Quantifying Population-level Neural Tuning Functions Using Ricker Wavelets and the Bayesian Bootstrap.

Tuning functions are a common way for describing sensory responses, primarily in the visual cortex.The quantification and interpretation of tuning functions has faced computational and conceptual problems.We demonstrated how the Ricker function can be used as a simple and interpretable way for measuring tuning functions.We applied a Ricker function together with a Bayesian Bootstrap approach across a gradient of stimulus features in a generalization conditioning task to characterize visual tuning in the human EEG data.