Biological Basis of the Code

The provided code is part of a computational neuroscience model that utilizes the NEST simulator to construct and study layered neural networks. Below, the biological basis of this model is explained.

Neuronal Types

1. Pyramidal Neurons (pyr)

• Biological Role: Pyramidal neurons are the principal excitatory neurons found in various regions of the brain, particularly in the cerebral cortex and hippocampus.
• Function in the Model: In the code, pyramidal neurons are implemented using iaf_neuron models and they're responsible for transferring excitatory signals within and across layers.

2. Interneurons (in)

• Biological Role: Interneurons are inhibitory neurons that modulate the activity of pyramidal neurons, crucial for maintaining the balance of excitation and inhibition within the neural circuit.
• Function in the Model: Just like pyramidal neurons, interneurons are created using iaf_neuron models in the code. These play a crucial role in regulating the activity of excitatory neurons and maintaining network stability.

Network Structure

Layer Organization

• Biological Correlate: The code models two distinct layers of neurons, each representing a small patch of cortical tissue. This is akin to layers found in the mammalian cortex where neurons are organized in a laminar fashion.
• Dimensions and Extent: Each layer is 30x30 neurons, with an extent of 3.0x3.0 in model units. This structured grid represents the spatial organization of neuronal networks in cortical sheets.

Connectivity Patterns

• Biological Correlates: The patterns of connectivity mimic known biological connections:
  • Divergent Connections: Each pyramidal neuron connects to multiple target neurons, either other pyramidal cells or interneurons. This reflects the biological reality where a single neuron often connects to multiple other neurons.
  • Circular Masks: The circular masks that define the connectivity radius are inspired by localized connection patterns seen in the cortex, where neurons are more likely to connect with nearby neurons.

Connectivity Parameters

• Delays and Weights: The delays (1.0 ms) and synaptic weights (1.0) mimic the time it takes for synaptic transmission to occur and the strength of these connections, respectively. These parameters are carefully chosen to replicate biological transmission speeds and strengths.

Visualization

Network Activity

• The visualization part of the code highlights key biological insights by showing:
  • Central Neuron Influence: The spatial reach of a neuron’s influence within the network and its respective targets, demonstrating convergence and divergence of neural pathways.
  • Network Boundaries: Boundaries and the layout of neurons that reflect the organization within a cortical layer.

Conclusion

This code is structured to model a part of cortical networks—specifically focusing on the interaction between excitatory pyramidal neurons and inhibitory interneurons within and across spatially defined layers. By using abstract neuron models and network topology reminiscent of the cerebral cortex, the model seeks to simulate and visualize important aspects of biological neuronal connectivity and information processing.