<｜begin▁of▁sentence｜>### Instruction:
As a neuropsychologist, you're investigating the dynamics of brain function in a network of interconnected neurons. Suppose you're conducting a study where you've simulated a brain network using the Erdos-Renyi model with 500 neurons and a connection probability of 0.3. Now, you're interested in sampling a subset of this network while retaining edges that exhibit an induction step. This is akin to observing how certain neural connections evolve or strengthen over time due to repeated activation.

To achieve this, you may utilize the RandomEdgeSamplerWithInduction method, which is a tool that allows you to extract a subset of connections from your simulated brain network while specifically focusing on those edges that display an induction step - indicating a significant increase in connectivity strength or activity level between neurons. 

Could you rephrase the question considering this context?
### Response:
import networkx as nx
from littleballoffur import RandomEdgeSamplerWithInduction

G = nx.gnp_random_graph(n=500, p=0.3)

sampler = RandomEdgeSamplerWithInduction()

sampler_G = sampler.sample(G)

print(sampler_G)
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