<｜begin▁of▁sentence｜>### Instruction:
As a radiologic technologist specializing in diagnostic imaging, you may encounter scenarios where you need to understand the local community structure around a specific point of interest. For example, imagine a situation where you are tasked with analyzing the neural network of a patient's brain to identify local community structures within the network. In this case, you'll need to apply a community detection algorithm, such as LSWL, to the neural network graph to identify these local communities. Once identified, you may also need to convert the resulting community structure to a JSON representation for further analysis or visualization. This process will help you gain insights into the interconnected regions of the brain and their functional relationships, ultimately contributing to more accurate diagnosis and treatment planning.
### Response:
import networkx as nx
from cdlib import algorithms

# Load the neural network of C. elegans
G = nx.read_gml('celegansneural.gml')

# Apply the LSWL algorithm to find the local community structure
# around a specific query node with default parameters
query_node = list(G.nodes())[0]  # Assuming we are interested in the first node's community
communities = algorithms.lswl(G, query_node=query_node)

# Convert communities to JSON
communities_json = communities.to_json()

print(communities_json)
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