The code provided is associated with a computational neuroscience model that focuses on the olfactory network, which is a biological system involved in the sense of smell. Specifically, this code is part of a study analyzing the interactions and dynamics within the insect olfactory system, involving neurons like Projection Neurons (PNs) and Kenyon Cells (KCs) in the mushroom bodies, with a particular focus on the Giant GABAergic Neurons (GGNs).
Olfactory Network:
Projection Neurons (PNs):
Kenyon Cells (KCs):
Giant GABAergic Neurons (GGNs):
plot_ggn_vm
and references to 'Vm'), which might help to understand how these inhibitory cells contribute to the overall network dynamics.Stimulus and Response:
onset
, duration
), which mirrors real biological stimulus conditions used in experiments. This implies exploring how olfactory networks sustain responses over time.Membrane Potential (Vm):
GGN_basal_Vm
, it is a crucial parameter for understanding neuron excitability and synaptic integration. The focus on Vm indicates interest in electrical dynamics over time, which affects neuron firing patterns and network-level communication.This code models the dynamics of the olfactory processing circuitry, particularly focusing on how inputs from sensory neurons are integrated and processed by PNs and KCs and modulated by the inhibitory GGNs. By examining parameters such as spiking activity and membrane potential, the study aims to shed light on the computational properties of olfactory information processing, including stimulus encoding, neural integration, and synaptic interactions. The use of a log-normal distribution for synaptic elements points to a sophisticated approach to mimic biological variability in synaptic strengths or inputs, common in real neural circuits.