# Biological Basis of the Code This model code represents passive membrane properties of neuronal dendrites, particularly focusing on both extrasynaptic and synaptic components of membrane conductance. Here’s an explanation of the biological basis of this model: ## Biological Context ### Passive Membrane Properties - **Passive Membrane Channels**: These channels allow ions to flow across the neuronal membrane without active gating, i.e., their permeability is not actively regulated by voltage or ligand binding. They dictate the passive electrical properties of neurons, contributing to the resting membrane potential and the linear integration of synaptic inputs. - **Extrasynaptic Currents (i)**: The `i` current in this model reflects the passive leak conductance across the dendritic membrane, which is determined by ion channels that are constitutively open and generally non-selective to ion type. This reflects the resting properties of the dendrite influenced by constant ion flow, mainly due to leaky potassium channels. - **Synaptic Currents (is)**: The `is` current models tonic (steady-state) activation of synaptic conductance. This is intended to simulate the constant excitation that might occur due to neurotransmitter spillover or persistent synaptic inputs. ### Conductance and Reversal Potentials - **Conductance Parameters**: `g` and `gs` represent the conductance of the extrasynaptic and synaptic channels, respectively, indicating how easily ions can pass through the membrane in each state. - **Reversal Potentials (erev and es)**: `erev` (extrasynaptic reversal potential) is set to -65 mV, which is often representative of the resting potential for neurons, largely influenced by the passive leak channels. `es` (excitatory synaptic reversal potential) is set to 0 mV, typical for excitatory postsynaptic potentials (EPSPs) mediated by receptors like AMPA which primarily allow the flow of sodium (Na+) ions. ## Purpose and Functionality The code aims to simulate a neuron's passive response to consistently activated extrasynaptic and synaptic conductances. It's focused on understanding how continuous excitatory input affects the passive dendritic properties in a computational model. Such models are crucial for exploring the integrative behavior of dendrites in response to synaptic input, contributing to the understanding of synaptic integration and neuronal computational properties. ### Reference to Literature The model is based on the work by Korogod and Kulagina (1998), who studied the integration of synaptic inputs in dendrites under various conditions, emphasizing the importance of dendritic properties in shaping the neuronal outputs. In conclusion, this model provides insight into the passive electrical behavior of dendrites when subjected to continuous synaptic activation, simulating aspects of neuronal behavior that are critical for understanding synaptic integration and neuronal signaling.