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Computational Methods
Statistical analysis and computational models for linking neural activity to behavior.
We develop and apply computational tools to extract meaning from complex neural datasets. This includes methods for detecting place cells across species, modeling behavioral learning dynamics, and relating single-neuron spiking to local field potential oscillations.
Our approach integrates neural engineering, computational psychiatry, and rigorous statistical inference to connect mechanistic hypotheses to human brain data.