<｜begin▁of▁sentence｜>### Instruction:
A neuropsychologist, Dr. Smith, is investigating the relationship between brain function and decision-making processes in a group of individuals. As part of the study, she has collected data in the form of 3x3 matrices with boolean values that represent decision-making outcomes under different conditions. Dr. Smith would like to visualize these matrices using a graph-based approach, and she is considering using the igraph library in Python. She's interested in creating a matplotlib plot that depicts the matrices with square cells, a grid, a border, and labeled rows and columns to better understand the decision-making patterns in her research participants.
### Response:
from igraph import Matrix
import matplotlib.pyplot as plt

# Initialize a matrix with boolean values
m = Matrix([[False, True, False], [True, False, True], [False, True, False]])

# Create a plot
fig, ax = plt.subplots()
m.__plot__(context=ax, style='boolean', square=True, grid_width=1, border_width=1, row_names=['A', 'B', 'C'], col_names=['X', 'Y', 'Z'])

# Display the plot
plt.show()
<|EOT|>
