The provided code is part of a computational neuroscience model intended to simulate key aspects of olfactory processing within the brain, particularly the interactions between olfactory sensory neurons (OSNs), mitral cells, and granule cells within the olfactory bulb.

Biological Basis

Olfactory Bulb Functionality

1. Olfactory Sensory Neurons (OSNs):
   The code models the input from OSNs, which are responsible for detecting odorants in the nasal cavity and transmitting signals to the brain. In the model, OSNs are represented as ThetaStim objects, which simulate the rhythmic bursting activity associated with the natural breathing cycle.

2. Mitral Cells:
   Mitral cells are a type of excitatory neuron found in the olfactory bulb. They receive input from OSNs at their dendritic tufts, process this sensory information, and transmit it to other areas of the brain. In this model, two mitral cells (m1 and m2) are instantiated, capturing the notion of parallel processing channels in the olfactory system.

3. Granule Cells:
   Granule cells are inhibitory interneurons within the olfactory bulb that primarily form dendrodendritic synapses with mitral cells. They provide feedback inhibition to mitral cells, which is crucial for modulating signal transmission and for setting up the dynamic range and specificity of odor detection.

Synaptic Interactions

• Excitatory Connections:

  • OSNs provide excitatory input to mitral cells via glutamatergic synapses represented in the code by AmpaNmda objects. These reflect the dual-component excitation involving AMPA and NMDA-type glutamate receptors, which are critical for synaptic transmission and plasticity.

• Inhibitory Connections:

  • Granule cells inhibit mitral cells through GABAergic synapses, modeled as FastInhib objects. This synaptic inhibition plays a critical role in feedback and lateral inhibition within the olfactory bulb, shaping the temporal dynamics and gain control of sensory processing.

Stimulus Representation

• Stimuli Types:
  • The code distinguishes between different types of stimuli (e.g., OSN input representing breathing cycles and light stimuli) to model the temporal dynamics of sensory processing in response to different environmental cues.
  • Background Activity: Baseline, random spiking activity is modeled using NetStim, reflecting spontaneous activity in the absence of specific sensory inputs.

Graphical User Interface (GUI)

The code also includes sections for controlling and visualizing the model's input parameters and responses, allowing users to manipulate stimulus features like frequency, onset, and noise to explore different sensory processing scenarios.

Conclusion

Overall, the model replicates biological interactions in the olfactory bulb through a network of simulated neurons, capturing both excitatory and inhibitory synaptic dynamics. It allows for the exploration of how sensory information is integrated and processed in the brain, specifically within the context of olfactory perception. The biophysical basis, grounded in neuron types and receptor activity, makes it a useful tool for understanding sensory processing dynamics.