<｜begin▁of▁sentence｜>### Instruction:
Imagine you're deep-diving into the psyche of an individual represented by a directed graph, with each node characterizing a critical psychological state or event, and the edges between them symbolizing the transition from one state to another. You have recorded transitions as follows: from state 0 to state 1, state 1 to state 2, state 2 to state 3, and then a loop back from state 3 to state 1, representing a recurring pattern in the individual's behavior.

To unravel the sequence of psychological states and their transitions, starting from the initial state 0, you would meticulously trace the path in the style of an edge-based depth-first exploration. Could you illustrate how this reflective probe can be conducted using the concepts of NetworkX, akin to how one might trace the steps in an intricate criminal mind?
### Response:
import networkx as nx

G = nx.DiGraph()

G.add_edges_from([(0, 1), (1, 2), (2, 3), (3, 1)])

edges_dfs_list = list(nx.edge_dfs(G, source=0))

print('Edge DFS:', edges_dfs_list)
<|EOT|>
