September 2015
Volume 15, Issue 12
Free
Vision Sciences Society Annual Meeting Abstract  |   September 2015
Towards a complete forward prediction from visual stimulus to BOLD.
Author Affiliations
  • Mark Schira
    School of Psychology, University of Wollongong Neuroscience Research Australia, Randwick, New South Wales 2031, Australia
  • Peter Robinson
    School of Physics, University of Sydney, New South Wales 2006, Australia Brain Dynamics Center, Sydney Medical School – Western, University of Sydney, Westmead, New South Wales 2145, Australia
  • Michael Breakspear
    The Royal Brisbane and Women's Hospital, Brisbane, Queensland 4029, Australia.
  • Kevin Aquino
    School of Physics, University of Sydney, New South Wales 2006, Australia
Journal of Vision September 2015, Vol.15, 583. doi:https://doi.org/10.1167/15.12.583
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    • Get Citation

      Mark Schira, Peter Robinson, Michael Breakspear, Kevin Aquino; Towards a complete forward prediction from visual stimulus to BOLD.. Journal of Vision 2015;15(12):583. https://doi.org/10.1167/15.12.583.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Functional magnetic resonance imaging (fMRI) has become a standard tool in vision science, and some properties of visual cortex are fairly well understood and modelled, such as retinotopic organisation, contrast response functions and the spatiotemporal Hemodynamic Response Function (stHRF). Here we combine these individual models into a new framework, integrating existing models. The key components are (i) retinal processing; (ii) accurate retino cortical projection (Schira et al 2010); (iii) neural responses; and a (iv) spatiotemporal hemodynamic modeling (Aquino et al. 2012 PLoS CB), combined to a modular toolbox. We argue that the result is greater than the sum of its parts, allowing the complete simulation of fMRI experiments, from visual input (video) to BOLD responses in space and time on an average cortical surface (FS_average) within a few minutes. This supports a number of novel applications. Firstly, exploring interactions between the models and generating exact predictions for a more realistic testing of each of the integrated models. Secondly, a more precise planning of fMRI experiments by generating concrete hypothesis in the space that is actually measured, such as estimating the effect of spatial and temporal interactions between multiple stimulus components. Thirdly, it provides a novel teaching tool, with approximately 5-10 minutes from stimulus video to simulated BOLD responses on a normal desktop computer.

Meeting abstract presented at VSS 2015

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