David Darrow

This paper introduces a foraging-theory-based model that better captures human behavioral diversity in sequential decision-making compared to traditional value-comparison models.

The paper shows that human exploration behavior follows a U-shaped pattern with the ratio of volatility to stochasticity in uncertain environments, with optimal performance at intermediate uncertainty ratios.

The paper identifies a dominant nonlinear axis of individual variability in decision-making tasks, showing that exploration tendency, rather than personality or learning parameters, drives differences in performance.

This study identifies distinct computational mechanisms of uncertainty processing in anxiety and apathy, showing how they influence exploratory behaviors through different perceptions of volatility and stochasticity.

This paper introduces a flexible multi-step hypothesis testing method using cluster-based permutation tests with LMEs and GLMEs to analyze human ECoG data, improving statistical power and accounting for random effects.

The paper identifies a low-dimensional behavioral manifold that captures exploration-exploitation decision-making and links it to symptoms of apathy and anxiety.

This study demonstrates real-time control of pallidal oscillations in Parkinson's disease using evoked interference deep brain stimulation (eiDBS) to suppress or amplify beta band activity.