Takatoshi Hikida
Papers
1
Total Citations
31
H-Index
1
About
Takatoshi Hikida is a leading neuroscientist whose research illuminates the hierarchical and parallel neural circuits underlying adaptive behavior. His most-cited work, "Parallel and hierarchical neural mechanisms for adaptive and predictive behavioral control" (2021, 31 citations), provides a foundational framework for understanding how the brain orchestrates complex, simultaneous actions through distributed yet coordinated networks. Hikida’s major contributions center on dissecting the cortico-basal ganglia-thalamic loops, revealing how these pathways enable predictive control and behavioral flexibility. By integrating electrophysiological, optogenetic, and computational approaches, he has demonstrated that the brain’s hierarchical organization allows for both specialized processing and parallel information flow—a principle critical for everything from motor learning to decision-making. His work has been widely recognized for bridging systems neuroscience with computational models, offering insights into disorders like Parkinson’s disease and addiction where these circuits malfunction. With a citation impact reflecting the growing importance of circuit-level analysis, Hikida continues to shape our understanding of how neural networks produce adaptive, predictive behavior in real time.
Research Focus
Key Achievements
Top Papers
- 1