Sign in
NeurosciencebioRxiv
Preprint

Real Time Estimation of Population Receptive Fields Using Gradient Descent

Mario SendeniD

Abstract

A real-time population receptive field mapping procedure based on gradient descent is proposed. Model-free receptive fields produced by the algorithm are evaluated in context of simulated data exhibiting different levels of temporally autocorrelated noise and spatial point spread. As with any model-free approach, the exact shape of receptive fields produced by the real-time algorithm depends on the stimulus. Nevertheless, estimated receptive fields show good correspondence with ground-truth receptive fields in terms of both position and size. Furthermore, fitting a parametric model to the previously obtained estimates approximates the exact shape of the true underlying receptive fields well.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISThielen '19Slater '17Moosavi '26Duncker '23Aoi '17Bhat '21
66% semantic matchNeuroscience
Jordy Thielen, Umut Güçlü, Yağmur Güçlütürk+3 more·bioRxiv·Aug 13, 2019· 11 citations