The provided code snippet is from a computational neuroscience model and suggests the use of the "pas" mechanism in a simulation. Here's an explanation of the biological basis:

Passive Membrane Properties

The pas mechanism represents the passive properties of neuronal membranes. This mechanism models the basic, non-activity-dependent electrical characteristics of neurons, focusing primarily on the following aspects:

1. Resting Membrane Conductance:

   • The "pas" implementation introduces a passive leak conductance to the model. This conductance represents ion channels that are always open, allowing ions to flow across the membrane irrespective of other neuronal activities.
   • The leak conductance contributes to setting the resting membrane potential, a critical aspect of neuron physiology that defines the baseline voltage across the neuron's membrane when it is not actively firing.

2. Resting Membrane Potential:

   • The equilibrium potential associated with the leak conductance in "pas" is generally close to the typical resting membrane potential of a neuron (around -65 to -70 mV in many neuron types).
   • This is crucial for maintaining the neuron's readiness to respond to synaptic inputs or generate action potentials.

3. Ohmic Nature:

   • The passive properties are typically modeled using Ohm's Law, where current (I) through the membrane is proportional to the voltage difference (V) between the membrane's inside and outside, minus the resting potential. The proportionality constant is the conductance (G, where I = G*(V - V_rest)).

Biological Role

• Baseline Electrical Activity:
  • Passive properties lay the foundational electrical characteristics of neurons, defining how they integrate synaptic inputs over time and space.
• Homeostasis:
  • By maintaining a stable resting potential, neurons can be poised to respond appropriately to excitatory and inhibitory inputs, thereby being essential for nerve cell homeostasis.
• Modeling Simplicity:
  • In computational models, the "pas" mechanism simplifies the representation of neuronal behavior by providing a baseline electrical activity, allowing the focus to shift towards modeling more complex dynamics like synaptic inputs or action potentials.

In summary, the code introduces a passive mechanism (pas) across all compartments (forall) of the neuronal model, ensuring that each part of the neuron reflects its intrinsic electrical properties that are vital for maintaining resting state and readiness for activity.