). - The analysis involves determining which axons within specific fascicles have fired in response to the stimulation, reflecting the spatial recruitment of nerve fibers. ### Geometric and Topological Representation - The code includes functionality for loading and utilizing the **geometry** of the axons, fascicles, and nerve contours from external files. This involves reading a JSON file containing the topology of the nerve internals and CSV files for nerve contours, allowing the spatial representation of nerve architecture. - This spatial information is crucial for simulating realistic neural structures where different fascicles might have distinct responses to stimuli due to their geometrical and spatial properties. ### Objective of Analysis - The processing results contribute to understanding the **recruitment** of axons during electrical stimulation, which can be used to infer properties like nerve conduction velocity or sensitivity to stimulation across different fascicles. - The results are stored in a structured format (JSON), indicating an emphasis on aggregating data regarding the number of axons firing, which can offer insights into the effectiveness of stimulation protocols in different parts of the nerve. In summary, the code models a nerve's response to electrical stimulation by analyzing axon activations and recruitment patterns, facilitating a deeper understanding of neural excitability and connectivity within biological tissues.