Extremely fast pRF mapping for real-time applications

Salil Bhat*, Michael Lührs*, Rainer Goebel*, Mario Senden*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Population receptive field (pRF) mapping is a popular tool in computational neuroimaging that allows for the investigation of receptive field properties, their topography and interrelations in health and disease. Furthermore, the possibility to invert population receptive fields provides a decoding model for constructing stimuli from observed cortical activation patterns. This has been suggested to pave the road towards pRF-based brain-computer interface (BCI) communication systems, which would be able to directly decode internally visualized letters from topographically organized brain activity. A major stumbling block for such an application is, however, that the pRF mapping procedure is computationally heavy and time consuming. To address this, we propose a novel and fast pRF mapping procedure that is suitable for real-time applications. The method is built upon hashed-Gaussian encoding of the stimulus, which tremendously reduces computational resources. After the stimulus is encoded, mapping can be performed using either ridge regression for fast offline analyses or gradient descent for real-time applications. We validate our model-agnostic approach in silico, as well as on empirical fMRI data obtained from 3T and 7T MRI scanners. Our approach is capable of estimating receptive fields and their parameters for millions of voxels in mere seconds. This method thus facilitates real-time applications of population receptive field mapping.

Original languageEnglish
Article number118671
Number of pages14
JournalNeuroimage
Volume245
Early online date26 Oct 2021
DOIs
Publication statusE-pub ahead of print - 26 Oct 2021

Keywords

  • AREAS
  • ATTENTION
  • CORTICAL MAGNIFICATION FACTOR
  • HUMAN VISUAL-CORTEX
  • HUMANS
  • IMAGES
  • MAPS
  • Population receptive field mapping
  • RECEPTIVE-FIELD SIZE
  • Real-time fMRI
  • SIGNAL
  • STRIATE
  • Stimulus encoding
  • Vision

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