<｜begin▁of▁sentence｜>### Instruction:
As an intercultural trainer, you've been tasked with hosting a cross-cultural session concerning scientific communication for a group of neuroscientists. As part of your preparation, one of the key examples you plan to use is how to handle the connectome of a Drosophila larva mushroom body, a critical element in studies about learning and memory. These neuroscientists will need to be coached on how they can successfully import, into the Python environment, the adjacency matrix that represents the connectome obtained via electron microscopy. In addition, you want to highlight the need for potentially accessing the associated cell type labels for every neuron. In this context, what is an effective way of conveying to them how to import the adjacency matrix and optionally recover the neuron's cell type labels?
### Response:
import graspologic

# Load the right Drosophila larva mushroom body connectome
# Optionally, get the cell type labels
adjacency_matrix, labels = graspologic.datasets.load_drosophila_right(return_labels=True)

# Work with the connectome's adjacency matrix and labels
print('Connectome adjacency matrix:\n', adjacency_matrix)
print('Cell type labels:\n', labels)
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