<｜begin▁of▁sentence｜>### Instruction:
Imagine we're in a consultation room and you're discussing the architecture of neural pathways in the human brain. You've brought up the idea of exploring a theoretical model of these pathways that is simple, devoid of complex junctions akin to the chaotic bewilderment we sometimes face in more severe cases of mental disarray.

You're curious about the possibility of creating a neurological network within this simplified model—a network with a total of eight synaptic junctions, mirroring the neat organization seen in less afflicted cognitive structures. You've proposed we conceive a pattern where every synaptic connection avoids creating a sequence that involves more than three neurons in a direct experience.

Using NetworkX, you've asked if we can construct this hypothetical neural cograph, ensuring it doesn't replicate the troubling pathways seen in disorders that involve sequences of four distressful emotional states, and how we might confirm that our conceptual model aligns with the cograph's defining properties. 

Could we delve into this endeavor together and examine the outcome to ascertain its validity as a cograph, indicating a structured and non-chaotic nature of synaptic connections?
### Response:
import networkx as nx

# Generate a random cograph with 2^n nodes
n = 3 # This would create a cograph with 2^3 = 8 nodes
seed = 42
G = nx.random_cograph(n, seed=seed)

# Display the edges of the cograph
print('Edges of the cograph:', G.edges())

# Check if the graph is indeed a cograph (has no path on four vertices)
is_cograph = nx.is_cograph(G)
print('Is the graph a cograph?', is_cograph)
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