<｜begin▁of▁sentence｜>### Instruction:
In the context of assessing neural pathways within a chiropractic framework, let's imagine we're looking at a simplified model of spinal nerve connections. Here we have a network where the base vertebra, labeled as '1', has direct influence over two subsequent vertebrae, which are labeled '2' and '3'. Each of these, in turn, has a pathway to the final vertebra in this model, labeled as '4'.

Could you evaluate the influence of the base vertebra '1', in terms of its capacity to affect the condition of other vertebrae in this model? Specifically, consider the proportion of vertebrae within this network that can be reached starting from the base vertebra '1'. How would you determine this measure of localized influence or 'health effect capacity', within the modeled neural network of the spine?
### Response:
import networkx as nx

# Create a directed graph
G = nx.DiGraph()

# Add edges to the graph
G.add_edges_from([(1, 2), (1, 3), (2, 4), (3, 4)])

# Calculate local reaching centrality for node 1
lrc = nx.local_reaching_centrality(G, 1)
print(f'Local reaching centrality for node 1: {lrc}')
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