The provided code is a computational model that simulates the electrical activity of neurons, particularly focusing on action potential generation and propagation using the Hodgkin-Huxley (H-H) model. The code evaluates the effect of injecting a constant current into neurons and records their spiking activity, displaying it in a raster plot format. ### Biological Basis #### Neuronal Modeling - **Single Compartment Model**: The code is structured to simulate individual neurons as single electrical compartments, which simplifies the geometry and focuses on the dynamic properties of the cell membrane. #### Ion Channels and Membrane Potentials - **Hodgkin-Huxley Model**: This well-known model describes how action potentials in neurons are initiated and propagated. It employs differential equations to represent the ionic currents through sodium (Na) and potassium (K) channels. - **Sodium and Potassium Channels**: The `make_Na_hh_tchan` and `make_K_hh_tchan` functions suggest the presence of voltage-gated sodium and potassium channels. These channels are crucial for spike initiation and the classic rise and fall in membrane voltage during an action potential. - **Equilibrium Potentials**: `ENA = 0.045` and `EK = -0.082` represent the equilibrium potentials for Na\(^+\) and K\(^+\) ions, respectively. These values drive the ionic movement necessary for depolarization and repolarization phases. - **Resting Membrane Potential**: `EREST_ACT = -0.07` indicates the resting membrane potential, a baseline electrical state determined largely by the permeability of the neuronal membrane to K\(^+\) ions. #### Spike Generation - **Spike Generator**: The element `spikegen` is employed with properties such as `thresh` (threshold voltage for spike initiation) and `abs_refract` (absolute refractory period). These are key parameters that determine when a neuron's membrane potential becomes sufficiently depolarized to generate an action potential and the subsequent recovery time. #### Current Injection - **Current Injection**: The code includes a mechanism to inject a specified amount of current (`injcurrent = 0.3e-9` amperes) into each neuron's soma. This simulates external stimuli and is instrumental in eliciting action potentials under controlled conditions. #### Simulation and Spike Recording - **Raster Plot**: The code creates a raster plot to visualize spike trains across multiple neurons (`Ncells = 128`). Raster plots are essential for understanding temporal aspects of neuronal firing and synchronization. - **Spike Time Storage**: Spike times are stored in arrays (`make_time_data_tables`), and output to a file (`make_time_data_file`), providing data equivalent to neural recordings from electrophysiology experiments. ### Conclusion The code provides a computational representation of neuronal action potential mechanisms using a simplified Hodgkin-Huxley framework. By simulating the ionic currents and membrane potentials involved in neuronal excitability, the model sheds light on fundamental neurophysiological processes. This form of modeling is crucial for understanding how neurons process inputs and produce the electrical signals that underlie all neural computation.