The provided code outlines a computational model designed to simulate certain characteristics of inhibitory synapses in the context of neural circuits. It extends the classical biphasic exponential synapse model (Exp2Syn) to capture specific features of inhibitory synapses and their modulation by various interneuron types and external conditions. Below, key biological concepts represented in the model are identified and explained:
Inhibitory synapses are critical in controlling neuronal excitability and shaping the dynamic range and timing of neuronal circuits. This model simulates a synapse where the neurotransmitter receptor leads to inhibition, typically hyperpolarizing the postsynaptic membrane.
tau1
and tau2
tau1
represents the rise time constant, and tau2
the decay time constant, reflecting the duration neurotransmitters remain bound to receptors, affecting synaptic conductance.tau1
and tau2
allows for modeling fast activation and slower deactivation typical of inhibitory receptors beyond simple transmitter-binding kinetics.The model incorporates voltage-dependent outward rectification:
rect(v)
V50
and slope_factor
describe the voltage sensitivity and steepness, respectively, of this modulation.vgat
, sst
, npy
, pv
)vgat
: Associated with the vesicular GABA transporter, indicates GABAergic synapses.sst
: Somatostatin, marking certain inhibitory interneurons.npy
: Neuropeptide Y, often seen in neurons involved in modulation of synaptic transmission.pv
: Parvalbumin, a calcium-binding protein marking fast-spiking interneurons.isOn
AttributeThis computational model captures the essential kinetic and modulatory properties of specific inhibitory synapses, including the molecular identity and voltage-dependent characteristics. These features allow researchers to simulate how various types of inhibitory synapses integrate into neuronal networks, reflecting their roles in regulating neural excitability and information processing in the brain.