Khitam Aqel / Mathematics / Faculty Mentor: Pedro Maia
Electroconvulsive therapy (ECT) has shown promise in managing acute pain by influencing neural circuits involved in pain perception. However, quantifying the changes in brain connectivity during this process is challenging. Recent advances allow us to build state-space models from high-resolution neural recordings. We applied a computational neurophysiology algorithm to analyze 5-minute LFP recordings from four rodent brain regions across different phases: baseline, acute pain from formalin injection, and ECT at varying intensities. Formalin increased signal complexity, indicating heightened neural processing. Network analysis revealed changes in connectivity metrics, such as expanded network diameter and average path length, along with reduced clustering and assortativity, suggesting a shift to long-range interactions. ECT restored signal complexity to baseline levels and even reversed formalin-induced network expansion, demonstrating its role in stabilizing pain-related neural complexity and reshaping brain connectivity through homeostatic mechanisms.
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