Range-Limited Scale Stability of Dynamic Direction Representations in a Connectome-Constrained Fly Visual Model
Neuroinformatics 24 (3), 54 · with S. Panwar
About
Nalin studies biological computation through connectome-constrained models, spatial network dynamics, and principles from statistical physics. His work asks which computational properties genuinely follow from biological wiring—and which disappear once initialization, topology, and null-model controls are made comparable.
Across fly visual circuits and spatially embedded directed networks, he investigates scale stability, information efficiency, plasticity, transport, and topological sensitivity.
Research interests
ConnectomicsNetwork dynamicsNeuromorphic AIStatistical physicsInformation theoryBiological learning
Publications
Flow condensation and nonlinear fragility in spatially embedded directed networks
Physica A: Statistical Mechanics and its Applications, 131773 · with S. Panwar
Energy-efficient information processing and eligibility-trace plasticity in the Drosophila optic lobe connectome
Scientific Reports · with S. Panwar