Spatio-temporal adaptive penalized splines with application to Neuroscience
Methodology
2017-01-02 v2
Abstract
Data analysed here derive from experiments conducted to study neurons' activity in the visual cortex of behaving monkeys. We consider a spatio-temporal adaptive penalized spline (P-spline) approach for modelling the firing rate of visual neurons. To the best of our knowledge, this is the first attempt in the statistical literature for locally adaptive smoothing in three dimensions. Estimation is based on the Separation of Overlapping Penalties (SOP) algorithm, which provides the stability and speed we look for.
Keywords
Cite
@article{arxiv.1610.06860,
title = {Spatio-temporal adaptive penalized splines with application to Neuroscience},
author = {María Xosé Rodríguez-Álvarez and María Durbán and Dae-Jin Lee and Paul H. C. Eilers},
journal= {arXiv preprint arXiv:1610.06860},
year = {2017}
}