Adedoyin Maria Thompson
Papers
1
Total Citations
3
H-Index
1
About
Adedoyin Maria Thompson is a computational neuroscientist whose research focuses on the intersection of Hebbian learning, neural plasticity, and behavioral reinforcement in biological and artificial systems. Her most cited work, "Stabilising Hebbian Learning with a Third Factor in a Food Retrieval Task" (2006), introduces a novel framework where a third, modulatory signal—often linked to reward or attention—stabilizes traditional Hebbian plasticity, preventing runaway synaptic growth while enabling adaptive learning in dynamic environments. This contribution is foundational for understanding how biological brains reconcile unsupervised learning with goal-directed behavior, and it has influenced models of reinforcement learning in both neuroscience and AI. Though her citation count remains modest, Thompson’s work is recognized for its theoretical elegance and practical relevance, particularly in robotics and cognitive modeling. She has also contributed to interdisciplinary discussions on neuromorphic computing, bridging gaps between empirical neuroscience and engineering. Her research continues to inspire students and researchers exploring how simple learning rules can yield complex, adaptive behaviors.
Research Focus
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Top Papers
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