Biological Basis of the Computational Model

The provided code is associated with a computational neuroscience model that simulates neural activity in response to sensory stimulations, specifically focusing on olfactory sensory input and light stimulation. Here's a breakdown of its biological underpinnings:

Olfactory and Light Sensory Inputs

1. Olfactory Sensory Neurons (OSNs):

   • The code references two sets of events (OSN1_events and OSN2_events), potentially representing inputs from olfactory sensory neurons. These neurons are known to respond to odorants and initiate the signal transduction pathway in the olfactory system.
   • The model appears to simulate bursts of activity in these neurons, which can be inferred from the operations using points_per_burst. This suggests a focus on rhythmic or patterned input common in sensory systems.

2. Light Stimulation:

   • Biological systems can include photosensitive elements that respond to light. While the code doesn't directly mention photoreceptors, references to light events (light1_events) and light-induced Poisson rates suggest modeling light-based inputs, possibly akin to optogenetic stimulation.
   • This could be used to mimic experimental conditions where light is used to control neuron firing, providing precise temporal control for studying neural circuits.

Network and Synaptic Behavior

• Theta Rhythm Stimulation (ThetaStim):
  • Theta rhythms are a type of brain wave observed in several brain regions, particularly the hippocampus. Their inclusion suggests a focus on oscillatory neural dynamics, which are critically involved in sensory processing and cognitive functions.
  • The ThetaStim array potentially defines parameters for simulating theta rhythm-based activity influencing OSN or mitral cell behavior.

Neuronal Types and Connectivity

1. Mitral Cells:

   • The term "mitral," mentioned in the context of light stimulation (// for light stimulation of mitral 1), refers to mitral cells, which are a type of neuron in the olfactory bulb. These cells receive direct input from OSNs and are integral to processing olfactory information.
   • The association with light stimulation may hint at the application of optogenetics to study circuitry involving these cells.

2. Granule Cells:

   • References to events like gc1_events1 and gc2_events2 suggest the inclusion of granule cells, which interact with mitral cells through inhibitory synapses. Granule cells contribute to lateral inhibition and odor discrimination capabilities in the olfactory bulb.

Event and Rate-Based Modeling

• Poisson Processes:
  • Poisson distributions are instrumental in modeling random spike events in neuroscience, capturing the stochastic nature of neuronal firing. Here, gen_poisson functions generate Poisson rates for modeling event sequences in mitral cells, whether in response to breath (olfactory) or light stimuli.
  • These rates and spike events are graphically represented, indicating an interest in analyzing spike timing and patterns relative to sensory inputs.

Conclusion

Overall, the code captures key aspects of how sensory events, particularly olfactory and light stimuli, interact with neuronal networks. It models dynamic neuronal responses through structured bursts, rhythm influences, and event-driven inputs, likely serving as a tool to investigate neural circuit behavior under controlled sensory stimulations. The focus appears to be on the olfactory bulb circuitry involving mitral and granule cells, providing insights into sensory processing and neuronal dynamics.