## Biological Basis of the Code The provided code is a computational model simulating the process of neuronal signaling, focusing on how somatic stimulation and proximal inhibition affect the backpropagation of action potentials (bAPs) in neurons. bAPs are action potentials that propagate from the soma back into the dendrites, important for synaptic plasticity and neural computations. ### Key Biological Concepts Modeled in the Code 1. **Somatic Stimulation:** - The code delivers a depolarizing current injection at the soma to initiate action potentials. This mimics an experimental setup where neurons are directly stimulated at the soma to observe their electrophysiological properties. - The parameter `POST_AMP` defines the amplitude of the injected current, a proxy for how strong the stimulus is. 2. **Backpropagating Action Potentials (bAPs):** - These are action potentials that travel from the soma back into dendrites. bAPs influence synaptic strength and plasticity, playing a key role in learning and memory. - The recordings of membrane potential at various dendritic locations allow studying how bAPs propagate through the dendritic tree and how they are affected by different factors. 3. **Proximal Inhibition:** - The code models the effects of inhibitory synapses proximal to the soma. This inhibition can modulate the amplitude and propagation of bAPs. - The parameter `shunt_weights` represents the strength of inhibitory input. Inhibition can decrease the amplitude of bAPs, affecting neurotransmission and synaptic plasticity. 4. **Synapses and Distributed Inhibition:** - The implementation of “distributed” inhibition provides insights into more realistic scenarios where synapses are not localized but dispersed along a dendrite. - Parameters such as `shunt_delay`, `shunt_number`, and `shunt_sigma` model the temporal and spatial characteristics of inhibition. 5. **Ionic Currents:** - The code records ionic currents, particularly sodium (`_ref_ina`) and potassium (`_ref_ik`), which are fundamental in generating and propagating action potentials. - This highlights how different ionic conductances influence neuronal excitability and response to synaptic inputs. 6. **Dendritic Integration:** - Recording voltages at multiple dendritic compartments provides insights into how electrical signals integrate along the dendrite, shedding light on the electrical properties and computational capabilities of neurons. ### Conclusion This code implements a model that allows for the exploration of how somatic injections and proximal inhibitory inputs can influence the dynamics of bAPs in neurons. Through simulation, it captures fundamental aspects of neuronal function and synaptic transmission, specifically focusing on the role of inhibition and its spatial distribution in modifying signal propagation within the dendritic architecture.