The code provided simulates and visualizes aspects of neural recruitment, likely within a peripheral nerve system, where electrical stimulation is applied to assess its effects on nerve and fascicle activation. Here's a breakdown of the biological basis of this code: ### Biological Concepts 1. **Neural Recruitment:** - The code models "recruitment," which refers to the activation of nerve fibers (axons) in response to electrical stimulation. - Recruitment is quantified in absolute terms (number of axons) and fractional terms (proportion of axons relative to the total within a nerve or fascicle). 2. **Nerve and Fascicles:** - A "nerve" is modeled alongside multiple smaller subdivisions referred to as "fascicles." Each fascicle represents a bundle of axons within the larger nerve structure. - The code refers to seven fascicles (`Fascicle_00` to `Fascicle_06`), each with differing numbers of axons. 3. **Electrical Stimulation:** - The variable `currents` represents the intensity or amplitude of electrical stimulation applied to the nerve/fascicles. - There are two scenarios represented: "EC" (with electrical conditioning) and "noEC" (without electrical conditioning), indicating different stimulation paradigms. 4. **Selectivity and Inter-fascicular Selectivity:** - Selectivity refers to the ability to preferentially activate one fascicle over others. This is important for targeted stimulation in therapies and devices, like prosthetics or neuro-modulation therapies. - The code calculates selectivity to assess how specific stimulations influence different fascicles, potentially aiming to refine techniques that minimize off-target effects. 5. **Recruitment Differences:** - Differences in recruitment between the two conditions (EC vs. noEC) are evaluated, suggesting a focus on understanding how certain stimulation parameters influence nerve fiber activation thresholds. 6. **Visualization:** - Several plots are generated to visualize fractional recruitment, selectivity, and recruitment differences as a function of electrical pulse amplitude. - These visual representations help in understanding the recruitment dynamics and the effectiveness of different stimulation strategies on nerve activation. ### Key Aspects in the Code - The `names` dictionary provides a biologically meaningful name for each modeled fascicle, which helps interpret the results in a biological context. - `naxons` indicates the number of axons within each nerve or fascicle, crucial for calculating fractional recruitment. - Differences between fascicles' recruitment responses are used to indicate the fascicular selectivity of the electrical stimulation, offering insights into stimulation specificity. In summary, this computational model simulates the recruitment of nerve fibers within a nerve and its fascicles under different conditions of electrical stimulation. It helps in analyzing the specificity of neural activation, which is valuable for developing precise nerve stimulation techniques in clinical and research settings.