The code snippet provided models an Ohmic potassium (K⁺) current based on the Hodgkin-Huxley type of dynamics used in computational neuroscience to simulate ion channel behavior in neurons. ### Biological Basis 1. **Ion Specificity:** - The model specifically implements a potassium (K⁺) current, which is crucial in neuronal electrophysiology. Potassium channels play a major role in repolarizing the membrane potential following an action potential. 2. **Conductance:** - `gkbar` represents the maximal conductance of the potassium channel. This value dictates how readily potassium ions can flow through the channel when it is open, directly influencing the strength of the potassium current. 3. **Reversal Potential:** - `eO` is set to -90 mV, which approximates the reversal potential for K⁺ in many neurons. This is the potential at which there is no net flow of K⁺ ions through the channel, balancing opposing concentration and electrical gradients. 4. **Ohmic Relationship:** - The model uses an Ohmic equation to describe the current (`iO = gkbar * (v - eO)`). Here, `v` represents the membrane voltage, and the difference `(v - eO)` is the driving force for the K⁺ current. 5. **Purpose:** - The primary goal is to provide a mathematical representation of the potassium ion flow across the neuronal membrane, which is integral for action potential dynamics and the regulation of membrane potential. Potassium currents are vital for numerous neuronal functions, including the generation of action potentials, shaping the action potential, and setting the resting membrane potential. 6. **Context:** - As cited, this model is based on Rubin and Cleland (2006), which suggests an application to specific physiological studies or simulations of neural dynamics. In summary, the code models a simplified K⁺ ion channel that contributes significantly to the electrophysiological properties of neurons by controlling the flow of K⁺ ions across the membrane, thereby influencing neuronal excitability and signaling.