A computational study of how a single neuron should adapt its encoding when the statistics of its environment change over time.
Using a one-neuron model with online Bayesian context inference, this project asks how the timing of adaptation, not just the encoding itself, shapes performance. I compare instant, hysteresis, and refractory-lockout switching rules against oracle and static baselines.
A final research project for PHY431, Topics in Biological Physics. The repository holds the simulation and analysis notebook, which reproduces all the figures, the manuscript covering the methods, results and discussion, and the supporting information with supplementary derivations and figures.